812 files changed, 73058 insertions, 0 deletions

diff --git a/SD-VBS/benchmarks/Makefile b/SD-VBS/benchmarks/Makefile
new file mode 100644
index 0000000..bc40226
--- /dev/null
+++ b/SD-VBS/benchmarks/Makefile
@@ -0,0 +1,10 @@
+include ../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
+
+#P := './preload'
+#preloading: 
+#       @echo Preloading...
+#       @find ./ -iname "*.bmp" -exec sh -c '$(P) {} &' \; 
+#       @kill -2 `pgrep preload`
+
diff --git a/SD-VBS/benchmarks/disparity/Makefile b/SD-VBS/benchmarks/disparity/Makefile
new file mode 100644
index 0000000..383f747
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/Makefile
@@ -0,0 +1,5 @@
+include ../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
+
+
diff --git a/SD-VBS/benchmarks/disparity/data/Makefile b/SD-VBS/benchmarks/disparity/data/Makefile
new file mode 100644
index 0000000..61efc60
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/Makefile
@@ -0,0 +1,4 @@
+include ../../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
+
diff --git a/SD-VBS/benchmarks/disparity/data/cif/1.bmp b/SD-VBS/benchmarks/disparity/data/cif/1.bmp
new file mode 100644
index 0000000..42b9fcd
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/cif/1.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/cif/2.bmp b/SD-VBS/benchmarks/disparity/data/cif/2.bmp
new file mode 100644
index 0000000..a3c393a
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/cif/2.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/cif/Makefile b/SD-VBS/benchmarks/disparity/data/cif/Makefile
new file mode 100644
index 0000000..c895ee4
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/cif/Makefile
@@ -0,0 +1,7 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=disparity
+INPUT=cif
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/disparity/data/cif/disparity b/SD-VBS/benchmarks/disparity/data/cif/disparity
new file mode 100755
index 0000000..96cab8c
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/cif/disparity
diff --git a/SD-VBS/benchmarks/disparity/data/cif/expected.m b/SD-VBS/benchmarks/disparity/data/cif/expected.m
new file mode 100644
index 0000000..beb8f9e
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/cif/expected.m
@@ -0,0 +1,288 @@
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+0       0       0       1       2       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       5       4       4       4       4       4       3       3       3       3       3       3       3       3       3       4       3       3       3       3       3       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       2       4       4       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       4       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       4       4       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       2       2       3       3       3       3       3       3       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       2       3       2       3       3       3       3       0       0       0       0       
+0       0       0       1       2       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       3       4       4       3       4       4       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       4       4       4       7       7       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       4       4       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       6       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       2       2       3       3       3       3       3       3       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       2       3       3       3       3       0       0       0       0       
+0       0       0       1       2       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       3       4       5       4       4       4       4       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       4       4       4       5       7       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       4       4       2       3       2       2       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       2       2       3       3       3       3       3       3       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       
+0       0       0       1       2       3       4       4       4       4       4       4       4       4       4       5       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       16      4       4       4       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       4       4       4       7       7       7       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       2       2       3       3       3       3       3       3       3       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       
+0       0       0       1       2       3       4       5       5       5       3       3       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       3       4       4       4       4       3       3       4       4       2       3       3       8       4       4       4       4       4       4       4       4       4       20      4       4       4       4       4       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       4       4       4       4       7       7       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       3       2       2       2       2       2       2       2       2       2       2       2       2       2       0       1       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       2       2       3       3       3       3       3       3       3       2       2       2       2       2       2       2       2       2       3       2       3       3       3       3       3       3       3       2       3       3       3       3       0       0       0       0       
+0       0       0       1       1       2       4       5       5       5       3       3       3       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       51      50      53      52      54      54      63      59      57      12      14      14      15      62      9       9       8       8       21      22      24      25      25      11      4       4       4       4       4       4       4       4       4       20      4       5       4       4       4       4       4       4       4       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       42      3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       4       4       4       7       7       7       8       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       3       2       3       2       2       2       2       2       2       2       2       2       2       2       0       1       1       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       3       2       3       2       2       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       2       3       2       3       3       3       3       3       3       3       2       3       3       3       3       0       0       0       0       
+0       0       0       1       1       2       4       5       4       3       3       3       3       3       4       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       59      59      53      53      63      63      63      59      57      62      62      62      62      62      63      63      7       20      21      0       24      24      25      11      4       4       4       4       4       4       4       4       4       20      4       5       3       16      5       4       3       3       3       3       3       3       3       3       4       3       3       3       3       3       3       3       3       3       3       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       4       3       4       5       7       7       8       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       7       7       2       2       2       2       2       2       2       2       2       2       2       2       2       0       1       1       2       2       2       2       2       11      11      3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       3       3       3       3       3       3       2       2       3       3       2       2       2       2       2       2       2       2       2       3       2       3       3       3       3       3       2       2       2       3       3       3       3       0       0       0       0       
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diff --git a/SD-VBS/benchmarks/disparity/data/cif/preload b/SD-VBS/benchmarks/disparity/data/cif/preload
new file mode 100755
index 0000000..b2e70fc
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/cif/preload
diff --git a/SD-VBS/benchmarks/disparity/data/fullhd/1.bmp b/SD-VBS/benchmarks/disparity/data/fullhd/1.bmp
new file mode 100644
index 0000000..a2aa1f1
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/fullhd/1.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/fullhd/2.bmp b/SD-VBS/benchmarks/disparity/data/fullhd/2.bmp
new file mode 100644
index 0000000..a1b5955
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/fullhd/2.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/fullhd/Makefile b/SD-VBS/benchmarks/disparity/data/fullhd/Makefile
new file mode 100644
index 0000000..a9d45fe
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/fullhd/Makefile
@@ -0,0 +1,7 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=disparity
+INPUT=fullhd
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/disparity/data/fullhd/disparity b/SD-VBS/benchmarks/disparity/data/fullhd/disparity
new file mode 100755
index 0000000..2b01bc0
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/fullhd/disparity
diff --git a/SD-VBS/benchmarks/disparity/data/fullhd/preload b/SD-VBS/benchmarks/disparity/data/fullhd/preload
new file mode 100755
index 0000000..b2e70fc
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/fullhd/preload
diff --git a/SD-VBS/benchmarks/disparity/data/qcif/1.bmp b/SD-VBS/benchmarks/disparity/data/qcif/1.bmp
new file mode 100644
index 0000000..fdc8981
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/qcif/1.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/qcif/2.bmp b/SD-VBS/benchmarks/disparity/data/qcif/2.bmp
new file mode 100644
index 0000000..d002847
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/qcif/2.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/qcif/Makefile b/SD-VBS/benchmarks/disparity/data/qcif/Makefile
new file mode 100644
index 0000000..5f02708
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/qcif/Makefile
@@ -0,0 +1,15 @@
+find-dir-with = $(shell /usr/bin/perl -e 'chomp($$_ = `pwd`); while ($$_ ne "" && ! -e "$$_/$(1)") { m:(.*)/[^/]+/??:; $$_ = $$1; } print;')
+
+# define canonical directories in starsearch
+ifndef TOP_DIR
+  export TOP_DIR := $(call find-dir-with,.SD-VBS)
+endif
+
+export MAKEFILE_COMMON_DIR=$(TOP_DIR)/common/makefiles
+
+
+BMARK=disparity
+INPUT=qcif
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/disparity/data/qcif/disparity b/SD-VBS/benchmarks/disparity/data/qcif/disparity
new file mode 100755
index 0000000..2bab8bf
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/qcif/disparity
diff --git a/SD-VBS/benchmarks/disparity/data/qcif/expected.m b/SD-VBS/benchmarks/disparity/data/qcif/expected.m
new file mode 100644
index 0000000..028b71a
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/qcif/expected.m
@@ -0,0 +1,154 @@
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diff --git a/SD-VBS/benchmarks/disparity/data/sim/1.bmp b/SD-VBS/benchmarks/disparity/data/sim/1.bmp
new file mode 100644
index 0000000..1fc5da9
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sim/1.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/sim/2.bmp b/SD-VBS/benchmarks/disparity/data/sim/2.bmp
new file mode 100644
index 0000000..c19a7fc
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sim/2.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/sim/Makefile b/SD-VBS/benchmarks/disparity/data/sim/Makefile
new file mode 100644
index 0000000..1b64583
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sim/Makefile
@@ -0,0 +1,6 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=disparity
+INPUT=sim
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/disparity/data/sim/disparity b/SD-VBS/benchmarks/disparity/data/sim/disparity
new file mode 100755
index 0000000..0f4c3d7
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sim/disparity
diff --git a/SD-VBS/benchmarks/disparity/data/sim/expected.m b/SD-VBS/benchmarks/disparity/data/sim/expected.m
new file mode 100644
index 0000000..9ca59f4
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sim/expected.m
@@ -0,0 +1,54 @@
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+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       0       1       1       1       1       2       2       2       2       2       2       1       1       1       2       2       3       2       2       2       2       2       1       1       1       0       0       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       1       1       1       1       1       2       1       2       1       2       1       2       2       2       3       3       1       1       2       2       2       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       2       2       1       1       1       1       1       2       2       2       1       1       1       1       1       2       3       3       1       1       1       1       2       2       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       2       2       2       2       2       3       2       2       1       1       1       1       1       1       1       2       1       1       1       1       1       1       2       2       3       1       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       0       0       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       2       2       2       2       2       2       2       1       1       2       1       2       1       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       5       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       2       2       2       2       2       2       1       1       1       1       1       2       1       1       2       1       1       1       1       1       1       1       2       1       1       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       5       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       0       2       1       1       1       2       2       2       2       2       1       1       1       2       1       1       2       1       1       1       1       1       2       1       2       1       1       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       5       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       2       2       2       2       2       1       1       0       1       2       2       1       2       1       1       1       1       1       2       2       2       1       1       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       6       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       2       2       2       2       1       1       1       0       2       2       2       2       1       1       1       1       1       1       2       1       1       1       1       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       6       7       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       1       1       1       1       2       2       2       2       2       1       1       1       2       1       2       1       1       1       0       1       2       2       2       1       1       1       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       0       2       1       1       1       2       2       2       1       1       7       2       2       2       2       1       1       1       2       2       2       2       1       1       6       1       1       2       2       1       1       1       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       1       1       2       1       1       1       1       1       2       2       2       1       2       1       1       1       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       1       1       1       1       1       1       2       2       2       2       1       2       2       1       0       2       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       2       2       2       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       2       3       0       1       1       1       1       1       1       1       1       1       2       1       1       1       1       1       1       1       1       2       2       2       2       1       2       2       1       0       2       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       6       2       2       2       2       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       1       1       2       1       1       0       2       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       6       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       1       1       1       1       1       1       1       1       1       0       1       1       1       5       1       1       1       2       2       2       2       1       2       1       1       0       2       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       3       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       1       1       1       1       1       1       1       1       1       1       1       1       1       3       1       1       1       1       2       2       2       1       2       2       1       0       2       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       1       1       1       1       1       1       1       1       1       0       1       1       1       3       1       1       1       1       2       1       2       1       2       2       2       0       2       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       5       1       1       1       1       1       1       2       1       2       7       1       0       2       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       2       7       1       0       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       7       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       2       7       2       0       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       7       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       6       1       2       7       2       0       2       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       7       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       6       1       2       7       2       0       2       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       7       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       3       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       6       1       2       2       2       0       2       1       1       1       0       0       0       
diff --git a/SD-VBS/benchmarks/disparity/data/sim_fast/1.bmp b/SD-VBS/benchmarks/disparity/data/sim_fast/1.bmp
new file mode 100644
index 0000000..f86d4df
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sim_fast/1.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/sim_fast/2.bmp b/SD-VBS/benchmarks/disparity/data/sim_fast/2.bmp
new file mode 100644
index 0000000..79704c3
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sim_fast/2.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/sim_fast/Makefile b/SD-VBS/benchmarks/disparity/data/sim_fast/Makefile
new file mode 100644
index 0000000..f206525
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sim_fast/Makefile
@@ -0,0 +1,5 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=disparity
+INPUT=sim_fast
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
diff --git a/SD-VBS/benchmarks/disparity/data/sim_fast/disparity b/SD-VBS/benchmarks/disparity/data/sim_fast/disparity
new file mode 100755
index 0000000..342a31e
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sim_fast/disparity
diff --git a/SD-VBS/benchmarks/disparity/data/sim_fast/expected.m b/SD-VBS/benchmarks/disparity/data/sim_fast/expected.m
new file mode 100644
index 0000000..68538c1
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sim_fast/expected.m
@@ -0,0 +1,48 @@
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       3       3       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       0       1       0       0       0       0       1       0       1       0       0       0       
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+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       0       0       0       0       0       0       0       0       
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+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       1       1       1       1       1       1       1       1       2       2       1       1       1       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       3       0       0       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       1       2       2       3       2       2       2       2       2       3       0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       3       0       0       
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+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       2       2       2       2       2       2       3       2       2       2       2       2       1       1       1       2       2       1       1       1       1       1       1       1       1       1       1       1       1       0       0       0       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       1       1       1       1       1       2       2       2       1       1       1       2       2       2       2       2       2       3       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       1       1       1       1       2       2       2       2       2       1       1       2       2       2       2       2       2       3       2       3       2       2       2       2       2       2       2       1       1       1       1       1       2       2       2       3       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       1       2       2       2       2       1       2       1       1       1       1       1       2       2       2       2       2       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       1       1       1       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       0       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       0       1       1       1       2       1       1       1       1       1       1       1       1       2       3       1       1       2       2       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       2       2       2       1       1       0       0       
+0       1       1       1       1       1       1       1       0       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       1       1       2       1       1       0       0       
+0       1       1       1       1       1       1       0       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       0       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       3       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       1       0       1       1       1       1       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       2       1       1       0       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       1       2       2       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       1       1       2       1       0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       2       1       1       0       2       1       1       0       0       0       
+0       1       1       1       1       1       1       1       1       1       2       2       2       2       1       1       1       2       2       2       2       1       2       2       2       2       2       2       2       1       1       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       2       1       1       0       2       1       1       0       0       0       
+0       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       2       1       1       0       2       1       1       0       0       0       
+0       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       0       1       1       1       1       0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       0       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       0       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       0       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       2       2       2       0       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       0       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       2       2       2       0       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       2       2       2       0       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       1       1       1       0       0       0       
+0       1       1       1       1       1       1       1       2       2       2       0       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       1       1       1       0       0       0       
diff --git a/SD-VBS/benchmarks/disparity/data/sqcif/1.bmp b/SD-VBS/benchmarks/disparity/data/sqcif/1.bmp
new file mode 100644
index 0000000..9b0b8dd
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sqcif/1.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/sqcif/2.bmp b/SD-VBS/benchmarks/disparity/data/sqcif/2.bmp
new file mode 100644
index 0000000..b831359
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sqcif/2.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/sqcif/Makefile b/SD-VBS/benchmarks/disparity/data/sqcif/Makefile
new file mode 100644
index 0000000..54160bc
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sqcif/Makefile
@@ -0,0 +1,8 @@
+include ../../../../common/makefiles/Makefile.include
+
+INPUT=sqcif
+BMARK=disparity
+
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/disparity/data/sqcif/disparity b/SD-VBS/benchmarks/disparity/data/sqcif/disparity
new file mode 100755
index 0000000..2bab8bf
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sqcif/disparity
diff --git a/SD-VBS/benchmarks/disparity/data/sqcif/expected.m b/SD-VBS/benchmarks/disparity/data/sqcif/expected.m
new file mode 100644
index 0000000..6581f99
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/sqcif/expected.m
@@ -0,0 +1,96 @@
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       25      25      25      29      6       6       6       29      2       2       1       29      26      26      26      26      2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       2       2       2       2       0       0       0       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       25      25      25      25      6       6       6       29      2       2       1       29      26      4       26      26      2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       2       2       2       0       0       0       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       25      25      25      25      29      6       6       29      2       2       1       29      4       4       26      26      2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       2       2       2       2       2       0       0       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       25      25      25      25      29      6       6       29      2       2       29      29      4       4       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       2       2       1       2       2       2       2       2       2       2       2       2       0       2       2       2       0       2       0       0       0       0       0       0       0       0       2       2       2       2       0       0       0       0       0       0       0       0       
+1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       25      25      25      29      29      6       6       29      2       2       29      29      4       4       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       2       2       2       2       0       0       0       0       0       0       0       
+1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       6       6       6       2       2       1       29      4       4       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       2       2       2       2       2       2       1       2       1       1       1       1       2       2       1       2       2       2       2       2       2       2       2       2       3       3       3       2       2       0       0       0       0       0       0       0       0       0       2       2       2       0       0       0       0       0       0       0       0       0       
+1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       4       4       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       4       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       0       0       4       0       2       6       2       2       0       0       0       0       0       0       0       0       0       0       2       2       2       2       2       0       0       0       0       0       0       
+1       1       1       1       2       2       2       2       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       1       2       2       2       2       1       2       2       2       2       1       4       4       4       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       0       0       0       0       0       2       2       2       2       2       2       2       2       2       0       0       0       0       2       2       2       2       2       2       0       0       0       0       0       
+1       1       1       1       2       2       2       2       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       1       2       1       2       2       1       2       2       2       2       1       4       4       4       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       2       2       2       3       2       2       2       2       2       2       2       0       0       2       2       2       0       0       0       0       0       0       0       0       0       
+0       0       0       1       2       2       2       2       1       1       1       2       2       2       2       2       2       2       2       1       1       1       1       1       1       2       2       1       2       2       2       2       2       2       2       2       2       1       2       1       2       1       1       2       2       2       1       1       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       1       1       1       2       2       2       2       2       2       2       2       1       1       1       1       1       1       2       2       1       2       2       2       2       2       2       2       2       2       1       1       1       2       1       1       2       2       2       1       1       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       1       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       0       0       0       0       
+0       0       0       1       2       2       2       2       1       1       1       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       2       2       2       1       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       1       2       2       1       2       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       1       1       1       2       1       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       1       2       1       1       1       1       2       1       1       2       2       2       2       1       2       2       1       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       1       1       1       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       2       2       2       1       1       1       1       2       1       1       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       1       1       1       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       5       5       5       5       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       2       2       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       5       5       5       2       2       8       8       8       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       
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+0       0       0       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       2       2       2       2       2       2       2       2       2       2       2       2       3       4       4       4       4       4       4       4       3       3       4       4       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       1       1       1       1       2       1       2       1       2       2       2       2       2       2       3       3       3       3       3       3       3       1       1       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       2       1       2       1       2       2       0       0       0       0       0       
+0       0       0       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       2       2       2       2       2       3       3       3       4       3       3       3       3       4       4       3       3       3       3       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       1       1       1       1       1       1       1       1       1       1       1       2       2       2       3       3       3       3       3       3       1       1       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       1       2       2       2       2       0       0       0       0       0       
+0       0       0       1       1       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       2       2       2       2       3       3       3       4       4       4       4       4       4       4       3       3       3       3       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       1       1       1       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       1       2       2       2       1       1       1       2       2       1       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       2       3       4       4       4       3       3       4       4       4       4       4       4       4       3       3       3       3       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       4       4       4       4       3       1       2       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       1       2       2       2       1       1       1       2       1       1       1       2       2       15      3       3       3       4       4       4       4       3       3       3       3       2       3       4       4       4       4       4       4       4       4       4       4       4       4       3       3       3       4       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       4       4       4       4       4       4       1       2       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       2       0       0       0       0       
+0       0       0       1       2       2       2       2       1       1       1       2       1       1       1       2       2       15      4       4       4       4       4       4       4       3       3       3       3       3       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       3       4       4       3       3       3       3       4       3       3       4       4       4       3       3       3       3       3       4       4       4       4       4       4       4       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       1       1       2       3       6       4       4       4       4       4       4       4       4       3       3       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       3       4       4       3       3       3       3       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       2       2       2       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       1       1       2       3       6       4       4       4       4       4       4       4       4       3       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       1       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       1       1       2       5       6       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       2       3       3       3       3       3       3       3       2       2       2       2       2       2       2       2       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       1       1       2       3       6       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       1       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       2       3       3       3       3       3       3       3       2       2       2       2       2       2       2       2       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       1       1       2       3       5       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       1       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       2       3       3       3       3       3       3       3       2       2       2       2       2       2       2       2       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       1       2       2       2       2       3       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       2       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       3       15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       3       13      4       4       4       4       4       4       0       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       4       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       3       15      3       4       4       4       4       4       0       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       3       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       3       15      3       4       4       4       4       4       0       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       3       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       3       15      3       3       3       4       4       4       0       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       4       3       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       3       15      13      3       3       4       4       4       0       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       3       3       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       3       15      13      4       4       4       4       4       0       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       3       4       4       4       4       4       4       4       3       1       2       2       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       2       2       2       2       2       2       2       0       0       0       0       0       
diff --git a/SD-VBS/benchmarks/disparity/data/test/1.bmp b/SD-VBS/benchmarks/disparity/data/test/1.bmp
new file mode 100644
index 0000000..3da018c
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/test/1.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/test/2.bmp b/SD-VBS/benchmarks/disparity/data/test/2.bmp
new file mode 100644
index 0000000..88b3918
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/test/2.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/test/Makefile b/SD-VBS/benchmarks/disparity/data/test/Makefile
new file mode 100644
index 0000000..06e43ae
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/test/Makefile
@@ -0,0 +1,6 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=disparity
+INPUT=test
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/disparity/data/test/disparity b/SD-VBS/benchmarks/disparity/data/test/disparity
new file mode 100755
index 0000000..b0f0e1b
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/test/disparity
diff --git a/SD-VBS/benchmarks/disparity/data/test/expected.m b/SD-VBS/benchmarks/disparity/data/test/expected.m
new file mode 100644
index 0000000..9ddac84
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/test/expected.m
@@ -0,0 +1,10 @@
+0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       
diff --git a/SD-VBS/benchmarks/disparity/data/vga/1.bmp b/SD-VBS/benchmarks/disparity/data/vga/1.bmp
new file mode 100644
index 0000000..fc8f89a
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/vga/1.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/vga/2.bmp b/SD-VBS/benchmarks/disparity/data/vga/2.bmp
new file mode 100644
index 0000000..8f08c5e
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/vga/2.bmp
diff --git a/SD-VBS/benchmarks/disparity/data/vga/Makefile b/SD-VBS/benchmarks/disparity/data/vga/Makefile
new file mode 100644
index 0000000..40662ea
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/vga/Makefile
@@ -0,0 +1,7 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=disparity
+INPUT=vga
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/disparity/data/vga/disparity b/SD-VBS/benchmarks/disparity/data/vga/disparity
new file mode 100755
index 0000000..2bab8bf
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/vga/disparity
diff --git a/SD-VBS/benchmarks/disparity/data/vga/expected.m b/SD-VBS/benchmarks/disparity/data/vga/expected.m
new file mode 100644
index 0000000..65f7e72
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/data/vga/expected.m
@@ -0,0 +1,480 @@
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+0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       3       3       3       2       2       2       2       2       2       2       3       3       3       4       4       13      14      14      14      6       7       8       9       2       3       2       2       2       2       2       2       2       3       3       3       3       3       3       4       4       3       3       4       22      22      22      22      22      21      21      2       2       2       2       2       1       1       2       2       2       2       3       5       6       6       7       7       11      12      12      12      12      0       1       1       2       2       2       2       2       2       2       3       3       3       2       3       3       4       4       46      4       39      39      39      39      3       0       0       0       3       4       28      36      8       9       9       9       9       3       3       3       4       4       5       5       8       9       9       0       1       1       1       1       1       2       2       2       2       3       3       4       4       4       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       2       2       2       2       2       2       2       2       2       2       2       1       1       0       0       1       2       1       0       1       1       1       0       0       0       0       1       1       2       3       4       5       6       6       6       6       7       0       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       49      49      2       2       3       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       2       2       2       2       1       1       0       0       0       0       0       0       0       0       0       0       0       1       1       1       1       1       1       1       1       1       1       1       2       2       2       0       1       1       1       1       1       1       1       3       5       1       1       1       1       1       1       2       2       2       2       2       0       0       0       0       0       0       0       0       1       1       2       2       1       2       2       2       2       2       11      11      11      0       0       0       0       
+0       0       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       5       3       3       3       3       2       2       2       2       2       2       2       2       3       3       3       4       4       5       9       8       9       9       8       9       2       3       2       2       2       2       2       2       2       3       3       3       3       3       3       4       4       3       3       4       22      22      1       21      21      2       2       2       2       2       2       2       35      35      35      2       2       2       2       5       5       6       6       7       6       6       11      12      12      1       1       1       2       2       2       2       2       2       3       3       3       3       3       3       3       3       4       2       10      2       2       2       2       2       2       0       0       0       4       35      36      8       8       9       9       9       3       3       4       4       5       5       5       8       9       9       10      1       1       1       1       1       1       0       1       3       3       4       4       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       0       0       0       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       2       2       2       2       2       2       2       2       0       1       2       2       2       1       2       2       3       3       3       3       3       3       0       0       0       1       1       1       3       4       4       5       6       6       7       6       7       1       2       2       2       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       2       48      49      2       2       3       3       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       1       2       2       1       1       0       0       0       0       0       0       0       0       0       0       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       0       1       1       1       1       1       1       1       3       5       1       1       1       1       1       1       1       2       1       2       2       0       0       0       0       0       0       0       0       1       1       2       2       1       2       2       2       2       1       1       8       9       0       0       0       0       
+0       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       2       4       5       5       3       3       3       3       2       2       2       2       2       2       2       2       3       3       3       4       5       5       9       8       9       9       8       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       28      28      28      28      4       23      23      22      1       1       2       2       2       2       2       2       2       35      35      35      35      2       2       2       2       5       6       6       7       7       7       6       7       7       5       1       2       2       2       2       2       2       16      16      16      16      17      17      6       3       3       4       0       10      10      2       1       1       2       2       2       3       34      35      35      5       5       8       9       9       9       9       3       3       4       4       4       4       4       5       2       9       1       1       1       1       1       1       1       0       2       3       3       6       4       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       1       1       1       1       2       2       2       3       3       3       3       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       3       3       3       3       3       3       4       1       3       3       4       4       4       5       6       6       6       7       7       7       7       2       2       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       2       2       2       2       3       3       3       3       3       3       1       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       1       2       2       1       0       0       0       0       0       0       0       0       0       1       1       1       2       2       1       1       1       1       1       1       1       1       1       2       2       2       0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       0       0       0       0       0       0       0       0       0       1       1       1       1       1       1       1       1       1       1       8       9       0       0       0       0       
+1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       1       5       5       4       4       3       4       4       3       2       2       2       2       2       2       2       3       3       3       3       4       5       8       9       9       9       2       2       2       2       2       3       2       3       9       2       2       2       3       3       3       28      29      28      28      28      28      28      28      23      28      28      9       1       2       2       2       2       3       2       35      35      35      35      2       2       2       2       2       6       6       7       7       7       6       7       6       5       2       2       2       2       9       9       9       16      16      16      16      17      17      18      6       8       9       0       0       10      0       1       2       2       2       2       2       2       3       4       5       6       6       8       8       9       2       2       3       3       2       3       3       3       2       2       1       1       1       1       1       1       1       2       1       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       0       0       0       0       0       1       1       1       2       2       3       3       3       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       0       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       3       4       3       4       4       4       4       1       3       4       4       3       4       5       6       7       7       7       7       7       7       8       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       1       1       1       1       1       1       1       2       2       1       2       3       3       2       2       3       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       1       2       1       1       1       1       1       2       2       1       1       0       1       1       3       3       3       2       1       1       1       1       1       1       1       1       1       2       2       2       1       1       1       1       1       1       1       1       1       1       1       0       0       0       0       1       1       1       1       2       2       2       1       0       0       0       0       30      0       0       1       1       1       1       1       1       1       1       1       7       7       8       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       0       0       0       1       1       3       3       4       4       3       2       2       2       2       2       2       2       2       3       3       3       4       5       1       8       9       1       2       2       2       2       3       3       7       8       9       10      3       3       3       28      27      28      29      28      28      28      28      28      28      24      24      8       9       8       2       2       2       2       45      43      44      35      35      35      2       1       1       2       2       5       6       6       7       6       6       6       6       1       2       2       2       2       2       10      11      17      17      17      16      17      17      6       6       8       0       0       0       0       0       1       2       2       2       2       2       2       3       4       0       0       0       8       8       1       2       2       2       2       2       2       3       3       4       4       3       4       5       1       1       1       6       1       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       0       0       0       0       1       1       1       2       3       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       0       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       3       2       3       2       2       3       3       3       3       4       5       4       5       5       5       1       2       3       2       2       3       6       7       7       7       7       7       1       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       1       1       1       1       1       1       1       1       2       2       2       2       3       3       2       2       3       3       3       3       2       3       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       1       1       1       2       2       2       3       3       3       3       4       4       3       3       3       3       2       1       1       1       1       1       1       1       1       1       2       2       1       1       1       2       1       1       1       1       62      1       1       0       0       0       0       0       1       1       1       2       2       2       2       1       1       29      29      30      0       0       0       0       0       0       0       1       1       7       7       7       7       8       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       0       0       0       0       0       1       1       3       3       3       3       2       2       2       2       2       2       2       2       3       3       3       3       2       2       8       9       10      12      12      13      14      15      16      17      3       4       4       17      4       3       26      27      27      29      28      28      28      28      28      23      24      24      28      22      2       2       46      46      44      45      45      45      45      33      34      4       1       1       2       2       5       6       6       6       7       6       7       6       1       2       2       2       11      11      11      11      17      18      17      3       5       6       6       21      21      23      0       0       0       0       1       1       2       2       2       2       2       3       4       4       5       2       2       2       2       5       6       4       2       2       2       2       1       2       2       3       4       5       5       6       6       6       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       2       2       2       2       1       1       0       0       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       0       0       1       1       1       0       1       1       1       2       2       2       2       2       3       2       2       2       2       3       3       2       2       3       3       3       3       4       5       4       4       5       0       1       1       1       2       2       2       2       1       1       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       3       2       1       1       2       2       3       3       3       3       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       1       2       2       2       2       3       3       3       6       7       7       8       3       3       2       2       1       1       1       1       1       1       1       1       1       2       2       1       1       1       2       1       1       2       1       1       1       1       0       0       0       0       1       1       1       1       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       5       1       6       7       7       7       7       13      0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       1       1       0       0       1       1       3       3       3       3       2       2       2       2       2       2       2       2       3       3       3       3       3       2       2       8       8       11      12      12      13      14      16      16      17      18      19      19      20      18      25      25      27      28      28      28      28      28      20      23      23      24      24      27      22      23      46      46      46      44      44      44      44      45      45      21      3       2       2       2       2       5       5       6       6       7       7       7       10      1       2       2       2       11      12      11      11      18      18      9       3       4       5       5       0       0       23      0       0       0       0       1       1       2       2       2       2       4       3       4       4       4       3       3       3       4       5       6       6       7       8       0       0       1       1       2       3       5       5       6       6       6       6       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       2       1       1       1       2       2       2       2       2       1       0       0       0       1       0       1       1       2       2       3       2       2       2       3       2       2       2       3       3       3       3       3       3       3       3       2       2       2       2       1       1       1       1       1       1       2       2       2       2       19      1       1       1       1       1       1       1       1       1       1       1       2       2       1       1       1       1       2       1       1       1       2       2       1       1       1       1       1       1       1       1       2       1       1       1       1       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       3       4       5       6       7       7       8       3       3       2       2       2       1       1       1       1       1       1       1       1       2       2       2       1       2       2       1       2       2       2       2       1       1       0       0       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       3       3       0       0       0       1       1       3       7       6       7       7       8       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       1       1       0       0       0       1       1       3       3       2       2       2       2       2       2       2       3       3       3       3       3       3       2       2       2       8       2       2       12      12      13      3       3       17      18      18      19      20      22      23      25      26      27      27      27      18      18      17      20      21      23      24      24      23      23      23      46      46      43      44      44      44      44      45      45      22      50      3       3       2       1       5       6       6       6       7       7       7       1       1       2       2       2       11      11      11      17      17      18      9       3       3       4       5       0       0       23      0       0       0       0       1       1       2       2       2       2       4       4       4       4       4       3       3       3       4       5       6       7       7       8       0       0       1       2       2       3       4       5       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       2       2       2       1       1       1       2       2       2       2       2       3       3       3       3       3       0       0       1       1       0       1       1       2       2       3       2       3       2       3       3       3       3       3       3       3       8       3       3       3       2       2       2       2       2       2       2       1       2       2       2       2       2       2       21      19      1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       3       2       3       3       3       4       5       6       6       7       8       3       3       2       2       2       1       1       1       1       1       1       1       1       2       2       2       1       1       2       1       1       2       1       1       2       1       1       1       1       1       1       1       1       1       2       2       2       2       2       3       3       3       3       3       3       3       0       0       0       0       2       3       3       6       7       7       8       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       0       0       0       0       0       1       3       3       3       2       3       2       2       2       2       3       3       3       3       2       3       3       2       7       7       2       2       12      12      13      3       3       3       4       4       4       22      23      23      24      25      26      17      17      17      17      17      17      21      23      23      24      23      22      23      34      35      43      43      44      44      44      45      45      50      50      51      2       3       0       5       6       6       6       7       6       6       1       1       2       2       1       11      12      10      17      18      18      9       3       3       4       2       1       1       1       1       1       1       1       1       2       2       3       2       3       3       3       4       4       3       3       3       3       4       5       6       7       8       8       0       0       1       1       2       2       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       0       1       1       1       1       1       1       2       2       2       2       2       3       3       3       3       3       3       0       1       1       0       0       1       1       2       2       3       3       3       3       3       4       3       3       3       3       8       9       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       18      1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       3       3       3       2       3       3       4       4       5       6       6       7       8       3       3       2       2       2       1       1       1       1       1       1       1       1       2       1       1       2       1       1       1       1       2       1       1       2       1       1       1       1       1       1       1       1       1       2       2       2       2       3       3       3       3       3       3       3       3       0       0       0       0       0       1       11      12      7       7       13      0       0       0       0       
+1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       3       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       0       0       0       0       0       0       1       2       2       3       2       3       3       3       2       2       3       3       3       3       2       2       2       2       2       2       2       2       12      13      13      3       3       4       4       2       2       22      23      23      24      25      16      17      17      17      17      17      17      21      22      23      26      26      26      2       34      35      35      9       44      44      44      45      3       3       3       3       3       3       4       5       5       6       6       5       5       1       1       1       1       2       1       11      12      17      17      17      9       2       3       22      22      22      22      22      23      24      24      24      2       2       2       2       8       8       2       3       3       3       3       3       3       2       3       4       5       6       7       8       9       0       0       1       1       2       2       2       2       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       2       2       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       0       0       0       1       1       1       1       1       1       1       2       2       2       2       3       3       3       3       3       4       0       0       0       0       0       0       1       2       2       3       4       4       4       4       4       4       2       3       3       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       18      1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       2       2       2       2       2       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       2       3       3       3       3       3       3       4       4       5       6       6       7       2       3       2       2       2       2       2       2       2       2       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       2       1       1       1       1       1       1       1       1       2       2       2       2       2       3       3       3       3       3       3       3       3       3       0       1       2       2       3       12      12      13      13      2       17      17      17      18      
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+0       0       0       0       0       0       1       1       1       1       1       0       7       8       8       8       8       5       6       6       5       5       5       2       3       4       5       19      20      19      19      19      26      26      7       7       7       7       7       7       7       7       7       7       7       6       6       6       7       7       7       7       7       7       6       6       6       6       6       6       6       6       6       7       7       7       7       7       7       7       7       7       7       7       7       7       7       7       7       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       7       6       7       9       10      11      12      13      14      15      16      17      18      19      19      4       4       23      24      25      25      25      4       5       5       5       6       6       7       7       0       0       0       11      0       1       2       25      17      17      18      25      25      35      6       6       6       6       6       6       6       6       6       6       45      33      33      7       7       7       8       8       8       11      11      6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       5       5       5       5       5       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       5       5       5       5       5       5       5       5       6       6       5       6       6       6       6       6       6       6       6       6       6       6       6       6       6       7       6       5       5       5       5       5       5       5       5       5       5       5       5       5       5       6       6       5       5       5       5       5       5       5       5       5       5       5       5       5       5       4       4       4       5       6       7       8       9       10      15      15      13      13      14      16      17      17      18      5       5       5       5       5       5       5       5       5       5       36      27      27      19      5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       4       4       3       1       3       3       11      11      4       4       4       4       4       5       5       5       5       4       4       4       4       4       4       4       3       3       3       3       3       3       3       4       38      38      39      39      32      1       1       2       2       2       2       3       3       19      19      19      19      16      20      21      5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       4       4       4       4       4       5       5       5       5       5       5       5       5       4       4       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       4       4       4       4       4       4       4       5       5       5       5       5       5       5       5       5       4       4       4       4       4       5       5       5       5       5       5       5       4       4       4       4       4       4       4       4       5       5       5       5       5       5       5       5       4       4       4       4       5       5       5       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       5       5       5       5       5       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       0       0       0       0       
+0       0       0       0       0       1       1       1       1       2       1       0       8       8       8       8       8       13      14      14      14      14      14      14      3       4       5       19      19      25      26      26      26      21      7       7       7       7       7       7       7       7       7       7       7       6       6       6       7       7       7       7       7       7       7       6       6       6       6       6       6       7       7       7       7       7       7       7       7       7       7       7       7       7       7       7       7       7       7       6       6       6       6       6       6       7       7       7       7       7       7       7       6       6       6       6       7       7       6       6       6       6       6       6       6       10      10      11      12      13      15      16      16      17      18      19      20      22      23      23      24      25      26      25      25      5       5       5       5       6       6       7       36      37      38      0       1       1       1       2       5       45      17      18      24      24      30      6       6       6       6       6       6       6       6       6       6       45      34      33      0       7       7       8       8       13      11      11      6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       4       5       4       5       5       5       5       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       8       6       6       6       6       6       6       6       6       6       5       5       5       5       5       5       5       5       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       6       7       7       5       5       5       5       5       5       5       5       5       5       5       5       5       5       6       6       5       5       5       5       5       5       5       5       5       5       5       5       5       2       3       4       4       4       10      10      8       8       9       15      15      16      16      16      16      17      17      18      18      5       6       6       5       5       5       5       5       5       5       17      20      27      19      5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       3       0       1       3       3       11      11      4       4       4       4       4       5       5       5       5       4       4       4       4       4       4       4       3       3       3       3       3       3       3       37      38      38      39      39      32      32      1       2       2       2       3       3       3       19      19      53      53      16      20      5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       4       5       5       5       5       5       5       5       5       5       5       5       5       5       4       4       4       4       5       5       5       5       5       5       5       5       4       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       5       4       4       4       4       4       4       4       5       5       5       5       5       5       5       5       5       4       4       4       5       5       5       5       42      42      42      42      5       4       4       4       4       4       4       4       4       5       5       5       5       5       5       5       5       5       4       4       5       5       5       5       29      29      4       4       4       4       4       4       4       4       4       4       5       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       5       5       5       5       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       5       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       0       0       0       0       
diff --git a/SD-VBS/benchmarks/disparity/src/c/computeSAD.c b/SD-VBS/benchmarks/disparity/src/c/computeSAD.c
new file mode 100644
index 0000000..e12bd55
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/c/computeSAD.c
@@ -0,0 +1,27 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "disparity.h"
+
+void computeSAD(I2D *Ileft, I2D* Iright_moved, F2D* SAD)
+{
+    int rows, cols, i, j, diff;
+    
+    rows = Ileft->height;
+    cols = Ileft->width;
+
+    for(i=0; i<rows; i++)
+    {
+        for(j=0; j<cols; j++)
+        {
+            diff = subsref(Ileft,i,j) - subsref(Iright_moved,i,j);
+            subsref(SAD,i,j) = diff * diff;
+        }
+    }
+    
+    return;
+}
+
diff --git a/SD-VBS/benchmarks/disparity/src/c/correlateSAD_2D.c b/SD-VBS/benchmarks/disparity/src/c/correlateSAD_2D.c
new file mode 100644
index 0000000..6b43cbd
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/c/correlateSAD_2D.c
@@ -0,0 +1,34 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "disparity.h"
+
+void correlateSAD_2D(I2D* Ileft, I2D* Iright, I2D* Iright_moved, int win_sz, int disparity, F2D* SAD, F2D* integralImg, F2D* retSAD, I2D* range)
+{
+    int rows, cols;
+    int i, j, endRM;
+    //I2D *range;
+    
+    //iResetArray(range,1,2,0);
+    subsref(range,0,0) = 0;
+    subsref(range,0,1) = disparity;
+
+    rows = Iright_moved->height;
+    cols = Iright_moved->width;
+
+    for(i=0; i<rows*cols; i++)
+        asubsref(Iright_moved,i) = 0;
+    
+    padarray4(Iright, range, -1, Iright_moved);
+   
+    computeSAD(Ileft, Iright_moved, SAD);
+    integralImage2D2D(SAD, integralImg);
+    finalSAD(integralImg, win_sz, retSAD);
+
+    //iFreeHandle(range);    
+    return;
+}
+
diff --git a/SD-VBS/benchmarks/disparity/src/c/disparity.h b/SD-VBS/benchmarks/disparity/src/c/disparity.h
new file mode 100644
index 0000000..8617a87
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/c/disparity.h
@@ -0,0 +1,24 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#ifndef _DISP_
+#define _DISP_
+
+#include "sdvbs_common.h"
+void computeSAD(I2D *Ileft, I2D* Iright_moved, F2D* SAD);
+I2D* getDisparity(I2D* Ileft, I2D* Iright, int win_sz, int max_shift,
+                  I2D* minSAD, I2D* retDisp, I2D* halfWin,
+                  I2D* IrightPadded, I2D* IleftPadded, I2D* Iright_moved,
+                  F2D* retSAD, F2D* SAD, F2D* integralImg,
+                  I2D* range);
+void finalSAD(F2D* integralImg, int win_sz, F2D* retSAD);
+void findDisparity(F2D* retSAD, F2D* minSAD, I2D* retDisp, int level, int nr, int nc);
+void integralImage2D2D(F2D* SAD, F2D* integralImg);
+void correlateSAD_2D(I2D* Ileft, I2D* Iright, I2D* Iright_moved, int win_sz, int disparity, F2D* SAD, F2D* integralImg, F2D* retSAD, I2D* range);
+I2D* padarray2(I2D* inMat, I2D* borderMat);
+void padarray4(I2D* inMat, I2D* borderMat, int dir, I2D* paddedArray);
+
+#endif
+
+
diff --git a/SD-VBS/benchmarks/disparity/src/c/finalSAD.c b/SD-VBS/benchmarks/disparity/src/c/finalSAD.c
new file mode 100644
index 0000000..8155820
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/c/finalSAD.c
@@ -0,0 +1,28 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "disparity.h"
+
+void finalSAD(F2D* integralImg, int win_sz, F2D* retSAD)
+{
+    int endR, endC;
+    int i, j, k;
+    
+    endR = integralImg->height;
+    endC = integralImg->width;
+    
+    k = 0;
+    for(j=0; j<(endC-win_sz); j++)
+    {
+        for(i=0; i<(endR-win_sz); i++)
+        {
+            subsref(retSAD,i,j) = subsref(integralImg,(win_sz+i),(j+win_sz)) + subsref(integralImg,(i+1) ,(j+1)) - subsref(integralImg,(i+1),(j+win_sz)) - subsref(integralImg,(win_sz+i),(j+1));
+        }
+    }
+
+    return;
+}
+
diff --git a/SD-VBS/benchmarks/disparity/src/c/findDisparity.c b/SD-VBS/benchmarks/disparity/src/c/findDisparity.c
new file mode 100644
index 0000000..6335daf
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/c/findDisparity.c
@@ -0,0 +1,29 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "disparity.h"
+
+void findDisparity(F2D* retSAD, F2D* minSAD, I2D* retDisp, int level, int nr, int nc)
+{
+    int i, j, a, b;
+    
+    for(i=0; i<nr; i++)
+    {
+        for(j=0; j<nc; j++)
+        {
+            a = subsref(retSAD,i,j);
+            b = subsref(minSAD,i,j);
+            if(a<b)
+            {
+                subsref(minSAD,i,j) = a;
+                subsref(retDisp,i,j) = level;
+            }
+        }
+    }
+    return;
+}
+
+
diff --git a/SD-VBS/benchmarks/disparity/src/c/getDisparity.c b/SD-VBS/benchmarks/disparity/src/c/getDisparity.c
new file mode 100644
index 0000000..3246e97
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/c/getDisparity.c
@@ -0,0 +1,43 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "disparity.h"
+
+I2D* getDisparity(I2D* Ileft, I2D* Iright, int win_sz, int max_shift,
+                  I2D* minSAD, I2D* retDisp, I2D* halfWin, 
+                  I2D* IrightPadded, I2D* IleftPadded, I2D* Iright_moved,
+                  F2D* retSAD, F2D* SAD, F2D* integralImg,
+                  I2D* range)
+{
+    int nr, nc, k;
+    int half_win_sz, rows, cols;
+    
+    nr = Ileft->height;
+    nc = Ileft->width;
+    half_win_sz=win_sz/2;
+    
+    
+    fResetArray(minSAD, nr, nc, 255.0*255.0);
+    iResetArray(retDisp, nr, nc,max_shift);
+    iResetArray(halfWin, 1,2,half_win_sz);
+
+    rows = IleftPadded->height;
+    cols = IleftPadded->width;
+    fResetArray(SAD, rows, cols,255);
+    fResetArray(integralImg, rows, cols,0);
+    //fResetArray(retSAD,rows-win_sz, cols-win_sz, 0);
+    iResetArray(Iright_moved, rows, cols, 0);
+    
+    for( k=0; k<max_shift; k++)
+    {    
+        correlateSAD_2D(IleftPadded, IrightPadded, Iright_moved, win_sz, k, SAD, integralImg, retSAD, range);
+        findDisparity(retSAD, minSAD, retDisp, k, nr, nc);
+    }
+    
+     
+    return retDisp;
+}
+
diff --git a/SD-VBS/benchmarks/disparity/src/c/integralImage2D2D.c b/SD-VBS/benchmarks/disparity/src/c/integralImage2D2D.c
new file mode 100644
index 0000000..cc964d1
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/c/integralImage2D2D.c
@@ -0,0 +1,31 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "disparity.h"
+
+void integralImage2D2D(F2D* SAD, F2D* integralImg)
+{
+    int nr, nc, i, j;
+    
+    nr = SAD->height;
+    nc = SAD->width;
+    
+    for(i=0; i<nc; i++)
+        subsref(integralImg,0,i) = subsref(SAD,0,i);
+    
+    for(i=1; i<nr; i++)
+        for(j=0; j<nc; j++)
+        {
+            subsref(integralImg,i,j) = subsref(integralImg, (i-1), j) + subsref(SAD,i,j);
+        }
+
+    for(i=0; i<nr; i++)
+        for(j=1; j<nc; j++)
+            subsref(integralImg,i,j) = subsref(integralImg, i, (j-1)) + subsref(integralImg,i,j);
+
+    return;
+    
+}
diff --git a/SD-VBS/benchmarks/disparity/src/c/padarray2.c b/SD-VBS/benchmarks/disparity/src/c/padarray2.c
new file mode 100644
index 0000000..49f1938
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/c/padarray2.c
@@ -0,0 +1,33 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "disparity.h"
+
+I2D* padarray2(I2D* inMat, I2D* borderMat)
+{
+    int rows, cols, bRows, bCols, newRows, newCols;
+    I2D *paddedArray;
+    int i, j;
+
+    rows = inMat->height;
+    cols = inMat->width;
+    
+    bRows = borderMat->data[0];
+    bCols = borderMat->data[1];
+    
+    newRows = rows + bRows*2;
+    newCols = cols + bCols*2;
+    
+    paddedArray = iSetArray(newRows, newCols, 0);
+    
+    for(i=0; i<rows; i++)
+        for(j=0; j<cols; j++)
+            subsref(paddedArray, (bRows+i), (bCols+j)) = subsref(inMat, i, j);
+    
+    return paddedArray;
+    
+}
+
diff --git a/SD-VBS/benchmarks/disparity/src/c/padarray4.c b/SD-VBS/benchmarks/disparity/src/c/padarray4.c
new file mode 100644
index 0000000..321cad9
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/c/padarray4.c
@@ -0,0 +1,41 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <math.h>
+#include "disparity.h"
+
+void padarray4(I2D* inMat, I2D* borderMat, int dir, I2D* paddedArray)
+{
+    int rows, cols, bRows, bCols, newRows, newCols;
+    int i, j;
+    int adir;
+   
+    adir = abs(dir); 
+    rows = inMat->height;
+    cols = inMat->width;
+    
+    bRows = borderMat->data[0];
+    bCols = borderMat->data[1];
+    
+    newRows = rows + bRows;
+    newCols = cols + bCols;
+    
+    if(dir ==1)
+    {
+        for(i=0; i<rows; i++)
+            for(j=0; j<cols; j++)
+                subsref(paddedArray, i, j) = subsref(inMat,i,j);
+    }
+    else
+    {
+        for(i=0; i<rows-bRows; i++)
+            for(j=0; j<cols-bCols; j++)
+                subsref(paddedArray, (bRows+i), (bCols+j)) = subsref(inMat,i,j);
+    }
+    
+    return;
+}
+
diff --git a/SD-VBS/benchmarks/disparity/src/c/script_disparity.c b/SD-VBS/benchmarks/disparity/src/c/script_disparity.c
new file mode 100644
index 0000000..431c02c
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/c/script_disparity.c
@@ -0,0 +1,132 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "disparity.h"
+#include <malloc.h>
+#include "extra.h"
+#define DISPARITY_MEM 1<<24
+int main(int argc, char* argv[])
+{
+    SET_UP
+    mallopt(M_TOP_PAD, DISPARITY_MEM);
+    mallopt(M_MMAP_MAX, 0);
+    int rows = 32;
+    int cols = 32;
+    I2D *imleft, *imright;
+    volatile I2D* retDisparity;
+    I2D *IrightPadded, *IleftPadded, *Iright_moved;
+    I2D *retDisp, *halfWin;
+    I2D *range;
+    F2D *retSAD, *minSAD, *SAD, *integralImg;
+    unsigned int *start, *endC, *elapsed;
+    
+    int i, j;
+    char im1[100], im2[100], timFile[100];
+    int WIN_SZ=8, SHIFT=64;
+    FILE* fp;
+    
+    printf("Image 1: ");
+    scanf("%s", im1);
+    printf("Image 2: ");
+    scanf("%s", im2);
+#ifdef CHECK
+    char checkFile[100] = "./expected_C.txt";
+#endif
+    imleft = readImage(im1);
+    imright = readImage(im2);
+
+    rows = imleft->height;
+    cols = imleft->width;
+
+#ifdef test
+    WIN_SZ = 2;
+    SHIFT = 1;
+#endif
+#ifdef sim_fast
+    WIN_SZ = 4;
+    SHIFT = 4;
+#endif
+#ifdef sim
+    WIN_SZ = 4;
+    SHIFT = 8;
+#endif
+
+
+    int nr, nc, k;
+    int half_win_sz;
+    nr = imleft->height;
+    nc = imleft->width;
+    half_win_sz = WIN_SZ / 2;
+
+    minSAD = fSetArray(nr, nc, 255.0*255.0);
+    retDisp = iSetArray(nr, nc, SHIFT);
+    halfWin = iSetArray(1,2,half_win_sz);
+
+
+    if(WIN_SZ > 1)
+    {
+        IleftPadded = padarray2(imleft, halfWin);
+        IrightPadded = padarray2(imright, halfWin);
+    }
+    else
+    {
+        IleftPadded = imleft;
+        IrightPadded = imright;
+    }
+
+    int paddedRows, paddedCols;
+    paddedRows = IleftPadded->height;
+    paddedCols = IleftPadded->width;
+    SAD = fSetArray(paddedRows, paddedCols,255);
+    integralImg = fSetArray(paddedRows, paddedCols,0);
+    retSAD = fMallocHandle(paddedRows- WIN_SZ, paddedCols - WIN_SZ);
+    Iright_moved = iSetArray(paddedRows, paddedCols, 0);
+
+    range = iMallocHandle(1, 2);
+    printf("starting..\n");
+    for_each_job{
+    retDisparity = getDisparity(imleft, imright, WIN_SZ, SHIFT, 
+                   minSAD, retDisp, halfWin,
+                   IrightPadded, IleftPadded, Iright_moved,
+                   retSAD, SAD, integralImg,
+                   range);
+    }
+    printf("ending\n");
+
+#ifdef CHECK   
+    /** Self checking - use expected.txt from data directory  **/
+    {
+        int tol, ret=0;
+        tol = 2;
+#ifdef GENERATE_OUTPUT
+        writeMatrix(retDisparity, argv[1]);
+#endif
+        ret = selfCheck(retDisparity, checkFile, tol);
+        if (ret == -1)
+            printf("Error in Disparity Map\n");
+    }
+    /** Self checking done **/
+#endif
+
+    //end of benchmark
+    fFreeHandle(minSAD);
+    fFreeHandle(SAD);
+    fFreeHandle(integralImg);
+    iFreeHandle(IrightPadded);
+    iFreeHandle(IleftPadded);
+    iFreeHandle(Iright_moved);
+    fFreeHandle(retSAD);
+    iFreeHandle(imleft);
+    iFreeHandle(imright);
+    iFreeHandle(retDisparity);
+    iFreeHandle(halfWin);
+    iFreeHandle(range);
+    free(start);
+    free(endC);
+    free(elapsed);
+    WRITE_TO_FILE;
+    return 0;
+}
diff --git a/SD-VBS/benchmarks/disparity/src/matlab/getDisparity.m b/SD-VBS/benchmarks/disparity/src/matlab/getDisparity.m
new file mode 100755
index 0000000..db64cac
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/matlab/getDisparity.m
@@ -0,0 +1,54 @@
+function [retDisparity retSAD minSAD]=getDisparity(Ileft, Iright, win_sz, max_shift)
+Ileft=double(Ileft);
+Iright=double(Iright);
+[nr,nc,nb]=size(Ileft);
+retSAD=zeros(nr, nc, max_shift);
+
+if(win_sz > 1)
+    half_win_sz=win_sz/2;
+    IleftPadded=padarray(Ileft, [half_win_sz, half_win_sz]);
+    IrightPadded=padarray(Iright, [half_win_sz, half_win_sz]);
+    for i=1:max_shift   
+        retSAD(:,:,i)=correlateSAD(IleftPadded,IrightPadded, win_sz, i-1);
+    end
+    [minSAD retDisparity]=min(retSAD,[],3);
+else
+    IleftPadded = Ileft;
+    IrightPadded = Iright;
+    retSAD=correlateSAD(IleftPadded,IrightPadded, win_sz, 0);
+    [minSAD retDisparity]=min(retSAD,[],3);
+end
+end
+
+function retSAD=correlateSAD(Ileft, Iright, win_sz, disparity)
+
+Iright_moved=padarray(Iright, [0,disparity], 'pre');    
+Iright_moved=Iright_moved(:, 1:end-disparity,:);
+
+[rows, cols] = size(Ileft);
+for i=1:rows
+    for j=1:cols
+        diff = Ileft(i,j) - Iright_moved(i,j);
+        SAD(i,j) = diff * diff;
+    end
+end
+
+%2D scan.
+integralImg=integralImage2D(SAD);
+retSAD=integralImg(win_sz+1:end,win_sz+1:end,:) +integralImg(2:end-win_sz+1,2:end-win_sz+1,:)-integralImg(2:end-win_sz+1,win_sz+1:end,:)-integralImg(win_sz+1:end,2:end-win_sz+1,:);
+
+end
+
+function retImg=integralImage2D(I)
+[nr,nc,nb]=size(I);
+retImg=zeros(nr,nc,nb);
+retImg(1,:,:)=I(1,:,:);
+for i=2:nr
+    retImg(i,:,:)=retImg(i-1,:,:)+I(i,:,:);
+end
+%vtuneResumeMex;
+for j=2:nc
+    retImg(:,j,:)=retImg(:,j-1,:)+retImg (:,j,:);
+end
+%vtunePauseMex;
+end
diff --git a/SD-VBS/benchmarks/disparity/src/matlab/refineDisparity.m b/SD-VBS/benchmarks/disparity/src/matlab/refineDisparity.m
new file mode 100755
index 0000000..f303236
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/matlab/refineDisparity.m
@@ -0,0 +1,31 @@
+function retDisparity=refineDisparity(Idisp, DispSAD, Ileft, Iright)
+[nr nc ndist]=size(DispSAD);
+retDisparity=zeros(nr, nc);
+
+IdispNext=padarray(Idisp, [0 1], 'replicate', 'post');
+IdispNext=IdispNext(:,2:end);
+
+
+IdispDiff=abs(Idisp-IdispNext);
+idx=find(IdispDiff>1);
+[idxI idxJ]=ind2sub([nr, nc], idx);
+
+%if(Idisp(idx)
+%sideFlag=
+checkedResult= (abs( DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ, Idisp(idx))) - ...
+DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ+1, Idisp(idx))) ) < 1 )+1;
+checkedResult= checkedResult + (abs( DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ, Idisp(idx+nr))) - ...
+DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ+1, Idisp(idx+nr))) ) < 1 );
+retDisparity(idx)=checkedResult;
+
+
+% IdispDiff=(Idisp-IdispNext);
+% idx=find(IdispDiff<-1);
+% [idxI idxJ]=ind2sub([nr, nc], idx);
+% 
+% checkedResult= abs( DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ, Idisp(idx+nr))) - ...
+% DispSAD(sub2ind( [nr, nc, ndist], idxI, idxJ+1, Idisp(idx+nr))) ) < 0.5;
+% retDisparity(idx)=checkedResult;
+
+
+
diff --git a/SD-VBS/benchmarks/disparity/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/disparity/src/matlab/script_run_profile.m
new file mode 100755
index 0000000..6e0386d
--- /dev/null
+++ b/SD-VBS/benchmarks/disparity/src/matlab/script_run_profile.m
@@ -0,0 +1,43 @@
+function script_run_profile(dataDir, resultDir, type, common, tooldir)
+
+path(path,common); 
+
+tol = 2;
+elapsed = [0, 0];
+
+WIN_SZ = 8;
+SHIFT = 64;
+
+if(strcmp(type,'test'))
+    WIN_SZ = 2;
+    SHIFT = 1;
+elseif(strcmp(type, 'sim_fast'))
+    WIN_SZ = 4;
+    SHIFT = 4;
+elseif(strcmp(type,'sim'))
+    WIN_SZ = 4;
+    SHIFT = 8;
+end
+
+    outFile = [resultDir, '/', 'out', '.bmp'];
+
+    file = [dataDir, '/1.bmp'];
+    imleft = readImage(file);
+    imright = readImage([dataDir, '/2.bmp']);
+    [rows, cols] = size(imright);
+
+    fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
+
+    start = photonStartTiming;
+    [imDispOwn, DispSAD, minSAD]=getDisparity(double(imleft), double(imright), WIN_SZ, SHIFT);
+    stop = photonEndTiming;
+    elapsed = photonReportTiming(start, stop);
+
+    writeMatrix(imDispOwn, dataDir);
+    imwrite(uint8(minSAD), outFile, 'bmp');
+
+    photonPrintTiming(elapsed);
+
+
+
+
diff --git a/SD-VBS/benchmarks/localization/Makefile b/SD-VBS/benchmarks/localization/Makefile
new file mode 100644
index 0000000..60cc0ec
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/Makefile
@@ -0,0 +1,3 @@
+include ../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/localization/data/Makefile b/SD-VBS/benchmarks/localization/data/Makefile
new file mode 100644
index 0000000..ba33d35
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/Makefile
@@ -0,0 +1,3 @@
+include ../../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/localization/data/cif/Makefile b/SD-VBS/benchmarks/localization/data/cif/Makefile
new file mode 100644
index 0000000..4bd562f
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/cif/Makefile
@@ -0,0 +1,7 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=localization
+INPUT=cif
+
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/localization/data/cif/VBS_Ver1 b/SD-VBS/benchmarks/localization/data/cif/VBS_Ver1
new file mode 100755
index 0000000..b04da34
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/cif/VBS_Ver1
diff --git a/SD-VBS/benchmarks/localization/data/cif/cif b/SD-VBS/benchmarks/localization/data/cif/cif
new file mode 100755
index 0000000..8489f9a
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/cif/cif
diff --git a/SD-VBS/benchmarks/localization/data/cif/expected.m b/SD-VBS/benchmarks/localization/data/cif/expected.m
new file mode 100644
index 0000000..22ef940
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/cif/expected.m
@@ -0,0 +1,3 @@
+1264.100919     1018.646860     -66.744065      1325.148554     -524.072802     104.959493      1293.736304     -176.791171     129.794173      28.123781       -825.907469     110.949588      -53.030419      -387.071088     175.278628      -306.960407     -332.128807     -859.326326     96.550227       -269.287595     -19.835881      207.383563      -251.431495     -71.876639      241.454426      -291.088405     115.707219      337.421875      329.434722      -31.556631      200.761584      273.097048      -209.534328     -460.765107     186.245449      116.289195      -351.230797     108.699099      -71.331712      386.736600      -292.419981     -0.334981       -242.589950     -353.060399     -99.262004      -109.249025     -360.813810     -40.844284      -206.722293     -430.241768     29.072174       -266.322402     -260.740639     -436.982547     -175.357022     283.583788      -279.093973     -387.176464     248.837096      447.196705      -268.019516     -298.939012     343.244024      206.071785      -225.746220     -187.288143     200.444712      -93.034358      -165.697562     15.808615       -304.358091     415.538855      63.043500       -136.137632     -383.437919     -7.746789       -329.599742     -221.224972     -348.912560     -202.666314     -227.899182     -232.552441     384.227756      166.317852      -184.182201     -68.725094      54.730375       0.000000        
+148.469605      249783.963758   249783.963758   2180.681112     383736.909385   383736.909385   253883.626524   253883.626524   476143.774773   476143.774773   389683.019120   389683.019120   545807.588908   545807.588908   232299.455988   599622.582238   599622.582238   417714.138595   417714.138595   646854.785707   646854.785707   517757.007454   517757.007454   687063.797171   687063.797171   337856.935013   720555.709843   720555.709843   508182.601804   508182.601804   752242.685858   752242.685858   596994.900082   596994.900082   781076.846278   781076.846278   408387.972486   804774.536536   804774.536536   572505.759937   572505.759937   829541.440024   829541.440024   656637.597514   656637.597514   852188.058601   852188.058601   464317.955836   871738.416433   871738.416433   625271.852328   625271.852328   892047.804954   892047.804954   706766.734908   706766.734908   911202.007529   911202.007529   761878.379462   761878.379462   929603.367197   929603.367197   805063.056324   805063.056324   947078.978085   947078.978085   841497.089926   841497.089926   714530.798901   871063.266696   871063.266696   847094.846486   847094.846486   900419.631759   900419.631759   907069.193562   907069.193562   927072.876646   927072.876646   695517.442884   948856.006854   948856.006854   840738.929439   840738.929439   972511.540879   972511.540879   909607.468542   0.000000        
+4907681162.639265       4996983773.346421       4996983773.346421       4907470495.183228       4968360833.406909       4968360833.406909       4908709186.117507       4908709186.117507       4953769759.629911       4953769759.629911       4909434990.624061       4909434990.624061       4944946321.273969       4944946321.273969       4908726987.816192       4939055160.653013       4939055160.653013       4909755868.543180       4909755868.543180       4934891702.718277       4934891702.718277       4910373711.010693       4910373711.010693       4931739973.964623       4931739973.964623       4909601991.354140       4929263185.565628       4929263185.565628       4910590381.898005       4910590381.898005       4927366117.137535       4927366117.137535       4911182724.385408       4911182724.385408       4925842684.055954       4925842684.055954       4910387212.896085       4924580415.310893       4924580415.310893       4911364419.082825       4911364419.082825       4923588892.702791       4923588892.702791       4911945399.855221       4911945399.855221       4922665132.406710       4922665132.406710       4911146778.096742       4921854906.683125       4921854906.683125       4912117527.337012       4912117527.337012       4921247956.389248       4921247956.389248       4912691752.735250       4912691752.735250       4920632038.287462       4920632038.287462       4913140704.670214       4913140704.670214       4920169402.955149       4920169402.955149       4913521889.855532       4913521889.855532       4919786752.370605       4919786752.370605       4913870380.414716       4913870380.414716       4918135706.514756       4914176948.628077       4914176948.628077       4918436009.170393       4918436009.170393       4914475956.108191       4914475956.108191       4918424403.658169       4918424403.658169       4914736253.512666       4914736253.512666       4917126279.233858       4914920865.993999       4914920865.993999       4917765910.500541       4917765910.500541       4915042054.464935       4915042054.464935       4918118358.250251       0.000000        
diff --git a/SD-VBS/benchmarks/localization/data/cif/localization b/SD-VBS/benchmarks/localization/data/cif/localization
new file mode 100755
index 0000000..be524d2
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/cif/localization
diff --git a/SD-VBS/benchmarks/localization/data/qcif/Makefile b/SD-VBS/benchmarks/localization/data/qcif/Makefile
new file mode 100644
index 0000000..d18c02d
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/qcif/Makefile
@@ -0,0 +1,8 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=localization
+INPUT=qcif
+
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/localization/data/qcif/expected.m b/SD-VBS/benchmarks/localization/data/qcif/expected.m
new file mode 100644
index 0000000..4263b3d
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/qcif/expected.m
@@ -0,0 +1,3 @@
+631.976450      516.498284      -197.996728     663.497659      -22.288426      -28.903321      647.817138      -351.955521     -312.433355     44.896667       -150.353868     -67.000702      -370.502974     26.299828       -488.261017     -321.672753     -20.467725      -293.286835     -85.465502      -243.718793     -74.565859      -549.266195     30.999329       -160.813808     -121.355881     -483.242401     -79.323855      -151.906467     -595.771606     12.823360       -12.448671      -172.470587     -511.488467     -21.514722      42.089059       -185.300910     -324.317055     89.756283       -187.135260     -628.505815     29.732164       124.069805      -182.587245     -367.573870     -76.374400      148.479017      -172.587616     -145.562423     167.983942      -157.609772     -529.296685     21.322336       179.630194      -137.981888     -185.584066     -112.106506     185.662406      -114.184459     25.859838       -163.799486     189.409619      -87.299860      149.829422      -166.716356     189.327882      -58.163997      221.918824      -144.524825     183.798380      253.096143      -116.072162     284.431081      -110.520707     261.347591      -74.376768      318.351401      -83.847971      256.673574      -30.452642      285.051087      232.480691      6.336376        352.034688      -65.985798      202.705055      47.633804       382.774465      0.000000        
+74.359725       55442.431887    55442.431887    916.112559      85048.747743    85048.747743    57211.398438    57211.398438    105779.314664   105779.314664   87600.029083    87600.029083    121512.447801   121512.447801   52860.067135    133141.106400   133141.106400   94517.909665    94517.909665    143946.045181   143946.045181   117118.457039   117118.457039   153064.488091   153064.488091   77359.640694    160318.887671   160318.887671   115674.880954   115674.880954   167827.918882   167827.918882   135968.435504   135968.435504   174698.161121   174698.161121   94713.555770    180133.542229   180133.542229   131871.515823   131871.515823   186165.689411   186165.689411   151252.883116   151252.883116   191909.078626   191909.078626   109392.213684   196358.978485   196358.978485   146078.668403   146078.668403   201651.395781   201651.395781   165046.805127   165046.805127   206711.131954   206711.131954   178320.376082   178320.376082   211596.482547   211596.482547   188947.507546   188947.507546   216497.738288   216497.738288   197921.386091   197921.386091   165985.571620   205091.855127   205091.855127   196779.521358   196779.521358   212609.207639   212609.207639   211533.666997   211533.666997   219561.468379   219561.468379   166056.319552   225227.570848   225227.570848   200047.795792   200047.795792   231596.764178   231596.764178   216995.904046   0.000000        
+2453723755.101060       2473138738.478060       2473138738.478060       2453633812.224546       2466744375.113051       2466744375.113051       2453912441.757200       2453912441.757200       2463514723.222767       2463514723.222767       2454091490.868995       2454091490.868995       2461535850.721794       2461535850.721794       2453959313.433379       2460231345.559122       2460231345.559122       2454218817.973337       2454218817.973337       2459307064.549955       2459307064.549955       2454389996.064240       2454389996.064240       2458639118.655468       2458639118.655468       2454254726.669796       2458128486.626955       2458128486.626955       2454513520.017527       2454513520.017527       2457726299.581051       2457726299.581051       2454684774.597973       2454684774.597973       2457410967.437045       2457410967.437045       2454549597.959815       2457150540.743558       2457150540.743558       2454807555.250977       2454807555.250977       2456916627.143601       2456916627.143601       2454977251.488404       2454977251.488404       2456719675.377667       2456719675.377667       2454837557.911356       2456573728.470717       2456573728.470717       2455086906.118260       2455086906.118260       2456453336.049111       2456453336.049111       2455239927.219034       2455239927.219034       2456371158.832802       2456371158.832802       2455342631.649824       2455342631.649824       2456355762.744594       2456355762.744594       2455396094.462677       2455396094.462677       2456381099.252142       2456381099.252142       2455441691.541200       2455441691.541200       2456128146.863575       2455477781.414840       2455477781.414840       2456282488.340037       2456282488.340037       2455516633.096739       2455516633.096739       2456357066.451140       2456357066.451140       2455552537.419121       2455552537.419121       2456129670.296010       2455581213.884797       2455581213.884797       2456300055.909151       2456300055.909151       2455615007.049098       2455615007.049098       2456385531.538922       0.000000        
diff --git a/SD-VBS/benchmarks/localization/data/qcif/localization b/SD-VBS/benchmarks/localization/data/qcif/localization
new file mode 100755
index 0000000..e2fb417
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/qcif/localization
diff --git a/SD-VBS/benchmarks/localization/data/sim/Makefile b/SD-VBS/benchmarks/localization/data/sim/Makefile
new file mode 100644
index 0000000..5dde8fe
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/sim/Makefile
@@ -0,0 +1,8 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=localization
+INPUT=sim
+
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/localization/data/sim/expected.m b/SD-VBS/benchmarks/localization/data/sim/expected.m
new file mode 100644
index 0000000..eb3b6a7
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/sim/expected.m
@@ -0,0 +1,3 @@
+12.543452       13.658157       13.497180       13.894946       13.959641       13.788874       13.848866       13.673453       13.788413       13.616173       13.675684       13.496716       13.628587       13.453379       13.516593       13.560943       13.384332       13.462265       13.282183       13.388606       13.211571       13.284906       13.102213       13.225472       13.047242       13.124615       13.157999       12.976742       13.069521       12.884701       12.981088       12.800202       12.888504       12.701228       12.814751       12.629592       12.721974       12.743435       12.557293       12.665573       12.476815       12.562721       12.375911       12.479525       12.287222       12.390423       12.201016       12.309248       12.317883       12.128404       12.252886       12.058258       12.132629       11.941091       12.061026       11.865997       11.957748       11.764361       11.888852       11.692058       11.785975       11.590614       11.715017       11.515945       11.611867       11.414693       11.539084       11.338245       11.436080       11.460551       11.257957       11.375602       11.175996       11.267413       11.064235       11.177627       10.976366       11.082948       10.877846       10.998140       11.002795       10.797280       10.937839       10.734714       10.807476       10.600371       10.736720       0.000000        
+1.632000        8.714650        8.714650        5.129768        12.757521       12.757521       15.132782       15.132782       19.299372       19.299372       21.467915       21.467915       24.972680       24.972680       19.672340       27.024481       27.024481       28.587185       28.587185       33.309821       33.309821       34.866787       34.866787       38.902191       38.902191       33.038006       40.913687       40.913687       41.893676       41.893676       47.112254       47.112254       48.100977       48.100977       52.615488       52.615488       46.241199       54.584753       54.584753       55.038349       55.038349       60.707646       60.707646       61.196608       61.196608       66.137221       66.137221       59.308127       68.071141       68.071141       68.059927       68.059927       74.125293       74.125293       74.174756       74.174756       79.495501       79.495501       79.469368       79.469368       84.667799       84.667799       84.745876       84.745876       89.812215       89.812215       90.008499       90.008499       87.828764       91.936749       91.936749       96.350144       96.350144       98.015654       98.015654       102.254126      102.254126      103.429097      103.429097      100.240384      105.344169      105.344169      108.716083      108.716083      111.397402      111.397402      114.567665      0.000000        
+49065484.652770 49065766.480798 49065766.480798 49064922.448163 49065254.824174 49065254.824174 49064855.994251 49064855.994251 49065287.991179 49065287.991179 49064888.152999 49064888.152999 49065317.057455 49065317.057455 49064879.431549 49065327.674120 49065327.674120 49064924.733918 49064924.733918 49065360.164908 49065360.164908 49064957.077832 49064957.077832 49065389.450818 49065389.450818 49064948.446741 49065400.174667 49065400.174667 49064993.921333 49064993.921333 49065432.868549 49065432.868549 49065026.426106 49065026.426106 49065462.347468 49065462.347468 49065017.873205 49065473.165037 49065473.165037 49065063.495276 49065063.495276 49065506.035072 49065506.035072 49065096.136128 49065096.136128 49065535.679932 49065535.679932 49065087.648925 49065546.577815 49065546.577815 49065133.393946 49065133.393946 49065579.597091 49065579.597091 49065166.145727 49065166.145727 49065609.380717 49065609.380717 49065194.860230 49065194.860230 49065638.305742 49065638.305742 49065223.608757 49065223.608757 49065667.272949 49065667.272949 49065252.386982 49065252.386982 49065658.990318 49065263.289712 49065263.289712 49065705.110400 49065705.110400 49065296.295918 49065296.295918 49065738.239086 49065738.239086 49065326.035265 49065326.035265 49065729.995233 49065336.962269 49065336.962269 49065776.182626 49065776.182626 49065370.006395 49065370.006395 49065809.367845 0.000000        
diff --git a/SD-VBS/benchmarks/localization/data/sim/localization b/SD-VBS/benchmarks/localization/data/sim/localization
new file mode 100755
index 0000000..4650997
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/sim/localization
diff --git a/SD-VBS/benchmarks/localization/data/sim_fast/Makefile b/SD-VBS/benchmarks/localization/data/sim_fast/Makefile
new file mode 100644
index 0000000..236ff8b
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/sim_fast/Makefile
@@ -0,0 +1,8 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=localization
+INPUT=sim_fast
+
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/localization/data/sim_fast/expected.m b/SD-VBS/benchmarks/localization/data/sim_fast/expected.m
new file mode 100644
index 0000000..9841d62
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/sim_fast/expected.m
@@ -0,0 +1,3 @@
+3.685028        3.432348        3.427322        3.424184        3.427974        3.422786        3.419637        3.414578        3.415206        3.410068        3.410692        3.405226        3.405845        3.400579        3.401194        3.405009        3.399313        3.396114        3.390933        3.391537        3.386565        3.387164        3.382115        3.382710        0.000000        
+0.570000        1.130093        1.130093        1.003619        1.457224        1.457224        1.872936        1.872936        2.195236        2.195236        2.517823        2.517823        2.839430        2.839430        2.624478        3.070964        3.070964        3.479898        3.479898        3.796360        3.796360        4.113478        4.113478        4.428227        0.000000        
+14719241.537176 14719192.885416 14719192.885416 14719192.253043 14719194.529914 14719194.529914 14719196.620169 14719196.620169 14719198.260497 14719198.260497 14719199.898726 14719199.898726 14719201.534841 14719201.534841 14719200.454656 14719202.721015 14719202.721015 14719204.800656 14719204.800656 14719206.430317 14719206.430317 14719208.057811 14719208.057811 14719209.683107 0.000000        
diff --git a/SD-VBS/benchmarks/localization/data/sim_fast/localization b/SD-VBS/benchmarks/localization/data/sim_fast/localization
new file mode 100755
index 0000000..82e40a9
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/sim_fast/localization
diff --git a/SD-VBS/benchmarks/localization/data/sqcif/Makefile b/SD-VBS/benchmarks/localization/data/sqcif/Makefile
new file mode 100644
index 0000000..496053b
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/sqcif/Makefile
@@ -0,0 +1,8 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=localization
+INPUT=sqcif
+
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/localization/data/sqcif/expected.m b/SD-VBS/benchmarks/localization/data/sqcif/expected.m
new file mode 100644
index 0000000..ec25c0d
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/sqcif/expected.m
@@ -0,0 +1,3 @@
+1011.303794     817.965338      52.925944       1061.980393     0.000000        
+118.818062      154080.851618   154080.851618   1652.527205     0.000000        
+3926083200.206786       3980824114.940394       3980824114.940394       3925922636.742242       0.000000        
diff --git a/SD-VBS/benchmarks/localization/data/sqcif/localization b/SD-VBS/benchmarks/localization/data/sqcif/localization
new file mode 100755
index 0000000..d26f656
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/sqcif/localization
diff --git a/SD-VBS/benchmarks/localization/data/test/Makefile b/SD-VBS/benchmarks/localization/data/test/Makefile
new file mode 100644
index 0000000..c997c9b
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/test/Makefile
@@ -0,0 +1,8 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=localization
+INPUT=test
+
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/localization/data/test/expected.m b/SD-VBS/benchmarks/localization/data/test/expected.m
new file mode 100644
index 0000000..d64ef46
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/test/expected.m
@@ -0,0 +1,3 @@
+3.685028        3.432348        3.380028        3.349426        0.000000        
+0.570000        6.035935        6.035935        4.771188        0.000000        
+14719241.537176 14719192.900190 14719192.900190 14719192.267816 0.000000        
diff --git a/SD-VBS/benchmarks/localization/data/test/localization b/SD-VBS/benchmarks/localization/data/test/localization
new file mode 100755
index 0000000..2ac32af
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/test/localization
diff --git a/SD-VBS/benchmarks/localization/data/vga/Makefile b/SD-VBS/benchmarks/localization/data/vga/Makefile
new file mode 100644
index 0000000..9d6ce33
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/vga/Makefile
@@ -0,0 +1,7 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=localization
+INPUT=vga
+
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/localization/data/vga/expected.m b/SD-VBS/benchmarks/localization/data/vga/expected.m
new file mode 100644
index 0000000..652c96f
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/vga/expected.m
@@ -0,0 +1,3 @@
+2528.691892     2020.606280     42.673530       2649.158291     -514.634787     -292.512047     2578.263949     -7.269003       194.344630      324.075534      -884.272217     -529.018602     -176.396317     -373.999381     141.933329      509.836051      -61.997773      -777.150225     -582.644009     -1449.348371    117.943370      -1299.856855    -24.357194      303.856978      101.324880      1351.287196     1422.667628     -81.220795      344.584054      305.716500      394.536408      -315.995792     1224.113905     -116.964887     -895.290651     -373.194309     -1302.711786    -1435.755958    -242.449596     -575.245533     -412.057612     -1163.249025    31.633454       -103.634994     415.883979      -436.888318     292.040993      -444.018359     393.038935      455.211286      226.985703      -74.940082      1088.234539     506.285008      -1138.224729    231.353564      1450.108183     424.629158      1302.669340     -76.648346      1416.427855     244.239852      681.206342      -224.646828     1050.911515     9.704005        -1471.352151    -152.384502     480.602928      -1300.853407    143.685698      523.473516      287.188506      131.080484      309.861529      -1053.044149    150.207963      1360.602516     248.798640      1127.783455     1393.329528     1.177020        559.095648      -122.280172     663.266614      -284.008725     -1411.582432    0.000000        
+296.698921      1111596.955926  1111596.955926  5126.049004     1711524.062418  1711524.062418  1121309.558827  1121309.558827  2122440.593817  2122440.593817  1725419.018071  1725419.018071  2432383.209869  2432383.209869  1024122.336452  2673880.369984  2673880.369984  1845737.015282  1845737.015282  2878366.041242  2878366.041242  2287693.000146  2287693.000146  3049953.380640  3049953.380640  1482353.660475  3188497.912222  3188497.912222  2229222.979737  2229222.979737  3305572.873952  3305572.873952  2612927.563784  2612927.563784  3403916.191632  3403916.191632  1753858.573799  3484955.565597  3484955.565597  2457415.775389  2457415.775389  3562678.977792  3562678.977792  2811889.463107  2811889.463107  3634601.849246  3634601.849246  1933573.519582  3697605.496416  3697605.496416  2624334.404817  2624334.404817  3762379.511669  3762379.511669  2969426.090059  2969426.090059  3822569.851774  3822569.851774  3195245.108477  3195245.108477  3881298.776581  3881298.776581  3368029.173453  3368029.173453  3937734.089771  3937734.089771  3515391.167840  3515391.167840  2881400.524568  3633838.763944  3633838.763944  3446715.106174  3446715.106174  3742334.428186  3742334.428186  3694017.653500  3694017.653500  3843749.772586  3843749.772586  2733802.286928  3926154.773246  3926154.773246  3358856.453555  3358856.453555  4004479.104494  4004479.104494  3646943.706728  0.000000        
+9815876281.390493       10219639146.152300      10219639146.152300      9815391366.338209       10092396791.994455      10092396791.994455      9820918023.651031       9820918023.651031       10026942674.566353      10026942674.566353      9824054607.271921       9824054607.271921       9986540179.952711       9986540179.952711       9820749328.610571       9958801841.680529       9958801841.680529       9825149742.124517       9825149742.124517       9937856152.645214       9937856152.645214       9827762146.439236       9827762146.439236       9919827156.765738       9919827156.765738       9824274661.168266       9902186131.605909       9902186131.605909       9828584290.748890       9828584290.748890       9890460431.944111       9890460431.944111       9831101864.497566       9831101864.497566       9882225999.229254       9882225999.229254       9827389673.717871       9876391451.389120       9876391451.389120       9831433794.626633       9831433794.626633       9872465819.701366       9872465819.701366       9833630954.938072       9833630954.938072       9870024758.678486       9870024758.678486       9829700710.912729       9867664635.469746       9867664635.469746       9833696340.678921       9833696340.678921       9865370958.567533       9865370958.567533       9835815770.213318       9835815770.213318       9864069463.541668       9864069463.541668       9837362817.867367       9837362817.867367       9862759213.674345       9862759213.674345       9838621454.607281       9838621454.607281       9861780884.733627       9861780884.733627       9839784146.273586       9839784146.273586       9855374465.163700       9840749921.502296       9840749921.502296       9856998863.783821       9856998863.783821       9841720196.125462       9841720196.125462       9857185100.692745       9857185100.692745       9842629577.938219       9842629577.938219       9851296681.760395       9843405989.632635       9843405989.632635       9853618282.752998       9853618282.752998       9844190452.540911       9844190452.540911       9854355745.217056       0.000000        
diff --git a/SD-VBS/benchmarks/localization/data/vga/localization b/SD-VBS/benchmarks/localization/data/vga/localization
new file mode 100755
index 0000000..cf7cdfd
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/data/vga/localization
diff --git a/SD-VBS/benchmarks/localization/src/c/eul2quat.c b/SD-VBS/benchmarks/localization/src/c/eul2quat.c
new file mode 100644
index 0000000..bea75cf
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/eul2quat.c
@@ -0,0 +1,50 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "localization.h"
+
+F2D* eul2quat(F2D* angle)
+{
+    F2D *ret;
+    F2D *x, *y, *z;
+    int k, i, j;
+    int rows, cols;
+
+    rows = angle->height;
+    cols = angle->width;
+
+    x = fDeepCopyRange(angle, 0, angle->height, 0, 1);
+    y = fDeepCopyRange(angle, 0, angle->height, 1, 1);
+    z = fDeepCopyRange(angle, 0, angle->height, 2, 1);
+
+    ret = fSetArray(x->height, 4, 0);
+    
+    for(i=0; i<rows; i++)
+    {
+        float xi, yi, zi;
+        k = 0;
+        xi = asubsref(x,i);
+        yi = asubsref(y,i);
+        zi = asubsref(z,i);
+
+        subsref(ret,i,k) = cos(xi/2)*cos(yi/2)*cos(zi/2)+sin(xi/2)*sin(yi/2)*sin(zi/2);
+        k++;
+        subsref(ret,i,k) = sin(xi/2)*cos(yi/2)*cos(zi/2)-cos(xi/2)*sin(yi/2)*sin(zi/2);
+        k++;
+        subsref(ret,i,k) = cos(xi/2)*sin(yi/2)*cos(zi/2)+sin(xi/2)*cos(yi/2)*sin(zi/2);
+        k++;
+        subsref(ret,i,k) = cos(xi/2)*cos(yi/2)*sin(zi/2)-sin(xi/2)*sin(yi/2)*cos(zi/2);
+    }
+
+    fFreeHandle(x);
+    fFreeHandle(y);
+    fFreeHandle(z);
+
+    return ret;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/generateSample.c b/SD-VBS/benchmarks/localization/src/c/generateSample.c
new file mode 100644
index 0000000..3acb4d7
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/generateSample.c
@@ -0,0 +1,88 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "localization.h"
+
+void generateSample(F2D *w, F2D *quat, F2D *vel, F2D *pos)
+{
+    int rows, cols, i, j, index;
+    I2D *sampleXId;
+    F2D *retQuat, *retVel, *retPos;
+
+    sampleXId = weightedSample(w);
+
+    rows = sampleXId->height;
+    cols = sampleXId->width;
+
+    if(cols > 1)
+        printf("ERROR: Cols more than 1.. Handle this case \n");
+
+    retQuat = fSetArray(quat->height, quat->width, 0);
+    retVel = fSetArray(vel->height, vel->width, 0);
+    retPos = fSetArray(pos->height, pos->width, 0);
+
+    for(i=0; i<rows; i++)
+    {
+        index = asubsref(sampleXId, i) - 1;
+        for(j=0; j<quat->width; j++)
+        {
+            subsref(retQuat,i,j) = subsref(quat,index,j);
+        }
+    }
+
+    for(i=0; i<rows; i++)
+    {
+        index = asubsref(sampleXId, i) - 1;
+        for(j=0; j<vel->width; j++)
+        {
+            subsref(retVel,i,j) = subsref(vel,index,j);
+        }
+    }
+    
+    for(i=0; i<rows; i++)
+    {
+        index = asubsref(sampleXId, i) - 1;
+        for(j=0; j<pos->width; j++)
+        {
+            subsref(retPos,i,j) = subsref(pos,index,j);
+        }
+    }
+
+    for(i=0; i<quat->height; i++)
+    {
+        for(j=0; j<quat->width; j++)
+        {
+            subsref(quat,i,j) = subsref(retQuat,i,j);
+        }
+    }
+
+    for(i=0; i<vel->height; i++)
+    {
+        for(j=0; j<vel->width; j++)
+        {
+            subsref(vel,i,j) = subsref(retVel,i,j);
+        }
+    }
+    
+    for(i=0; i<pos->height; i++)
+    {
+        for(j=0; j<pos->width; j++)
+        {
+            subsref(pos,i,j) = subsref(retPos,i,j);
+        }
+    }
+    
+    fFreeHandle(retQuat);
+    fFreeHandle(retVel);
+    fFreeHandle(retPos);
+    iFreeHandle(sampleXId);
+    
+    return;
+}
+
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/get3DGaussianProb.c b/SD-VBS/benchmarks/localization/src/c/get3DGaussianProb.c
new file mode 100644
index 0000000..58c4475
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/get3DGaussianProb.c
@@ -0,0 +1,49 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "localization.h"
+
+F2D* get3DGaussianProb( F2D* data, F2D* mean, F2D* A)
+{
+    F2D *p, *diff, *temp1, *temp2, *mt;
+    float temp;
+    int n_data, n_channel;
+    int i, j, k;
+    F2D* t;
+    float pi = 3.1412;
+
+    n_data = data->height;
+    n_channel = data->width;
+
+    t = fSetArray(n_data, 1, 1);
+
+    mt = fMtimes(t, mean); 
+    diff = fMinus( data, mt);
+    p = fSetArray(diff->height, 1, 0);
+
+    temp = sqrt(1.0/(pow(2*pi, n_channel)));
+    temp2 = randWrapper(diff->height,1);
+
+    j = (temp2->height*temp2->width);
+    for(i=0; i<j; i++)
+    {
+        float temp2i;
+        temp2i = asubsref(temp2,i);
+
+        temp2i = exp(-0.5*temp2i);
+        asubsref(p,i) = temp2i*temp;
+    }
+
+    fFreeHandle(t);
+    fFreeHandle(temp2);
+    fFreeHandle(mt);
+    fFreeHandle(diff);
+    
+    return p;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/localization.h b/SD-VBS/benchmarks/localization/src/c/localization.h
new file mode 100644
index 0000000..b2c03bb
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/localization.h
@@ -0,0 +1,24 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#ifndef _LOCALIZATION_
+#define _LOCALIZATION_
+
+#include "sdvbs_common.h"
+
+int script_localization();
+F2D* eul2quat(F2D* angle);
+void generateSample(F2D *w, F2D *quat, F2D *vel, F2D *pos);
+F2D* get3DGaussianProb( F2D* data, F2D* mean, F2D* A);
+F2D* mcl(F2D* x, F2D* sData, F2D* invConv);
+F2D* quat2eul(F2D* quat);
+F2D* quatConj(F2D* a);
+F2D* quatMul(F2D* a, F2D* b);
+F2D* quatRot(F2D* vec, F2D* rQuat);
+F2D* readSensorData(I2D* index, F2D* fid, I2D* type, I2D* eof);
+I2D* weightedSample(F2D* w);
+
+#endif
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/mcl.c b/SD-VBS/benchmarks/localization/src/c/mcl.c
new file mode 100644
index 0000000..a3c56b6
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/mcl.c
@@ -0,0 +1,34 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "localization.h"
+
+F2D* mcl(F2D* x, F2D* sData, F2D* invConv)
+{
+    int i, j;
+    F2D *retW, *retX, *sum;
+    float sumVal;
+
+    retX = fDeepCopy(x);
+    retW = get3DGaussianProb(retX, sData, invConv);
+    sum = fSum(retW);
+    if(sum->height == 1 && sum->width ==1)
+    {
+        sumVal = asubsref(sum,0);
+        for(i=0; i<retW->height; i++)
+            for(j=0; j<retW->width; j++)
+                subsref(retW,i,j) = subsref(retW,i,j)/sumVal;
+    }
+    else
+        retW = fMdivide(retW, sum);
+
+    fFreeHandle(retX);
+    fFreeHandle(sum);
+
+    return retW;
+}
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/quat2eul.c b/SD-VBS/benchmarks/localization/src/c/quat2eul.c
new file mode 100644
index 0000000..bc581c9
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/quat2eul.c
@@ -0,0 +1,47 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "localization.h"
+#include <math.h>
+
+F2D* quat2eul(F2D* quat)
+{
+    F2D *retEul;
+    int i, j, k;
+    int rows, cols;
+
+    rows = quat->height;
+    cols = quat->width;
+
+    retEul = fSetArray(rows, 3, 0);
+
+    for(i=0; i<rows; i++)
+    {
+        float temp, temp1, temp2, temp3, temp4;
+        float quati2, quati3, quati1, quati0;
+
+        quati0 = subsref(quat,i,0);
+        quati1 = subsref(quat,i,1);
+        quati2 = subsref(quat,i,2);
+        quati3 = subsref(quat,i,3);
+
+        temp = 2 *quati2 * quati3 + quati0 * quati1;
+        temp1 = pow(quati0,2) - pow(quati1,2) - pow(quati2,2) + pow(quati3,2);
+        temp2 = -2*quati1 * quati2 + quati0 * quati3;
+        temp3 = 2*quati1 * quati2 + quati0 * quati3;
+        temp4 = pow(quati0,2) + pow(quati1,2) - pow(quati2,2) - pow(quati3,2);
+        
+        asubsref(retEul,k++) = atan2(temp, temp1);
+        asubsref(retEul,k++) = asin(temp2);
+        asubsref(retEul,k++) = atan2(temp3, temp4);
+    }
+
+    return retEul;
+}
+
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/quatConj.c b/SD-VBS/benchmarks/localization/src/c/quatConj.c
new file mode 100644
index 0000000..6607186
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/quatConj.c
@@ -0,0 +1,32 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "localization.h"
+
+F2D* quatConj(F2D* a)
+{
+    F2D* retQuat;
+    int rows, cols;
+    int i, j, k;
+
+    rows = a->height;
+    cols = a->width;
+    retQuat = fSetArray(rows, 4, 0);
+
+    for(i=0; i<rows; i++)
+    {
+        k=0;
+        subsref(retQuat,i,k++) = subsref(a,i,0);
+        subsref(retQuat,i,k++) = -subsref(a,i,1);
+        subsref(retQuat,i,k++) = -subsref(a,i,2);
+        subsref(retQuat,i,k) = -subsref(a,i,3);
+    }
+
+    return retQuat;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/quatMul.c b/SD-VBS/benchmarks/localization/src/c/quatMul.c
new file mode 100644
index 0000000..8b8dafe
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/quatMul.c
@@ -0,0 +1,55 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "localization.h"
+
+F2D* quatMul(F2D* a, F2D* b)
+{
+    int ra, ca, rb, cb;
+    F2D *ret;
+    int i, j, k=0;
+
+    ra = a->height;
+    ca = a->width;
+
+    rb = b->height;
+    cb = b->width;
+
+    ret = fSetArray(ra, 4, 0);
+
+    j = 0;
+    for(i=0; i<ra; i++)
+    {
+        k = 0;
+        float ai0, ai1, ai2, ai3;
+        float bj0, bj1, bj2, bj3;
+
+        ai0 = subsref(a,i,0);
+        ai1 = subsref(a,i,1);
+        ai2 = subsref(a,i,2);
+        ai3 = subsref(a,i,3);
+        
+        bj0 = subsref(b,j,0);
+        bj1 = subsref(b,j,1);
+        bj2 = subsref(b,j,2);
+        bj3 = subsref(b,j,3);
+        
+        subsref(ret,i,k++) = ai0*bj0 - ai1*bj1 - ai2*bj2 - ai3*bj3;
+        subsref(ret,i,k++) = ai0*bj1 + ai1*bj0 + ai2*bj3 - ai3*bj2;
+        subsref(ret,i,k++) = ai0*bj2 - ai1*bj3 + ai2*bj0 + ai3*bj1;
+        subsref(ret,i,k++) = ai0*bj3 + ai1*bj2 - ai2*bj1 + ai3*bj0;
+    
+        if(rb == ra)
+            j++;
+    }
+
+    return ret;
+}
+
+
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/quatRot.c b/SD-VBS/benchmarks/localization/src/c/quatRot.c
new file mode 100644
index 0000000..4962b55
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/quatRot.c
@@ -0,0 +1,47 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "localization.h"
+
+F2D* quatRot(F2D* vec, F2D* rQuat)
+{
+    F2D *ret;
+    int nr, i, j, k, rows, cols;
+    F2D *tv, *vQuat, *temp, *temp1;
+    F2D *retVec;
+
+    nr = vec->height;
+    tv = fSetArray(nr, 1, 0);
+    vQuat = fHorzcat(tv, vec);
+    temp = quatMul(rQuat, vQuat);
+    temp1 = quatConj(rQuat);
+    retVec = quatMul(temp, temp1);
+
+    rows = retVec->height;
+    cols = retVec->width;
+
+    ret = fSetArray(rows, 3, 0);
+
+    for(i=0; i<rows; i++)
+    {
+        k = 0;
+        for(j=1; j<4; j++)
+        {
+            subsref(ret,i,k) = subsref(retVec,i,j);
+            k++;
+        }
+    }
+
+    fFreeHandle(tv);
+    fFreeHandle(vQuat);
+    fFreeHandle(temp);
+    fFreeHandle(temp1);
+    fFreeHandle(retVec);
+        
+    return ret;
+}
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/readSensorData.c b/SD-VBS/benchmarks/localization/src/c/readSensorData.c
new file mode 100644
index 0000000..12c0dc0
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/readSensorData.c
@@ -0,0 +1,63 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "localization.h"
+
+F2D* readSensorData(I2D* index, F2D* fid, I2D* type, I2D* eof)
+{
+    F2D *retData;
+    int rows, i, j, k;
+    int atype=-1, aindex;
+
+    aindex = asubsref(index, 0);
+
+    asubsref(index,0) = asubsref(index,0) + 1;
+    rows = fid->height;
+    asubsref(type,0) = 0;
+    retData = fSetArray(1, 8, 0);
+    
+    if( asubsref(index,0) > (rows-1) )
+        asubsref(eof,0) = 1;
+    else
+    {
+        if( asubsref(index,0) == rows)
+            asubsref(eof,0) = 1;
+        else
+            asubsref(eof,0) = 0;
+
+        k = asubsref(index,0);
+        atype = subsref(fid, k, 1);
+        if( (atype == 1) || (atype == 2) || (atype == 3) )
+        {
+            for(i=0; i<3; i++)
+            {
+                asubsref(retData,i) = subsref(fid,k,(i+2));
+            }
+        }
+        if( atype == 4 )
+        {
+            for(i=0; i<3; i++)
+            {
+                asubsref(retData,i) = subsref(fid,k,(i+2));
+            }
+            for(i=3; i<8; i++)
+            {
+                asubsref(retData,i) = subsref(fid,k+1,(i-3));
+            }
+            aindex = aindex + 1;
+        }
+        aindex = aindex + 1;
+    }
+
+    asubsref(index,0) = aindex;
+    asubsref(type, 0) = atype;
+
+    return retData;
+}
+
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/script_localization.c b/SD-VBS/benchmarks/localization/src/c/script_localization.c
new file mode 100644
index 0000000..3392320
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/script_localization.c
@@ -0,0 +1,534 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <malloc.h>
+#include "localization.h"
+#include "extra.h"
+#define LOCOLIZATION_MEM 1<<24
+int main(int argc, char* argv[])
+{
+    SET_UP
+    mallopt(M_TOP_PAD, LOCOLIZATION_MEM);
+    mallopt(M_MMAP_MAX, 0);
+    int n, i, j, k, icount=-1;
+    F2D* fid;
+    float gyroTimeInterval=0.01;
+    float acclTimeInterval=0.01;
+
+    float STDDEV_GPSVel=0.5;
+    float STDDEV_ODOVel=0.1;
+    float STDDEV_ACCL=1;
+    float M_STDDEV_GYRO=0.1;
+    float M_STDDEV_POS=0.1;
+    float M_STDDEV_VEL=0.02;
+
+    F2D *pos, *vel;
+    float pi = 3.1416;
+    F2D *eul1, *eul2, *quat;
+    F2D *sData, *gyro, *norm_gyro, *angleAlpha;
+    F2D *quatDelta, *Opos, *temp_STDDEV_GPSPos, *w;
+    F2D *qConj, *orgWorld, *accl, *gtemp;
+    F2D *gravity, *t1;
+    I2D *tStamp, *sType, *isEOF;
+    I2D *index;
+    int rows, cols;
+    F2D *resultMat;
+    F2D *STDDEV_GPSPos;
+    F2D *ones, *randW;
+
+    char im1[100];
+
+    printf("Input txt File: ");
+    scanf("%s", im1);
+
+    fid = readFile(im1);
+
+    n = 1000;
+
+    #ifdef test
+        n = 3;
+        gyroTimeInterval = 0.1;
+        acclTimeInterval = 0.1;
+        M_STDDEV_VEL = 0.2;
+    #endif
+    #ifdef sim_fast
+        n = 3;
+    #endif
+    #ifdef sim
+        n = 10;
+    #endif
+    #ifdef sqcif
+        n = 800;
+    #endif
+    #ifdef qcif
+        n = 500;
+    #endif
+    #ifdef vga
+        n = 2000;
+    #endif
+    #ifdef wuxga
+        n = 3000;
+    #endif
+
+    resultMat = fSetArray(3,fid->height, 0);
+
+    pos = fSetArray(n, 3, 0);
+    vel = fSetArray(n, 3, 0);
+    ones = fSetArray(n,1,1);
+
+    
+    F2D *randn;
+
+    randn = randWrapper(n,3);
+    printf("start\n");
+    for_each_job{
+        fResetArray(pos,n, 3, 0);
+        fResetArray(vel,n, 3, 0);
+        fResetArray(ones,n,1,1);
+
+        {
+            int j;
+            for(i=0; i<n; i++)
+                for(j=0; j<3; j++)
+                    subsref(vel, i, j) += subsref(randn,i,j) * STDDEV_ODOVel;
+
+        }  
+
+
+ 
+        {
+            F2D *eulAngle, *randn;
+            eulAngle = fSetArray(n, 3, 0);
+            randn = randWrapper(n,1);
+    
+            for(i=0; i<n; i++)
+            {
+                subsref(eulAngle, i, 2) = subsref(randn, i, 0) * 2 * pi;
+            }
+            
+            eul1 = eul2quat(eulAngle); 
+            fFreeHandle(eulAngle);
+    
+            eulAngle = fSetArray(1, 3, 0);
+            subsref(eulAngle, 0, 0) = pi;
+            eul2 = eul2quat(eulAngle);
+            
+            fFreeHandle(randn);
+            fFreeHandle(eulAngle);
+        }
+        
+        quat = quatMul(eul1, eul2);
+        fFreeHandle(eul1);
+        fFreeHandle(eul2);
+    
+        i=0;
+        index = iSetArray(1,1,-1);
+        sType = iSetArray(1,1,-1);
+        isEOF = iSetArray(1,1,-1);
+        
+    
+        rows =0;
+        cols = 5;
+        STDDEV_GPSPos = fSetArray(3,3,0);
+        randW = randnWrapper(n,3);
+        icount=-1;
+        while(1)
+        {
+            icount=icount+1;
+            
+            /*     
+            S = 4
+            A = 3
+            G = 2
+            V = 1
+            */
+    
+            sData = readSensorData(index, fid, sType, isEOF);    
+            rows++;
+    
+    
+    
+            if( asubsref(sType,0) ==2)
+            {
+    
+            //Motion model
+                
+                {
+                    int i;
+                    F2D *t, *t1;
+                    F2D *abc, *abcd;
+                    int qD_r=0, qD_c=0;
+                    F2D *cosA, *sinA;
+                    
+                    t = fDeepCopyRange(sData, 0, 1, 0, 3);
+                    gyro = fMtimes(ones, t);
+                    abc = fMallocHandle(gyro->height, gyro->width);
+                    t1 = fDeepCopy(randW);
+                                    
+                    for(i=0; i<(n*3); i++)
+                    {
+                        asubsref(t1,i) = asubsref(randW,i) * M_STDDEV_GYRO;
+                        asubsref(gyro, i) += asubsref(t1,i);
+                        asubsref(abc, i) = pow(asubsref(gyro, i), 2);
+                    }
+                    fFreeHandle(t1);
+                    abcd = fSum2(abc, 2);
+    
+                    norm_gyro = fMallocHandle(abcd->height,abcd->width);
+                    angleAlpha = fMallocHandle(abcd->height, abcd->width);
+    
+                    for(i=0; i<(abcd->height*abcd->width); i++)
+                    {
+                        asubsref(norm_gyro, i) = sqrt(asubsref(abcd,i));
+                        asubsref(angleAlpha,i) = asubsref(norm_gyro,i) * gyroTimeInterval;
+                    }
+    
+                    qD_r += angleAlpha->height + gyro->height;
+                    qD_c += angleAlpha->width + 3;
+                    
+                    fFreeHandle(t);
+                    fFreeHandle(abcd); 
+                    
+                    cosA = fSetArray(angleAlpha->height, angleAlpha->width, 0);
+                    sinA = fSetArray(angleAlpha->height, angleAlpha->width, 0);
+    
+                    for(i=0; i<(cosA->height*cosA->width); i++)
+                        asubsref(cosA,i) = cos( asubsref(angleAlpha,i) /2 );
+     
+                    for(i=0; i<(sinA->height*sinA->width); i++)
+                        asubsref(sinA,i) = sin( asubsref(angleAlpha,i) /2 );
+        
+                    
+                    fFreeHandle(abc);
+                    abc = fSetArray(1,3,1);
+                    t1 = fMtimes(norm_gyro, abc);
+                    t = ffDivide(gyro, t1);
+                    fFreeHandle(t1);
+    
+                    abcd = fMtimes(sinA, abc);
+                    t1 = fTimes(t, abcd);
+                    quatDelta = fHorzcat(cosA, t1);
+                    
+                    fFreeHandle(abcd);
+                    fFreeHandle(t);
+                    fFreeHandle(t1);
+                    fFreeHandle(abc);
+    
+                    t = quatMul(quat, quatDelta);
+                    fFreeHandle(quat);
+                    fFreeHandle(quatDelta);
+                    quat = fDeepCopy(t);
+                    
+                    fFreeHandle(t);
+                    fFreeHandle(norm_gyro);
+                    fFreeHandle(gyro);
+                    fFreeHandle(angleAlpha);
+                    fFreeHandle(cosA);
+                    fFreeHandle(sinA);
+    
+                }            
+           }
+    
+         if( asubsref(sType,0) ==4)
+         {
+             //Observation
+            
+            float tempSum=0;
+            F2D *Ovel;
+            float OvelNorm;
+            int i;
+    
+    
+            asubsref(STDDEV_GPSPos, 0) = asubsref(sData, 6);
+            asubsref(STDDEV_GPSPos, 4) = asubsref(sData,7);
+            asubsref(STDDEV_GPSPos, 8) = 15;
+    
+            Opos = fDeepCopyRange(sData, 0, 1, 0, 3);
+     
+            //Initialize
+             
+            for(i=0; i<(pos->height*pos->width); i++)
+                tempSum += asubsref(pos,i);
+    
+            if(tempSum == 0)
+            {
+                F2D *t, *t1;
+                t = fMtimes( randW, STDDEV_GPSPos);
+                t1 = fMtimes(ones, Opos);
+    
+                for(i=0; i<(pos->height*pos->width); i++)
+                    asubsref(pos,i) = asubsref(t,i) + asubsref(t1,i);
+    
+                fFreeHandle(t);
+                fFreeHandle(t1);
+            }
+            else 
+            {
+                int rows, cols;
+                int mnrows, mncols;
+    
+                rows = STDDEV_GPSPos->height;
+                cols = STDDEV_GPSPos->width;
+    
+                temp_STDDEV_GPSPos = fSetArray(rows,cols,1);
+                for( mnrows=0; mnrows<rows; mnrows++)
+                {
+                    for( mncols=0; mncols<cols; mncols++)
+                    {
+                        subsref(temp_STDDEV_GPSPos,mnrows,mncols) = pow(subsref(STDDEV_GPSPos,mnrows,mncols),-1);
+                    }
+                }
+    
+                w = mcl(pos, Opos , temp_STDDEV_GPSPos);
+                generateSample(w, quat, vel, pos);
+            }
+            fFreeHandle(Opos);
+    
+            //compare direction
+            Ovel = fDeepCopyRange(sData, 0, 1, 3, 3);
+            OvelNorm=2;//1.1169e+09;
+        
+            if (OvelNorm>0.5)
+            {
+                F2D *t;
+                t = fDeepCopy(Ovel);
+                fFreeHandle(Ovel);
+                /* This is a double precision division */
+                Ovel = fDivide(t, OvelNorm);
+                qConj = quatConj(quat);
+                fFreeHandle(t);
+                
+                {
+                    t = fSetArray(1,3,0);
+                    subsref(t,0,0) = 1;
+                    orgWorld = quatRot(t, qConj);
+                    fFreeHandle(t);
+                    fFreeHandle(qConj);
+                    t = fSetArray(3,3,0);
+                    asubsref(t,0) = 1;
+                    asubsref(t,4) = 1;
+                    asubsref(t,8) = 1;
+                   
+                    {
+                        int i;
+                        for(i=0; i<(t->height*t->width); i++)
+                            asubsref(t, i) = asubsref(t,i)/STDDEV_GPSVel;
+                        w = mcl( orgWorld, Ovel, t);
+                        generateSample(w, quat, vel, pos);
+                    }
+    
+                    fFreeHandle(t);
+                    fFreeHandle(w);
+                    fFreeHandle(orgWorld);
+                }
+            }
+            fFreeHandle(Ovel);
+        }
+        
+        if( asubsref(sType,0) ==1)
+        {
+            //Observation
+            F2D *Ovel;
+            F2D *t, *t1, *t2;
+            float valVel;
+    
+            t = fSetArray(vel->height, 1, 0);
+    
+            for(i=0; i<vel->height; i++)
+            {
+                subsref(t,i,0) = sqrt(pow(subsref(vel,i,0),2) + pow(subsref(vel,i,1),2) + pow(subsref(vel,i,2),2));
+            }
+    
+            Ovel = fSetArray(1, 1, asubsref(sData,0));
+            valVel = 1.0/STDDEV_ODOVel;
+    
+            t1 = fSetArray(1,1,(1.0/STDDEV_ODOVel));
+            w = mcl (t, Ovel, t1);
+            generateSample(w, quat, vel, pos);
+    
+            
+            fFreeHandle(w);
+            fFreeHandle(t);
+            fFreeHandle(t1);
+            fFreeHandle(Ovel);
+        }
+        
+        if( asubsref(sType,0) ==3)
+        {
+            //Observation
+            F2D *t;
+            t = fSetArray(1, 3, 0);
+            asubsref(t,2) = -9.8;
+    
+            accl = fDeepCopyRange(sData, 0, 1, 0, 3);
+            gtemp = fMtimes( ones, t); 
+            gravity = quatRot(gtemp, quat);
+    
+            fFreeHandle(gtemp);
+            fFreeHandle(t);
+            t = fSetArray(3,3,0);
+            asubsref(t,0) = 1;
+            asubsref(t,4) = 1;
+            asubsref(t,8) = 1;
+            
+            {                
+                int i;
+                for(i=0; i<(t->height*t->width); i++)
+                    asubsref(t,i) = asubsref(t,i)/STDDEV_ACCL;
+                w = mcl( gravity, accl, t);
+            }
+            
+            generateSample(w, quat, vel, pos);
+            fFreeHandle(t);
+            //Motion model
+            t = fMtimes(ones, accl);
+            fFreeHandle(accl);
+    
+            accl = fMinus(t, gravity);
+            
+            fFreeHandle(w);
+            fFreeHandle(gravity);
+            fFreeHandle(t);
+    
+            {
+                //pos=pos+quatRot(vel,quatConj(quat))*acclTimeInterval+1/2*quatRot(accl,quatConj(quat))*acclTimeInterval^2+randn(n,3)*M_STDDEV_POS;            
+                
+                F2D *s, *is;
+                int i;
+                is = quatConj(quat);
+                s = quatRot(vel, is);
+                fFreeHandle(is);
+    
+                for(i=0; i<(s->height*s->width); i++)
+                {
+                    asubsref(s,i) = asubsref(s,i)*acclTimeInterval;   //+(1/2);
+                }
+                is = fPlus(pos, s);
+                fFreeHandle(pos);
+                pos = fDeepCopy(is);
+                fFreeHandle(is);
+                fFreeHandle(s);
+    
+                /** pos_ above stores: pos+quatRot(vel,quatConj(quat))*acclTimeInterval **/
+                
+                is = quatConj(quat);
+                s = quatRot(accl, is);
+                t = fDeepCopy(s);
+                for(i=0; i<(s->height*s->width); i++)
+                {
+                    asubsref(t,i) = 1/2*asubsref(s,i)*acclTimeInterval*acclTimeInterval;
+                }
+    
+                /** t_ above stores: 1/2*quatRot(accl,quatCong(quat))*acclTimeInterval^2 **/
+    
+                fFreeHandle(s);
+                fFreeHandle(is);
+                s = randnWrapper(n,3);
+    
+                for(i=0; i<(s->height*s->width); i++)
+                {
+                    asubsref(s,i) = asubsref(s,i) * M_STDDEV_POS;
+                }
+    
+                /** s_ above stores: randn(n,3)*M_STDDEV_POS **/
+    
+                is = fPlus(pos, t);
+                fFreeHandle(pos);
+                pos = fPlus(is, s);
+    
+                fFreeHandle(s);
+                fFreeHandle(t);
+                fFreeHandle(is);
+            
+    //            vel=vel+accl*acclTimeInterval+randn(n,3)*M_STDDEV_VEL; %??
+                
+                t = fDeepCopy(accl);
+                for(i=0; i<(accl->height*accl->width); i++)
+                    asubsref(t,i) = asubsref(accl,i) * acclTimeInterval;
+                
+                is = fPlus(vel, t);
+    
+                fFreeHandle(accl);
+                fFreeHandle(t);
+                s = randnWrapper(n,3);
+                for(i=0; i<(s->height*s->width); i++)
+                {
+                    asubsref(s,i) = asubsref(s,i) * M_STDDEV_VEL;
+                }
+    
+                fFreeHandle(vel);
+                vel = fPlus(is, s);
+                fFreeHandle(is);
+                fFreeHandle(s);
+           }
+    
+        }
+    
+            // Self check
+            {
+                F2D* temp;
+                float quatOut=0, velOut=0, posOut=0;
+                int i;
+    
+                for(i=0; i<(quat->height*quat->width); i++)
+                    quatOut += asubsref(quat, i);
+    
+                for(i=0; i<(vel->height*vel->width); i++)
+                    velOut += asubsref(vel, i);
+                
+                for(i=0; i<(pos->height*pos->width); i++)
+                    posOut += asubsref(pos, i);
+                
+                subsref(resultMat,0,icount) = quatOut;
+                subsref(resultMat,1,icount) = velOut;
+                subsref(resultMat,2,icount) = posOut;
+            }
+    
+            fFreeHandle(sData);
+    
+        
+            if (asubsref(isEOF,0) == 1)
+               break;
+        }
+    }
+    printf("end..\n");
+
+#ifdef CHECK   
+    
+    // Self checking - use expected.txt from data directory
+    {
+        int ret=0;
+        float tol = 2.0;
+#ifdef GENERATE_OUTPUT
+        fWriteMatrix(resultMat, argv[1]);
+#endif
+        ret = fSelfCheck(resultMat, "./expected_C.txt", tol);
+        if (ret == -1)
+            printf("Error in Localization\n");
+    }
+    // Self checking done
+#endif
+
+    
+    fFreeHandle(STDDEV_GPSPos);
+    iFreeHandle(index);
+    iFreeHandle(sType);
+    iFreeHandle(isEOF);
+    fFreeHandle(fid);
+    fFreeHandle(resultMat);
+    fFreeHandle(pos);
+    fFreeHandle(vel);
+    fFreeHandle(quat);
+    fFreeHandle(ones);
+    fFreeHandle(randW);
+    fFreeHandle(randn);
+    WRITE_TO_FILE
+    return 0;
+
+}
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/c/weightedSample.c b/SD-VBS/benchmarks/localization/src/c/weightedSample.c
new file mode 100644
index 0000000..28099e8
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/c/weightedSample.c
@@ -0,0 +1,37 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <math.h>
+#include "localization.h"
+
+I2D* weightedSample(F2D* w)
+{
+    I2D *bin;
+    F2D *seed;
+    int n, i, j;
+
+    n = w->height;
+    seed = randWrapper(n, 1);
+    bin = iSetArray(n, 1, 0);
+
+    for(i=0; i<n; i++)
+    {
+        for(j=0; j<n; j++)
+        {
+            if(asubsref(seed,j) > 0)
+                asubsref(bin,j) = asubsref(bin,j) + 1;
+        }
+        for(j=0; j<n; j++)
+            asubsref(seed,j) = asubsref(seed,j) - asubsref(w,i);
+    }
+
+    free(seed);
+    return bin;
+}
+
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/addEulNoise.m b/SD-VBS/benchmarks/localization/src/matlab/addEulNoise.m
new file mode 100644
index 0000000..3d2ac76
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/addEulNoise.m
@@ -0,0 +1,12 @@
+function retQuat=addEulNoise(quat, STD)
+n=size(quat,1);
+
+% KVS: replacing randnWrapper(n,3) with rand(n,3)
+gyro=randnWrapper(n,3)*STD;
+
+norm_gyro=sqrt(sum(gyro.^2,2));
+angleAlpha=norm_gyro;
+quatDelta=[cos(angleAlpha/2), gyro./(norm_gyro*ones(1,3)).*(sin(angleAlpha/2)*ones(1,3))];
+
+retQuat=quatMul(quat, quatDelta);
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/calculate3DGaussian.m b/SD-VBS/benchmarks/localization/src/matlab/calculate3DGaussian.m
new file mode 100644
index 0000000..060713a
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/calculate3DGaussian.m
@@ -0,0 +1,11 @@
+function [meanColor A]=calculate3DGaussian(data)
+n_data=size(data,1);
+n_channel=size(data,2);
+meanColor=mean(data);
+diff=double(data)-ones(n_data,1)*meanColor;
+diifTr = transpose(diff);
+Ainv=(diffTr*diff/n_data);
+AinvTr = transpose(Ainv);
+A=inv(AinvTr);
+
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/drawLog.m b/SD-VBS/benchmarks/localization/src/matlab/drawLog.m
new file mode 100644
index 0000000..f88e078
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/drawLog.m
@@ -0,0 +1,44 @@
+function drawLog(data, ground_data)
+subplot(1,3,1);
+[nr nc]=size(data);
+for i=1:nr
+    x=data(i,2);
+    y=data(i,3);
+    z=data(i,4);
+    R=[1 0 0; 0 cos(x) sin(x); 0 -sin(x) cos(x)]...
+        *[cos(y) 0 -sin(y); 0 1 0; sin(y) 0 cos(y)]...
+        *[cos(z) sin(z) 0; -sin(z) cos(z) 0; 0 0 1];
+    coord=R*[1 0 0]';
+    axis([-1 1 -1 1 -1 1]);axis on
+    plot3([0 coord(1)], [0 coord(2)], [0 coord(3)], 'b'); hold on
+end
+
+[nr nc]=size(ground_data);
+for i=1:nr
+x=ground_data(i,2);
+y=ground_data(i,3);
+z=ground_data(i,4);
+R=[1 0 0; 0 cos(x) sin(x); 0 -sin(x) cos(x)]...
+        *[cos(y) 0 -sin(y); 0 1 0; sin(y) 0 cos(y)]...
+        *[cos(z) sin(z) 0; -sin(z) cos(z) 0; 0 0 1];
+coord=R*[1 0 0]';
+coord2=R*[0 -1 0]';
+axis([-1 1 -1 1 -1 1]);axis on
+plot3([0 coord(1)], [0 coord(2)], [0 coord(3)], 'r'); hold on
+plot3([0 coord2(1)], [0 coord2(2)], [0 coord2(3)], 'g');
+end
+
+xlabel('x');
+ylabel('y');
+zlabel('z');
+hold off
+drawnow
+subplot(1,3,2);
+Xoffset=4422610;
+Yoffset=483660;
+axis([4422610-Xoffset 4422660-Xoffset 483620-Yoffset 483720-Yoffset]);axis on
+scatter(data(:,5)-Xoffset, data(:,6)-Yoffset, 8, 'b'); hold on
+axis([4422610-Xoffset 4422660-Xoffset 483620-Yoffset 483720-Yoffset]);axis on
+scatter(ground_data(:,5)-Xoffset, ground_data(:,6)-Yoffset, 10, 'r'); hold off
+drawnow
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/eul2quat.m b/SD-VBS/benchmarks/localization/src/matlab/eul2quat.m
new file mode 100644
index 0000000..57001a8
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/eul2quat.m
@@ -0,0 +1,9 @@
+function retQuat=eul2quat(eulAngle)
+x=eulAngle(:,1);
+y=eulAngle(:,2);
+z=eulAngle(:,3);
+retQuat=[cos(x/2).*cos(y/2).*cos(z/2)+sin(x/2).*sin(y/2).*sin(z/2) ...
+        sin(x/2).*cos(y/2).*cos(z/2)-cos(x/2).*sin(y/2).*sin(z/2) ...
+        cos(x/2).*sin(y/2).*cos(z/2)+sin(x/2).*cos(y/2).*sin(z/2) ...
+        cos(x/2).*cos(y/2).*sin(z/2)-sin(x/2).*sin(y/2).*cos(z/2)];
+    
diff --git a/SD-VBS/benchmarks/localization/src/matlab/generateSample.m b/SD-VBS/benchmarks/localization/src/matlab/generateSample.m
new file mode 100644
index 0000000..f3658f8
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/generateSample.m
@@ -0,0 +1,25 @@
+function [retQuat retVel retPos]=generateSample(w, quat, vel, pos, STDDEV_VEL, STDDEV_POS)
+sampledXId=weightedSample(w);
+
+rows = size(sampledXId, 1);
+cols = size(sampledXId, 2);
+
+if(cols > 1)
+    disp(123456);
+end
+
+% retQuat = zeros(rows, 1);
+% retVel = zeros(rows, 1);
+% retPos = zeros(rows, 1);
+
+% for i=1:rows
+%     retQuat(i,1) = quat(sampleXId(i,1),1);
+%     retVel(i,1) = vel(sampleXId(i,1),1) + randnWrapper(1,1) * STDDEV_VEL;
+%     retPos(i,1) = pos(sampleXId(i,1),1) + randnWrapper(1,1) * STDDEV_POS;    
+% end
+
+retQuat=quat(sampledXId,:);
+retVel=vel(sampledXId,:);%+randnWrappern(n,3)*STDDEV_VEL;
+retPos=pos(sampledXId,:);%+randnWrappern(n,3)*STDDEV_POS;
+
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/get3DGaussianProb.m b/SD-VBS/benchmarks/localization/src/matlab/get3DGaussianProb.m
new file mode 100644
index 0000000..6a54530
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/get3DGaussianProb.m
@@ -0,0 +1,22 @@
+function p=get3DGaussianProb(data, mean, A)
+n_data=size(data,1);
+n_channel=size(data,2);
+
+p=zeros(n_data,1);
+diff=(data)-ones(n_data,1)*mean;
+detA = 1; %detA = det(A)
+dotA = randWrapper(size(diff,1),1); %dotA = dot(diff*A, diff, 2)
+p=sqrt(detA/((2*pi)^n_channel))*exp(-0.5*dotA);
+
+%% KVS If the above doesnt work, try uncommenting these lines below
+
+%%temp = (det(A)/((2*pi)^n_channel));
+%temp = (1.0/((2*pi)^n_channel));
+%temp1 = dot(diff*A,diff,2);
+%%temp1 = rand(1000,1); 
+%temp2 = exp(-0.5*temp1);
+%p = sqrt(temp) * exp(temp2);
+%
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/getGroundData.m b/SD-VBS/benchmarks/localization/src/matlab/getGroundData.m
new file mode 100644
index 0000000..7cf5f9c
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/getGroundData.m
@@ -0,0 +1,5 @@
+function retData=getGroundData(data, tStamp)
+idx=find(data(:,1)==tStamp);
+retData=data(idx,:);
+
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/mcl.m b/SD-VBS/benchmarks/localization/src/matlab/mcl.m
new file mode 100644
index 0000000..8ab8aa6
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/mcl.m
@@ -0,0 +1,9 @@
+function [retX, retW]=mcl(x,sData, invCov)
+%instead of using importance resampling, I assumed 3D gaussian for each
+%particle
+%retX=x+randn(nr,nc)*(invCov^-1); %add noise
+retX=x;
+retW=get3DGaussianProb(retX, sData, invCov);
+retW=retW/sum(retW);
+
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/mclWhole.m b/SD-VBS/benchmarks/localization/src/matlab/mclWhole.m
new file mode 100644
index 0000000..4e78b8f
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/mclWhole.m
@@ -0,0 +1,18 @@
+function retW=mclWhole(quat, Ovel, STDDEV_GPSVel, accl, STDDEV_ACCL)
+n=size(quat,1);
+OvelNorm=norm(Ovel);
+if (OvelNorm>0.5)
+    Ovel=Ovel/norm(Ovel);
+    %trick
+    %quat=addEulNoise(quat, STDDEV_GPSVel); 
+    orgWorld=quatRot([1 0 0],quatConj(quat));
+    p1=get3DGaussianProb(orgWorld, Ovel, eye(3)./STDDEV_GPSVel);
+else
+    p1=zeros(n,1);
+end
+
+gravity=quatRot(ones(n,1)*[0 0 -9.8], quat);
+p2=get3DGaussianProb(gravity, accl, eye(3)./(STDDEV_ACCL));
+retW=p1+p2;
+retW=retW/sum(retW);
+            
\ No newline at end of file
diff --git a/SD-VBS/benchmarks/localization/src/matlab/quat2eul.m b/SD-VBS/benchmarks/localization/src/matlab/quat2eul.m
new file mode 100644
index 0000000..a6b48ee
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/quat2eul.m
@@ -0,0 +1,6 @@
+function retEul=quat2eul(quat)
+retEul=[atan2(2*(quat(:,3).*quat(:,4)+quat(:,1).*quat(:,2))...
+               ,(quat(:,1).^2 -quat(:,2).^2 -quat(:,3).^2 +quat(:,4).^2)) ...
+        asin(-2*(quat(:,2).*quat(:,4)-quat(:,1).*quat(:,3))) ...
+        atan2(2*(quat(:,2).*quat(:,3)+quat(:,1).*quat(:,4))...
+               ,(quat(:,1).^2 +quat(:,2).^2 -quat(:,3).^2 -quat(:,4).^2))];
diff --git a/SD-VBS/benchmarks/localization/src/matlab/quatConj.m b/SD-VBS/benchmarks/localization/src/matlab/quatConj.m
new file mode 100644
index 0000000..ff494b4
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/quatConj.m
@@ -0,0 +1,5 @@
+function retQuat=quatConj(a)
+rows = size(a,1);
+retQuat = zeros(rows, 4);
+retQuat=[a(:,1), -a(:,2), -a(:,3), -a(:,4)];
+         
diff --git a/SD-VBS/benchmarks/localization/src/matlab/quatMul.m b/SD-VBS/benchmarks/localization/src/matlab/quatMul.m
new file mode 100644
index 0000000..b397554
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/quatMul.m
@@ -0,0 +1,18 @@
+function retQuat=quatMul(a, b)
+
+rowsa = size(a,1);
+colsa = size(a,2);
+
+rowsb = size(b,1);
+colsb = size(b,2);
+
+retQuat=[a(:,1).*b(:,1) - a(:,2).*b(:,2) - a(:,3).*b(:,3) - a(:,4).*b(:,4) ...
+    a(:,1).*b(:,2) + a(:,2).*b(:,1) + a(:,3).*b(:,4) - a(:,4).*b(:,3) ...
+    a(:,1).*b(:,3) - a(:,2).*b(:,4) + a(:,3).*b(:,1) + a(:,4).*b(:,2) ...
+    a(:,1).*b(:,4) + a(:,2).*b(:,3) - a(:,3).*b(:,2) + a(:,4).*b(:,1)];
+
+% disp('retQuat');
+% disp(retQuat);
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/quatRot.m b/SD-VBS/benchmarks/localization/src/matlab/quatRot.m
new file mode 100644
index 0000000..3688172
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/quatRot.m
@@ -0,0 +1,24 @@
+function ret=quatRot(vec, rQuat)
+nr=size(vec,1);
+tv = zeros(nr,1);
+vQuat=[tv, vec];
+temp = quatMul(rQuat, vQuat);
+temp1 = quatConj(rQuat);
+retVec = quatMul(temp, temp1);
+%retVec=quatMul(quatMul(rQuat, vQuat),quatConj(rQuat));
+%ret=retVec(:,2:4);
+rows = size(retVec, 1);
+ret = zeros(rows,3);
+
+for i=1:rows
+    k =1;
+    for j=2:4
+        ret(i,k) = retVec(i,j);
+        k = k+1;
+    end
+end
+%size(ret)
+
+
+
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/readLoc.m b/SD-VBS/benchmarks/localization/src/matlab/readLoc.m
new file mode 100644
index 0000000..fc679d4
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/readLoc.m
@@ -0,0 +1,53 @@
+function out = readLoc
+out = [...
+10.512346 3.466955 9.006616 ;...
+13.242645 4.280358 14.675757 ;...
+12.418589 6.286052 22.721924 ;...
+13.598760 5.229711 19.622804 ;...
+13.568058 5.229711 19.622804 ;...
+13.537888 5.229711 19.622804 ;...
+13.508315 5.229711 19.622804 ;...
+13.479378 5.229711 19.622804 ;...
+13.450420 5.229711 19.622804 ;...
+13.345976 7.607621 29.644342 ;...
+13.500197 7.803792 32.248338 ;...
+13.354279 10.248983 42.939018 ;...
+13.500197 10.442337 45.593042 ;...
+13.354279 12.925516 56.404386 ;...
+13.700372 10.538259 47.007521 ;...
+13.669945 10.538259 47.007521 ;...
+13.640058 10.538259 47.007521 ;...
+13.608179 10.538259 47.007521 ;...
+13.576901 10.538259 47.007521 ;...
+13.545771 10.538259 47.007521 ;...
+13.731515 12.682360 55.887526 ;...
+1.016192 12.058634 55.442021 ;...
+6.263918 15.094210 64.436498 ;...
+6.263918 18.208480 70.198939 ;...
+6.263918 20.848498 78.618094 ;...
+6.263918 23.887747 84.333007 ;...
+6.263918 22.065907 78.853015 ;...
+6.237774 22.065907 78.853015 ;...
+6.211166 22.065907 78.853015 ;...
+6.183471 22.065907 78.853015 ;...
+6.155114 22.065907 78.853015 ;...
+6.126730 22.065907 78.853015 ;...
+6.154098 26.480108 89.543387 ;...
+6.168298 28.571946 93.679254 ;...
+6.157243 32.868572 105.963003 ;...
+6.155032 35.245287 110.401650 ;...
+6.155032 38.531472 119.557291 ;...
+6.155032 36.849296 111.296948 ;...
+6.128369 36.849296 111.296948 ;...
+6.101609 36.849296 111.296948 ;...
+6.073750 36.849296 111.296948 ;...
+6.046859 36.849296 111.296948 ;...
+6.019815 36.849296 111.296948 ;...
+6.046273 40.863016 123.894104 ;...
+6.060599 43.054591 127.680881 ;...
+6.049203 47.179478 140.858302 ;...
+6.046924 49.530293 145.484328 ;...
+6.046924 52.526113 153.189673 ;...
+6.046924 51.113294 146.241709 ;...
+6.021072 51.113294 146.241709 ...
+];
\ No newline at end of file
diff --git a/SD-VBS/benchmarks/localization/src/matlab/readMatrix.m b/SD-VBS/benchmarks/localization/src/matlab/readMatrix.m
new file mode 100644
index 0000000..fe684c5
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/readMatrix.m
@@ -0,0 +1,28 @@
+function readMatrix(srcImage, outName)
+
+write = fopen([outName '.m'], 'w');
+
+count = fwrite(write, 'function out = ');
+count = fwrite(write, outName);
+fprintf(write, '\n');
+count = fwrite(write, 'out = [...');
+fprintf(write, '\n');    
+
+height = size(srcImage,1);
+width = size(srcImage,2);
+
+for nI=1:height
+    for nJ=1:width
+        fprintf(write, '%f ', srcImage(nI,nJ));
+    end
+    if(nI < height)
+        fprintf(write, ';...\n');
+    end
+end
+
+fprintf(write, '...\n');
+count = fwrite(write, '];');
+
+fclose(write);
+
+end
diff --git a/SD-VBS/benchmarks/localization/src/matlab/readSensorData.m b/SD-VBS/benchmarks/localization/src/matlab/readSensorData.m
new file mode 100644
index 0000000..e84a6db
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/readSensorData.m
@@ -0,0 +1,46 @@
+function [retTStamp, retType, retData, retEOF, index]=readSensorData(index1, fid)
+
+index = index1+1;
+rows = size(fid, 1);
+retTStamp = 0;
+retType = 0;
+retData = zeros(1,8);
+
+if(index > rows)
+    retEOF = 1;
+else
+%     for i=index:rows
+%         index = i;
+%         if(fid(i,2) == 4)
+%             break;
+%         end
+%     end
+    if(index == rows)
+        retEOF = 1;
+    else
+        retEOF = 0;
+    end
+
+    k = index;
+    retTStamp=fid(k,1);
+    retType=fid(k,2);
+    if(fid(k, 2) == 1 || fid(k, 2) == 2 || fid(k, 2) == 3)
+        index = k;
+        for i=1:3
+            retData(1,i)=fid(k,i+2);
+%            fprintf(1,'retData,i -> %f\t%d\n', retData(1,i), i);
+        end
+    end
+    if(fid(k, 2) == 4)
+        index = k;
+        for i=1:3
+            retData(1,i)=fid(k,i+2);
+%            fprintf(1,'retData,i -> %f\t%d\n', retData(1,i), i);
+        end
+        for i=4:8
+            retData(1,i) = fid(k+1,i-3);
+%            fprintf(1,'retData,i -> %f\t%d\n', retData(1,i), i);
+        end
+        index = index + 1;        
+    end    
+end
diff --git a/SD-VBS/benchmarks/localization/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/localization/src/matlab/script_run_profile.m
new file mode 100644
index 0000000..44ce3aa
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/script_run_profile.m
@@ -0,0 +1,209 @@
+function script_run_profile(dataDir, resultDir, type, common, toolDir)
+
+path(path, common);
+file = fopen([dataDir, '/1.txt'], 'r');
+full = fscanf(file,'%f');
+elapsed = zeros(1,2);
+
+rows = full(2);
+cols = full(1);
+fid = zeros(rows, cols);
+
+k = 3;
+for i=1:rows
+    for j =1:cols
+        fid(i,j) = full(k);
+        k = k+1;
+    end
+end
+
+fclose(file);
+
+n=1000;
+
+gyroTimeInterval=0.01;
+acclTimeInterval=0.01;
+
+STDDEV_GPSVel=0.5;
+
+STDDEV_ODOVel=0.1;
+STDDEV_ACCL=1;
+M_STDDEV_GYRO=0.1;
+M_STDDEV_POS=0.1;
+M_STDDEV_VEL=0.02;
+
+if(strcmp(type,'test'))
+        n = 3;
+        gyroTimeInterval = 0.1;
+        acclTimeInterval = 0.1;
+        M_STDDEV_VEL = 0.2;
+    
+elseif(strcmp(type, 'sim_fast'))
+        n = 3;
+elseif(strcmp(type, 'sim'))
+        n = 10;
+elseif(strcmp(type, 'sqcif'))
+        n = 800;
+elseif(strcmp(type, 'qcif'))
+        n = 500;
+elseif(strcmp(type, 'vga'))
+        n = 2000;
+elseif(strcmp(type, 'wuxga'))
+        n = 3000;
+end
+
+fprintf(1,'Input size\t\t- (%dx%dx%d)\n', rows, cols,n);
+pos=zeros(n,3);
+
+vel=zeros(n,3) + randWrapper(n,3)*STDDEV_ODOVel;
+pi = 3.1416;
+
+eul1 = eul2quat([zeros(n,2), randWrapper(n,1)*2*pi]);
+eul2 = eul2quat([pi, 0, 0]);
+quat=quatMul(eul1, eul2);
+
+i=0;
+index = 0;
+resultMat = zeros(3,rows);
+
+while 1
+    i=i+1;
+    [tStamp, sType, sData, isEOF, index] = readSensorData(index, fid);
+
+    start = photonStartTiming;
+
+    if(sType==2)
+
+
+        %Motion model
+        gyro = sData(1, 1:3);
+        randnWrapper_mat = randnWrapper(n,3);    % KVS: We do not have function implementation for randnWrapper()
+        gyro=ones(n,1)*gyro+randnWrapper_mat*M_STDDEV_GYRO;
+
+        abc = gyro.^2;
+        abcd = sumCol(abc);
+        norm_gyro = sqrt(abcd);
+%        norm_gyro=sqrt(sum(gyro.^2,2));
+        angleAlpha=norm_gyro*gyroTimeInterval;
+        quatDelta=[cos(angleAlpha/2), gyro./(norm_gyro*ones(1,3)+0.00000001).*(sin(angleAlpha/2)*ones(1,3))];
+        quat=quatMul(quat, quatDelta);
+
+    end
+
+    if(sType==4)
+        %Observation
+        STDDEV_GPSPos=[sData(1,7), 0, 0; 0, sData(1,8), 0; 0, 0, 15];
+        Opos=sData(1,1:3);
+
+        %Initialize
+        
+        randnWrapper_mat = randnWrapper(n,3);
+        if sum(sum(pos))==0
+            pos=ones(n,1) * Opos + randnWrapper_mat*STDDEV_GPSPos;
+        else 
+           rows = size(STDDEV_GPSPos, 1);
+           cols = size(STDDEV_GPSPos, 2);
+
+            temp_STDDEV_GPSPos = ones(rows,cols);
+            for mnrows=1:rows                                 % KVS" Photon rejects this loop becasue of too many nestings ??
+                for mncols=1:cols
+                    temp_STDDEV_GPSPos(mnrows, mncols) = power(STDDEV_GPSPos(mnrows,mncols),-1);
+                end
+            end
+           [temp, w]=mcl(pos, Opos , temp_STDDEV_GPSPos);
+           [quat, vel, pos]=generateSample(w, quat, vel, pos, M_STDDEV_VEL, M_STDDEV_POS);
+       end
+
+       %compare direction
+       Ovel=sData(1,4:6);
+
+%        KVS: We do not have function for norm() yet! So replacing this operating with OvelNorm
+  
+%        OvelNorm=norm(Ovel);                               
+       OvelNorm= 2.0;  %1.1169e+09;
+       
+       if (OvelNorm>0.5)
+       
+           % KVS: Similar here: No impln of norm(), so replacing
+           % norm(Ovel) with OvelNorm value
+           
+           Ovel=Ovel/OvelNorm;
+           %trick
+           %quat=addEulNoise(quat, STDDEV_GPSVel);
+           qConj = quatConj(quat);
+            orgWorld=quatRot([1, 0, 0],qConj);
+            eye3 = [1,0,0;0,1,0;0,0,1];
+            [temp, w]=mcl(orgWorld, Ovel, eye3./STDDEV_GPSVel);
+            [quat, vel, pos]=generateSample(w, quat, vel, pos, M_STDDEV_VEL, M_STDDEV_POS);
+       end
+ 
+   end
+   
+   if(sType==1)
+
+       %Observation
+       Ovel=sData(1,1);
+       [temp, w]=mcl(sqrt(vel(:,1).^2+vel(:,2).^2+vel(:,3).^2), Ovel, 1/(STDDEV_ODOVel));
+
+       [quat vel pos]=generateSample(w, quat, vel, pos, M_STDDEV_VEL, M_STDDEV_POS);
+   end
+   
+   if(sType==3)
+       %Observation
+       accl=sData(1,1:3);
+       
+       gtemp = ones(n,1) * [0 0 -9.8];
+       
+       gravity=quatRot(gtemp, quat);
+        eye3 = [1,0,0;0,1,0;0,0,1];
+        [gravity, w]=mcl(gravity, accl, eye3./(STDDEV_ACCL));
+
+        [quat, vel, pos]=generateSample(w, quat, vel, pos, M_STDDEV_VEL, M_STDDEV_POS);
+
+        %Motion model
+        accl=ones(n,1)*accl;
+        accl=accl-gravity;
+        pos=pos+quatRot(vel,quatConj(quat))*acclTimeInterval ...
+            +1/2*quatRot(accl,quatConj(quat))*acclTimeInterval^2 ...
+            +randnWrapper(n,3)*M_STDDEV_POS;
+        vel=vel+accl*acclTimeInterval+randnWrapper(n,3)*M_STDDEV_VEL;
+
+   end
+   
+    stop = photonEndTiming;
+    
+    temp = photonReportTiming(start, stop);
+    elapsed(1) = elapsed(1) + temp(1);
+    elapsed(2) = elapsed(2) + temp(2);
+
+    % Self check
+
+    quatOut = 0;
+    posOut = 0;
+    velOut = 0;
+
+    for ij=1:(size(quat,1)*size(quat,2))
+        quatOut = quatOut + quat(ij);
+    end
+
+    for ij=1:(size(vel,1)*size(vel,2))
+        velOut = velOut + vel(ij);
+    end
+
+    for ij=1:(size(pos,1)*size(pos,2))
+        posOut = posOut + pos(ij);
+    end
+
+    resultMat(:, i) = [quatOut, velOut, posOut];
+
+    if (isEOF == 1)
+        break;
+    end
+end
+
+%% Timing
+photonPrintTiming(elapsed);
+
+%% Self checking %%
+fWriteMatrix(resultMat,dataDir);
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/selfCheck.m b/SD-VBS/benchmarks/localization/src/matlab/selfCheck.m
new file mode 100644
index 0000000..ac80ebd
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/selfCheck.m
@@ -0,0 +1,33 @@
+function ret = selfCheck(in1, in2, tol)
+
+r1 = size(in1, 1);
+c1 = size(in1, 2);
+
+r2 = size(in2, 1);
+c2 = size(in2, 2);
+
+ret = 1;
+
+if r1~=r2 
+    disp(1298);
+    ret = 0;
+end
+
+if c1 ~= c2
+        disp(1297);
+        ret = 0;
+end
+
+for i=1:r1
+    if(ret == 0)
+        break;
+    end
+    for j=1:c1
+        if( abs(in1(i,j)-in2(i,j)) > tol)
+            ret = 0;
+            break;
+        end
+    end
+end
+
+
diff --git a/SD-VBS/benchmarks/localization/src/matlab/sumCol.m b/SD-VBS/benchmarks/localization/src/matlab/sumCol.m
new file mode 100644
index 0000000..ad0114e
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/sumCol.m
@@ -0,0 +1,14 @@
+function ret = sumCol(mat)
+
+row = size(mat, 1);
+col = size(mat, 2);
+
+ret = zeros(row, 1);
+
+for i=1:row
+        temp = 0;
+        for j=1:col
+                temp = temp + mat(i, j);
+        end
+        ret(i, 1) = temp;
+end
diff --git a/SD-VBS/benchmarks/localization/src/matlab/weightedSample.m b/SD-VBS/benchmarks/localization/src/matlab/weightedSample.m
new file mode 100644
index 0000000..dc9274b
--- /dev/null
+++ b/SD-VBS/benchmarks/localization/src/matlab/weightedSample.m
@@ -0,0 +1,20 @@
+%function x_gen_id=weightedSample(w)
+function bin=weightedSample(w)
+n=size(w,1);
+seed=randWrapper(n,1);
+bin = zeros(n,1);
+%x_gen_id=zeros(n,1);
+ for i=1:n
+     for j=1:n
+         if(seed(j,1) > 0)
+             bin(j,1) = bin(j,1) + 1;
+%             x_gen_id(j,1) = x_gen_id(j,1) + bin(j,1);
+         end
+     end
+%     bin = (seed>0);
+%     x_gen_id=x_gen_id+bin;
+     seed=seed-w(i,1);
+ end
+% x_gen_id = bin;
+%x_gen=x(:,x_gen_id);
+
diff --git a/SD-VBS/benchmarks/mser/.mser.mex.c.swp b/SD-VBS/benchmarks/mser/.mser.mex.c.swp
new file mode 100755
index 0000000..4f3a21c
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/.mser.mex.c.swp
diff --git a/SD-VBS/benchmarks/mser/Makefile b/SD-VBS/benchmarks/mser/Makefile
new file mode 100644
index 0000000..60cc0ec
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/Makefile
@@ -0,0 +1,3 @@
+include ../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/mser/data/Makefile b/SD-VBS/benchmarks/mser/data/Makefile
new file mode 100644
index 0000000..ba33d35
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/Makefile
@@ -0,0 +1,3 @@
+include ../../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/mser/data/cif/1.bmp b/SD-VBS/benchmarks/mser/data/cif/1.bmp
new file mode 100644
index 0000000..df56ca3
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/cif/1.bmp
diff --git a/SD-VBS/benchmarks/mser/data/cif/Makefile b/SD-VBS/benchmarks/mser/data/cif/Makefile
new file mode 100644
index 0000000..41c7f38
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/cif/Makefile
@@ -0,0 +1,6 @@
+INPUT=cif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=mser
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/mser/data/cif/VBS_Ver1 b/SD-VBS/benchmarks/mser/data/cif/VBS_Ver1
new file mode 100755
index 0000000..bafb9c7
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/cif/VBS_Ver1
diff --git a/SD-VBS/benchmarks/mser/data/cif/expected.m b/SD-VBS/benchmarks/mser/data/cif/expected.m
new file mode 100644
index 0000000..b4123c3
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/cif/expected.m
@@ -0,0 +1,162 @@
+91080   
+40916   
+90318   
+48277   
+57285   
+66702   
+66453   
+15757   
+56228   
+9401    
+72213   
+62502   
+50676   
+8016    
+76446   
+4080    
+26989   
+2894    
+15233   
+25177   
+46411   
+77708   
+79330   
+79286   
+7639    
+39100   
+20919   
+24125   
+69034   
+87683   
+33330   
+9587    
+14591   
+37790   
+57107   
+2905    
+72581   
+30138   
+66349   
+69782   
+53208   
+63252   
+8011    
+20400   
+47661   
+59179   
+71075   
+3544    
+75352   
+5143    
+42527   
+49924   
+9933    
+13880   
+38559   
+45184   
+48697   
+51275   
+57095   
+27545   
+41718   
+46519   
+25666   
+31481   
+56792   
+59176   
+29879   
+42197   
+62643   
+58210   
+20334   
+5623    
+43569   
+46210   
+50474   
+62104   
+65808   
+46945   
+52682   
+63195   
+77194   
+50534   
+60544   
+41770   
+48717   
+53246   
+57723   
+3829    
+20457   
+28461   
+32341   
+6413    
+30286   
+41193   
+50243   
+55458   
+56851   
+60038   
+35141   
+59004   
+63503   
+34763   
+48953   
+55092   
+4534    
+70791   
+20249   
+28134   
+33971   
+53439   
+55882   
+30562   
+33993   
+34523   
+67709   
+60469   
+8591    
+20489   
+72123   
+20237   
+62971   
+26046   
+27337   
+27638   
+29497   
+46390   
+18004   
+41108   
+47659   
+72386   
+31584   
+52173   
+58091   
+46624   
+68233   
+25267   
+29768   
+52802   
+63228   
+39529   
+37092   
+48469   
+41074   
+44231   
+18653   
+40524   
+26529   
+32423   
+27131   
+37373   
+39650   
+65233   
+72920   
+12277   
+33656   
+33151   
+40026   
+48408   
+33352   
+91265   
+32307   
+33875   
diff --git a/SD-VBS/benchmarks/mser/data/cif/mser b/SD-VBS/benchmarks/mser/data/cif/mser
new file mode 100755
index 0000000..e2e5016
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/cif/mser
diff --git a/SD-VBS/benchmarks/mser/data/fullhd/1.bmp b/SD-VBS/benchmarks/mser/data/fullhd/1.bmp
new file mode 100644
index 0000000..c09aaf0
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/fullhd/1.bmp
diff --git a/SD-VBS/benchmarks/mser/data/fullhd/Makefile b/SD-VBS/benchmarks/mser/data/fullhd/Makefile
new file mode 100644
index 0000000..5cce221
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/fullhd/Makefile
@@ -0,0 +1,6 @@
+INPUT=fullhd
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=mser
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/mser/data/fullhd/mser b/SD-VBS/benchmarks/mser/data/fullhd/mser
new file mode 100755
index 0000000..ab94dc8
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/fullhd/mser
diff --git a/SD-VBS/benchmarks/mser/data/qcif/1.bmp b/SD-VBS/benchmarks/mser/data/qcif/1.bmp
new file mode 100644
index 0000000..f5a4408
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/qcif/1.bmp
diff --git a/SD-VBS/benchmarks/mser/data/qcif/Makefile b/SD-VBS/benchmarks/mser/data/qcif/Makefile
new file mode 100644
index 0000000..0c1d924
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/qcif/Makefile
@@ -0,0 +1,6 @@
+INPUT=qcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=mser
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/mser/data/qcif/VBS_Ver1 b/SD-VBS/benchmarks/mser/data/qcif/VBS_Ver1
new file mode 100755
index 0000000..a973e58
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/qcif/VBS_Ver1
diff --git a/SD-VBS/benchmarks/mser/data/qcif/expected.m b/SD-VBS/benchmarks/mser/data/qcif/expected.m
new file mode 100644
index 0000000..41fc7d7
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/qcif/expected.m
@@ -0,0 +1,68 @@
+22308   
+10162   
+14251   
+9500    
+18683   
+5669    
+1501    
+2813    
+5180    
+6119    
+3731    
+3939    
+22065   
+2417    
+5048    
+17994   
+14159   
+15203   
+17195   
+18926   
+13616   
+2192    
+2       
+6900    
+9794    
+11366   
+14679   
+5344    
+17471   
+11778   
+16661   
+10323   
+12856   
+13141   
+7022    
+12740   
+11984   
+14560   
+12982   
+19042   
+13916   
+1250    
+7680    
+159     
+5477    
+13909   
+15632   
+7620    
+6936    
+14660   
+2021    
+12466   
+16436   
+6556    
+12499   
+9457    
+6559    
+13998   
+17616   
+9992    
+12224   
+14654   
+9572    
+6970    
+8661    
+18900   
+3364    
+8379    
diff --git a/SD-VBS/benchmarks/mser/data/qcif/mser b/SD-VBS/benchmarks/mser/data/qcif/mser
new file mode 100755
index 0000000..3a8d82b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/qcif/mser
diff --git a/SD-VBS/benchmarks/mser/data/sim/1.bmp b/SD-VBS/benchmarks/mser/data/sim/1.bmp
new file mode 100644
index 0000000..953fe98
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sim/1.bmp
diff --git a/SD-VBS/benchmarks/mser/data/sim/Makefile b/SD-VBS/benchmarks/mser/data/sim/Makefile
new file mode 100644
index 0000000..fc94f6e
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sim/Makefile
@@ -0,0 +1,6 @@
+INPUT=sim
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=mser
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/mser/data/sim/expected.m b/SD-VBS/benchmarks/mser/data/sim/expected.m
new file mode 100644
index 0000000..c52e720
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sim/expected.m
@@ -0,0 +1,16 @@
+3611    
+5615    
+3876    
+2441    
+5556    
+127     
+1109    
+71      
+8       
+16      
+3567    
+817     
+3169    
+2121    
+4036    
+3985    
diff --git a/SD-VBS/benchmarks/mser/data/sim/mser b/SD-VBS/benchmarks/mser/data/sim/mser
new file mode 100755
index 0000000..3a8d82b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sim/mser
diff --git a/SD-VBS/benchmarks/mser/data/sim_fast/1.bmp b/SD-VBS/benchmarks/mser/data/sim_fast/1.bmp
new file mode 100644
index 0000000..5ec0de1
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sim_fast/1.bmp
diff --git a/SD-VBS/benchmarks/mser/data/sim_fast/Makefile b/SD-VBS/benchmarks/mser/data/sim_fast/Makefile
new file mode 100644
index 0000000..f5845eb
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sim_fast/Makefile
@@ -0,0 +1,8 @@
+
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=mser
+INPUT=sim_fast
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/mser/data/sim_fast/expected.m b/SD-VBS/benchmarks/mser/data/sim_fast/expected.m
new file mode 100644
index 0000000..5ba3c55
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sim_fast/expected.m
@@ -0,0 +1,7 @@
+1214    
+353     
+1146    
+29      
+187     
+829     
+976     
diff --git a/SD-VBS/benchmarks/mser/data/sim_fast/mser b/SD-VBS/benchmarks/mser/data/sim_fast/mser
new file mode 100755
index 0000000..3a8d82b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sim_fast/mser
diff --git a/SD-VBS/benchmarks/mser/data/sqcif/1.bmp b/SD-VBS/benchmarks/mser/data/sqcif/1.bmp
new file mode 100644
index 0000000..9122269
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sqcif/1.bmp
diff --git a/SD-VBS/benchmarks/mser/data/sqcif/Makefile b/SD-VBS/benchmarks/mser/data/sqcif/Makefile
new file mode 100644
index 0000000..42808ce
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sqcif/Makefile
@@ -0,0 +1,6 @@
+INPUT=sqcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=mser
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/mser/data/sqcif/expected.m b/SD-VBS/benchmarks/mser/data/sqcif/expected.m
new file mode 100644
index 0000000..a3ccbad
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sqcif/expected.m
@@ -0,0 +1,27 @@
+3549    
+5615    
+3941    
+5626    
+5113    
+1079    
+3840    
+4838    
+4050    
+7       
+1741    
+2778    
+2060    
+3911    
+13      
+1923    
+3918    
+3463    
+480     
+1488    
+344     
+33      
+2158    
+3398    
+1694    
+2420    
+4026    
diff --git a/SD-VBS/benchmarks/mser/data/sqcif/mser b/SD-VBS/benchmarks/mser/data/sqcif/mser
new file mode 100755
index 0000000..3a8d82b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/sqcif/mser
diff --git a/SD-VBS/benchmarks/mser/data/test/1.bmp b/SD-VBS/benchmarks/mser/data/test/1.bmp
new file mode 100644
index 0000000..ba8fb8b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/test/1.bmp
diff --git a/SD-VBS/benchmarks/mser/data/test/Makefile b/SD-VBS/benchmarks/mser/data/test/Makefile
new file mode 100644
index 0000000..8a1c79b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/test/Makefile
@@ -0,0 +1,7 @@
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=mser
+INPUT=test
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/mser/data/test/expected.m b/SD-VBS/benchmarks/mser/data/test/expected.m
new file mode 100644
index 0000000..30d764c
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/test/expected.m
@@ -0,0 +1 @@
+171     
diff --git a/SD-VBS/benchmarks/mser/data/test/mser b/SD-VBS/benchmarks/mser/data/test/mser
new file mode 100755
index 0000000..3a8d82b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/test/mser
diff --git a/SD-VBS/benchmarks/mser/data/vga/1.bmp b/SD-VBS/benchmarks/mser/data/vga/1.bmp
new file mode 100644
index 0000000..bbb3e60
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/vga/1.bmp
diff --git a/SD-VBS/benchmarks/mser/data/vga/Makefile b/SD-VBS/benchmarks/mser/data/vga/Makefile
new file mode 100644
index 0000000..1b0032a
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/vga/Makefile
@@ -0,0 +1,6 @@
+INPUT=vga
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=mser
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/mser/data/vga/expected.m b/SD-VBS/benchmarks/mser/data/vga/expected.m
new file mode 100644
index 0000000..23ca6be
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/vga/expected.m
@@ -0,0 +1,297 @@
+150188  
+139161  
+226889  
+295683  
+188158  
+218738  
+24760   
+122860  
+234561  
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+304797  
+90329   
+57239   
+104324  
+58669   
+114859  
+185568  
diff --git a/SD-VBS/benchmarks/mser/data/vga/mser b/SD-VBS/benchmarks/mser/data/vga/mser
new file mode 100755
index 0000000..3a8d82b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/data/vga/mser
diff --git a/SD-VBS/benchmarks/mser/src/c/mser.c b/SD-VBS/benchmarks/mser/src/c/mser.c
new file mode 100644
index 0000000..d886d7a
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/c/mser.c
@@ -0,0 +1,714 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+/***
+%   MSER  Maximally Stable Extremal Regions
+%   R=MSER(I,DELTA) computes the Maximally Stable Extremal Regions
+%   (MSER) of image I with stability threshold DELTA. I is any
+%   array of class UINT8, while DELTA is a scalar of the same class.
+%   R is an index set (of class UINT32) which enumerates the
+%   representative pixels of the detected regions.
+%
+%   A region R can be recovered from a representative pixel X as the
+%   connected component of the level set {Y:I(Y) <= I(X)} which
+%   contains X.
+***/
+
+
+#include "mser.h"
+#include <string.h>
+
+/* advance N-dimensional subscript */
+void
+adv(iArray *dims, int ndims, iArray *subs_pt)
+{
+    int d = 0 ;
+    while(d < ndims) 
+    {
+        sref(subs_pt,d) = sref(subs_pt,d) + 1;
+        if( sref(subs_pt,d)  < sref(dims,d) ) 
+            return ;
+        sref(subs_pt,d++) = 0 ;
+    }
+}
+
+/** driver **/
+I2D* mser(I2D* I, int in_delta,
+          iArray* subs_pt, iArray* nsubs_pt, iArray* strides_pt, iArray* visited_pt, iArray* dims, 
+          uiArray* joins_pt,
+          region_t* regions_pt, 
+          pair_t* pairs_pt,
+          node_t* forest_pt,
+          ulliArray* acc_pt, ulliArray* ell_pt,
+          I2D* out)
+{
+   idx_t i, rindex=0;
+   int k;
+   int nout = 1;
+   
+   int OUT_REGIONS=0;
+   int OUT_ELL = 1;
+   int OUT_PARENTS = 2;
+   int OUT_AREA = 3;
+   int BUCKETS = 256;
+   
+   //I2D* out;
+
+   int IN_I = 0;
+   int IN_DELTA = 1;   
+
+    /* configuration */
+    int verbose = 1 ;      /* be verbose                              */
+    int small_cleanup= 1 ; /* remove very small regions               */
+    int big_cleanup  = 1 ; /* remove very big regions                 */
+    int bad_cleanup  = 0 ; /* remove very bad regions                 */
+    int dup_cleanup  = 1 ; /* remove duplicates                       */
+    val_t delta ;          /* stability delta                         */
+
+    /* node value denoting a void node */
+    idx_t const node_is_void = 0xffffffff ;
+
+    //iArray*   subs_pt ;       /* N-dimensional subscript                 
+    //iArray*   nsubs_pt ;      /* diff-subscript to point to neigh.       
+//    uiArray* strides_pt ;    /* strides to move in image array          
+//    uiArray* visited_pt ;    /* flag                                    
+
+    int nel ;              /* number of image elements (pixels)       */
+    int ner = 0 ;          /* number of extremal regions              */
+    int nmer = 0 ;         /* number of maximally stable              */
+    int ndims ;            /* number of dimensions                    */
+//    iArray* dims ;           /* dimensions                              
+    int njoins = 0 ;       /* number of join ops                      */
+
+    I2D* I_pt ;    /* source image                            */
+    //pair_t*   pairs_pt ;   /* scratch buffer to sort pixels           
+//    node_t*   forest_pt ;  /* the extremal regions forest             
+//    region_t* regions_pt ; /* list of extremal regions found          
+    int regions_pt_size;
+    int pairs_pt_size;
+    int forest_pt_size;
+
+    /* ellipses fitting */
+    //ulliArray* acc_pt ;        /* accumulator to integrate region moments
+    //ulliArray* ell_pt ;        /* ellipses parameters                     
+    int    gdl ;           /* number of parameters of an ellipse      */
+    //uiArray* joins_pt ;      /* sequence of joins                       
+   
+    delta = 0;
+    delta = in_delta;
+
+    /* get dimensions */
+
+    nel = I->height*I->width;            /* number of elements of src image */
+    ndims = 2;
+    //dims = malloc(sizeof(iArray) + sizeof(int)*ndims);
+    I_pt = I;
+    
+    sref(dims,0) = I->height;
+    sref(dims,1) = I->width;
+    
+    /* allocate stuff */
+    //subs_pt = malloc(sizeof(iArray) + sizeof(int)*ndims);
+    //nsubs_pt = malloc(sizeof(iArray) + sizeof(int)*ndims);
+
+    //strides_pt = malloc(sizeof(uiArray)+sizeof(unsigned int)*ndims);
+    //visited_pt = malloc(sizeof(uiArray) + sizeof(unsigned int)*nel);
+    //joins_pt = malloc(sizeof(uiArray) + sizeof(unsigned int)*nel);
+
+    //regions_pt = (region_t*)malloc(sizeof(region_t)*nel);
+    regions_pt_size = nel;
+
+    //pairs_pt = (pair_t*)malloc(sizeof(pair_t)*nel);
+    pairs_pt_size = nel;
+
+    //forest_pt = (node_t*)malloc(sizeof(node_t)*nel);
+    forest_pt_size = nel;
+
+    /* compute strides to move into the N-dimensional image array */
+    sref(strides_pt,0) = 1;
+    for(k = 1 ; k < ndims ; ++k)
+    {
+        sref(strides_pt,k) = sref(strides_pt,k-1) * sref(dims,k-1) ;
+    }
+
+    /* sort pixels in increasing order of intensity: using Bucket Sort */
+    {
+        int unsigned buckets [BUCKETS] ;
+        memset(buckets, 0, sizeof(int unsigned)*BUCKETS) ;
+
+        for(i = 0 ; i < nel ; ++i) 
+        {
+            val_t v = asubsref(I_pt,i) ;
+            ++buckets[v] ;
+        }
+        
+        for(i = 1 ; i < BUCKETS ; ++i) 
+        {
+            arrayref(buckets,i) += arrayref(buckets,i-1) ;
+        }
+        
+        for(i = nel ; i >= 1 ; )
+        {
+            val_t v = asubsref(I_pt,--i) ;
+            idx_t j = --buckets[v] ;
+            pairs_pt[j].value = v ;
+            pairs_pt[j].index = i ;
+        }
+    }
+     
+    /* initialize the forest with all void nodes */
+    for(i = 0 ; i < nel ; ++i) 
+    {
+        forest_pt[i].parent = node_is_void  ;
+    }
+  
+    /* number of ellipse free parameters */
+    gdl = ndims*(ndims+1)/2 + ndims ;
+
+    /* -----------------------------------------------------------------
+    *                                     Compute extremal regions tree
+    * -------------------------------------------------------------- */
+  
+    for(i = 0 ; i < nel ; ++i)
+    {
+        /* pop next node xi */
+        idx_t index = pairs_pt [i].index ;    
+        val_t value = pairs_pt [i].value ;
+
+        /* this will be needed later */
+        rindex = index ;
+    
+        /* push it into the tree */
+        forest_pt [index] .parent   = index ;
+        forest_pt [index] .shortcut = index ;
+        forest_pt [index] .area     = 1 ;
+#ifdef USE_RANK_UNION
+        forest_pt [index] .height   = 1 ;
+#endif
+    
+    /* convert index into a subscript sub; also initialize nsubs 
+    to (-1,-1,...,-1) */
+        {
+            idx_t temp = index ;
+            for(k = ndims-1 ; k >=0 ; --k) 
+            {
+                sref(nsubs_pt,k) = -1 ;
+                sref(subs_pt,k) = temp / sref(strides_pt,k) ;
+                temp         = temp % sref(strides_pt,k) ;
+            }
+        }
+    
+    /* process neighbors of xi */
+        while(1) 
+        {
+            int good = 1 ;
+            idx_t nindex = 0 ;
+      
+      /* compute NSUBS+SUB, the correspoinding neighbor index NINDEX
+         and check that the pixel is within image boundaries. */
+            for(k = 0 ; k < ndims && good ; ++k) 
+            {
+                int temp = sref(nsubs_pt,k) + sref(subs_pt,k) ;
+                good &= 0 <= temp && temp < sref(dims,k) ;
+                nindex += temp * sref(strides_pt,k) ;
+            }      
+      
+
+      /* keep going only if
+         1 - the neighbor is within image boundaries;
+         2 - the neighbor is indeed different from the current node
+             (this happens when nsub=(0,0,...,0));
+         3 - the nieghbor is already in the tree, meaning that
+             is a pixel older than xi.
+      */
+            if(good && nindex != index && forest_pt[nindex].parent != node_is_void ) 
+            {
+                idx_t nrindex = 0, nvisited ;
+                val_t nrvalue = 0 ;
+                
+
+#ifdef USE_RANK_UNION
+                int height  = forest_pt [ rindex] .height ;
+                int nheight = forest_pt [nrindex] .height ;
+#endif
+        
+        /* RINDEX = ROOT(INDEX) might change as we merge trees, so we
+           need to update it after each merge */
+        
+        /* find the root of the current node */
+        /* also update the shortcuts */
+                nvisited = 0 ;
+                while( forest_pt[rindex].shortcut != rindex ) 
+                {          
+                    sref(visited_pt,nvisited++) = rindex ;
+                    rindex = forest_pt[rindex].shortcut ;
+                }      
+                while( nvisited-- ) 
+                {
+                    forest_pt [ sref(visited_pt,nvisited) ] .shortcut = rindex ;
+                }
+        
+        /* find the root of the neighbor */
+                nrindex  = nindex ;
+                nvisited = 0 ;
+                while( forest_pt[nrindex].shortcut != nrindex ) 
+                {          
+                    sref(visited_pt, nvisited++) = nrindex ;
+                    nrindex = forest_pt[nrindex].shortcut ;
+                }      
+                while( nvisited-- ) 
+                {
+                    forest_pt [ sref(visited_pt,nvisited) ] .shortcut = nrindex ;
+                }
+        
+        /*
+          Now we join the two subtrees rooted at
+          
+            RINDEX = ROOT(INDEX) and NRINDEX = ROOT(NINDEX).
+          
+          Only three things can happen:
+          
+          a - ROOT(INDEX) == ROOT(NRINDEX). In this case the two trees
+              have already been joined and we do not do anything.
+          
+          b - I(ROOT(INDEX)) == I(ROOT(NRINDEX)). In this case index
+              is extending an extremal region with the same
+              value. Since ROOT(NRINDEX) will NOT be an extremal
+              region of the full image, ROOT(INDEX) can be safely
+              addedd as children of ROOT(NRINDEX) if this reduces
+              the height according to union rank.
+               
+          c - I(ROOT(INDEX)) > I(ROOT(NRINDEX)) as index is extending
+              an extremal region, but increasing its level. In this
+              case ROOT(NRINDEX) WILL be an extremal region of the
+              final image and the only possibility is to add
+              ROOT(NRINDEX) as children of ROOT(INDEX).
+        */
+
+                if( rindex != nrindex ) 
+                {
+                    /* this is a genuine join */
+          
+                    nrvalue = asubsref(I_pt,nrindex) ;
+                    if( nrvalue == value 
+#ifdef USE_RANK_UNION             
+              && height < nheight
+#endif
+                    ) 
+                    {
+                        /* ROOT(INDEX) becomes the child */
+                        forest_pt[rindex] .parent   = nrindex ;
+                        forest_pt[rindex] .shortcut = nrindex ;          
+                        forest_pt[nrindex].area    += forest_pt[rindex].area ;
+
+#ifdef USE_RANK_UNION
+                        forest_pt[nrindex].height = MAX(nheight, height+1) ;
+#endif
+
+                        sref(joins_pt,njoins++) = rindex ;
+
+                    } 
+                    else 
+                    {
+                        /* ROOT(index) becomes parent */
+                        forest_pt[nrindex] .parent   = rindex ;
+                        forest_pt[nrindex] .shortcut = rindex ;
+                        forest_pt[rindex]  .area    += forest_pt[nrindex].area ;
+
+#ifdef USE_RANK_UNION
+                        forest_pt[rindex].height = MAX(height, nheight+1) ;
+#endif
+                        if( nrvalue != value ) 
+                        {            
+                            /* nrindex is extremal region: save for later */
+                            forest_pt[nrindex].region = ner ;
+                            regions_pt [ner] .index      = nrindex ;
+                            regions_pt [ner] .parent     = ner ;
+                            regions_pt [ner] .value      = nrvalue ;
+                            regions_pt [ner] .area       = forest_pt [nrindex].area ;
+                            regions_pt [ner] .area_top   = nel ;
+                            regions_pt [ner] .area_bot   = 0 ;            
+                            ++ner ;
+                        }
+            
+                        /* annote join operation for post-processing */
+                        sref(joins_pt,njoins++) = nrindex ;
+                    }
+                }
+        
+            } /* neighbor done */
+      
+            /* move to next neighbor */      
+            k = 0 ;
+            sref(nsubs_pt,k) = sref(nsubs_pt,k) + 1;
+            while( sref(nsubs_pt, k) > 1) 
+            {
+                sref(nsubs_pt,k++) = -1 ;
+                if(k == ndims) goto done_all_neighbors ;
+                sref(nsubs_pt,k) = sref(nsubs_pt,k) + 1;
+            }
+        } /* next neighbor */
+        done_all_neighbors : ;
+    } /* next pixel */    
+    
+ 
+    /* the root of the last processed pixel must be a region */
+    forest_pt [rindex].region = ner ;
+    regions_pt [ner] .index      = rindex ;
+    regions_pt [ner] .parent     = ner ;
+    regions_pt [ner] .value      = asubsref(I_pt,rindex) ;
+    regions_pt [ner] .area       = forest_pt [rindex] .area ;
+    regions_pt [ner] .area_top   = nel ;
+    regions_pt [ner] .area_bot   = 0 ;            
+    ++ner ;
+    
+    /* -----------------------------------------------------------------
+    *                                            Compute region parents
+    * -------------------------------------------------------------- */
+    for( i = 0 ; i < ner ; ++i) 
+    {
+        idx_t index  = regions_pt [i].index ;    
+        val_t value  = regions_pt [i].value ;
+        idx_t j      = i ;
+
+        while(j == i) 
+        {
+            idx_t pindex = forest_pt [index].parent ;
+            val_t pvalue = asubsref(I_pt,pindex) ;
+
+            /* top of the tree */
+            if(index == pindex) 
+            {
+                j = forest_pt[index].region ;
+                break ;
+            }
+
+            /* if index is the root of a region, either this is still
+            i, or it is the parent region we are looking for. */
+            if(value < pvalue) 
+            {
+                j = forest_pt[index].region ;
+            }
+
+            index = pindex ;
+            value = pvalue ;
+        }
+        regions_pt[i]. parent = j ;
+    }
+  
+    /* -----------------------------------------------------------------
+    *                                 Compute areas of tops and bottoms
+    * -------------------------------------------------------------- */
+
+    /* We scan the list of regions from the bottom. Let x0 be the current
+     region and be x1 = PARENT(x0), x2 = PARENT(x1) and so on.
+     
+     Here we do two things:
+     
+     1) Look for regions x for which x0 is the BOTTOM. This requires
+        VAL(x0) <= VAL(x) - DELTA < VAL(x1).
+        We update AREA_BOT(x) for each of such x found.
+        
+     2) Look for the region y which is the TOP of x0. This requires
+          VAL(y) <= VAL(x0) + DELTA < VAL(y+1)
+          We update AREA_TOP(x0) as soon as we find such y.
+        
+    */
+
+    for( i = 0 ; i < ner ; ++i) 
+    {
+        /* fix xi as the region, then xj are the parents */
+        idx_t parent = regions_pt [i].parent ;
+        int   val0   = regions_pt [i].value ;
+        int   val1   = regions_pt [parent].value ;
+        int   val    = val0 ;
+        idx_t j = i ;
+
+        while(1) 
+        {
+            int valp = regions_pt [parent].value ;
+
+            /* i is the bottom of j */
+            if(val0 <= val - delta && val - delta < val1) 
+            {
+                regions_pt [j].area_bot  =
+                MAX(regions_pt [j].area_bot, regions_pt [i].area) ;
+            }
+      
+            /* j is the top of i */
+            if(val <= val0 + delta && val0 + delta < valp) 
+            {
+                regions_pt [i].area_top = regions_pt [j].area ;
+            }
+      
+            /* stop if going on is useless */
+            if(val1 <= val - delta && val0 + delta < val)
+                break ;
+
+            /* stop also if j is the root */
+            if(j == parent)
+                break ;
+      
+            /* next region upward */
+            j      = parent ;
+            parent = regions_pt [j].parent ;
+            val    = valp ;
+        }
+    }
+
+    /* -----------------------------------------------------------------
+    *                                                 Compute variation
+    * -------------------------------------------------------------- */
+    for(i = 0 ; i < ner ; ++i) 
+    {
+        int area     = regions_pt [i].area ;
+        int area_top = regions_pt [i].area_top ;
+        int area_bot = regions_pt [i].area_bot ;    
+        regions_pt [i].variation = (area_top - area_bot) / (area*1.0) ;
+
+        /* initialize .mastable to 1 for all nodes */
+        regions_pt [i].maxstable = 1 ;
+    }
+
+    /* -----------------------------------------------------------------
+    *                     Remove regions which are NOT maximally stable
+    * -------------------------------------------------------------- */
+    nmer = ner ;
+    for(i = 0 ; i < ner ; ++i) 
+    {
+        idx_t parent = regions_pt [i]      .parent ;
+        float var    = regions_pt [i]      .variation ;
+        float pvar   = regions_pt [parent] .variation ;
+        idx_t loser ;
+
+        /* decide which one to keep and put that in loser */
+        if(var < pvar) loser = parent ; else loser = i ;
+    
+        /* make loser NON maximally stable */
+        if(regions_pt [loser].maxstable) --nmer ;
+        regions_pt [loser].maxstable = 0 ;
+    }
+
+
+    /* -----------------------------------------------------------------
+    *                                               Remove more regions
+    * -------------------------------------------------------------- */
+
+    /* it is critical for correct duplicate detection to remove regions
+     from the bottom (smallest one first) */
+
+    if( big_cleanup || small_cleanup || bad_cleanup || dup_cleanup ) 
+    {
+        int nbig   = 0 ;
+        int nsmall = 0 ;
+        int nbad   = 0 ;
+        int ndup   = 0 ;
+
+        /* scann all extremal regions */
+        for(i = 0 ; i < ner ; ++i) 
+        {
+      
+            /* process only maximally stable extremal regions */
+            if(! regions_pt [i].maxstable) continue ;
+      
+            if( bad_cleanup   && regions_pt[i].variation >= 1.0f  ) 
+            {
+                ++nbad ;
+                goto remove_this_region ;
+            }
+
+            if( big_cleanup   && regions_pt[i].area  >  nel/2 ) 
+            {
+                ++nbig ;
+                goto remove_this_region ;
+            }
+
+            if( small_cleanup && regions_pt[i].area      <  25    ) 
+            {
+                ++nsmall ;
+                goto remove_this_region ;
+            }
+      
+            /** Remove duplicates */
+
+            if( dup_cleanup ) 
+            {
+                idx_t parent = regions_pt [i].parent ;
+                int area, parea ;
+                float change ;
+        
+                /* the search does not apply to root regions */
+                if(parent != i) 
+                {
+          
+                    /* search for the maximally stable parent region */
+                    while(! regions_pt[parent].maxstable) 
+                    {
+                        idx_t next = regions_pt[parent].parent ;
+                        if(next == parent) break ;
+                        parent = next ;
+                    }
+          
+                    /* compare with the parent region; if the current and parent
+                    regions are too similar, keep only the parent */
+          
+                    area   = regions_pt [i].area ;
+                    parea  = regions_pt [parent].area ;
+                    change = (parea - area)/(area*1.0) ;
+
+                    if(change < 0.5)  
+                    {
+                        ++ndup ;
+                        goto remove_this_region ;
+                    }
+
+                } /* drop duplicates */ 
+            }
+      
+            continue ;
+            remove_this_region :
+            regions_pt[i].maxstable = 0 ;
+            --nmer ;
+                  
+        } /* next region to cleanup */
+
+        if(0) 
+        {
+            printf("  Bad regions:        %d\n", nbad   ) ;
+            printf("  Small regions:      %d\n", nsmall ) ;
+            printf("  Big regions:        %d\n", nbig   ) ;
+            printf("  Duplicated regions: %d\n", ndup   ) ;
+        }
+    }
+
+/*    printf("Cleaned-up regions: %d (%.1f%%)\n", 
+                       nmer, 100.0 * (double) nmer / ner) ;
+*/
+    /* -----------------------------------------------------------------
+    *                                                      Fit ellipses
+    * -------------------------------------------------------------- */
+    //ell_pt = 0 ;
+    //memset(ell_pt, sizeof(ulliArray) + sizeof(acc_t)*gdl*nmer, 0) ; 
+    if (nout >= 1) 
+    {
+        int midx = 1 ;
+        int d, index, j ;
+    
+        /* enumerate maxstable regions */
+        for(i = 0 ; i < ner ; ++i) 
+        {      
+            if(! regions_pt [i].maxstable) continue ;
+            regions_pt [i].maxstable = midx++ ;
+        }
+    
+        /* allocate space */
+        //acc_pt = malloc(sizeof(ulliArray) + sizeof(acc_t)*nel) ;
+        //printf("nmer = %d\n", nmer);
+        //ell_pt = malloc(sizeof(ulliArray) + sizeof(acc_t)*gdl*nmer) ; 
+   
+        /* clear accumulators */
+        for(d=0; d<(gdl*nmer); d++)
+            sref(ell_pt,d) = 0;
+    
+        /* for each gdl */
+        for(d = 0 ; d < gdl ; ++d) 
+        {
+            /* initalize parameter */
+            int counter_i;
+            for(counter_i=0; counter_i<ndims; counter_i++)
+                sref(subs_pt,counter_i) = 0;
+      
+            if(d < ndims) 
+            {
+                for(index = 0 ; index < nel ; ++ index) 
+                {
+                    sref(acc_pt,index) = sref(subs_pt,d) ;
+                    adv(dims, ndims, subs_pt) ;
+                }
+            } 
+            else 
+            {
+                /* decode d-ndims into a (i,j) pair */
+                i = d-ndims ; 
+                j = 0 ;
+                while(i > j) 
+                {
+                    i -= j + 1 ;
+                    j ++ ;
+                }
+
+                /* add x_i * x_j */
+                for(index = 0 ; index < nel ; ++ index)
+                {
+                    sref(acc_pt,index) = sref(subs_pt,i) * sref(subs_pt,j) ;
+                    adv(dims, ndims, subs_pt) ;
+                }
+            }
+
+            /* integrate parameter */
+            for(i = 0 ; i < njoins ; ++i) 
+            {      
+                idx_t index  = sref(joins_pt,i);
+                idx_t parent = forest_pt [ index ].parent ;
+                sref(acc_pt,parent) += sref(acc_pt,index) ;
+            }
+    
+            /* save back to ellpises */
+            for(i = 0 ; i < ner ; ++i) 
+            {
+                idx_t region = regions_pt [i].maxstable ;
+
+                /* skip if not extremal region */
+                if(region-- == 0) continue ;
+                sref(ell_pt,d + gdl*region) = sref(acc_pt, regions_pt[i].index) ;
+            }
+
+            /* next gdl */
+        }
+        //free(acc_pt) ;
+        //free(ell_pt) ;
+    }
+  
+    /* -----------------------------------------------------------------
+    *                                                Save back and exit
+    * -------------------------------------------------------------- */
+
+    /*
+    * Save extremal regions
+    */
+    {
+        int dims[2], j=0;
+        I2D* pt ;
+        dims[0] = nmer ;
+        //out = iMallocHandle(1, nmer);
+        out->height = 1;
+        out->width = nmer;
+        pt = out;
+        for (i = 0 ; i < ner ; ++i) 
+        {
+            if( regions_pt[i].maxstable ) 
+            {
+                /* adjust for MATLAB index compatibility */
+//                *pt++ = regions_pt[i].index + 1 ;
+                asubsref(pt,j++) = regions_pt[i].index + 1 ;
+            }
+        }
+    }
+
+    /* free stuff */
+    //free(dims);
+    //free( forest_pt  ) ;
+    //free( pairs_pt   ) ;
+    //free( regions_pt ) ;
+    //free( visited_pt ) ;
+    //free( strides_pt ) ;
+    //free( nsubs_pt   ) ;
+    //free( subs_pt    ) ;
+    //free( joins_pt    ) ;
+
+    return out;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/mser/src/c/mser.h b/SD-VBS/benchmarks/mser/src/c/mser.h
new file mode 100644
index 0000000..8876311
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/c/mser.h
@@ -0,0 +1,83 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#ifndef _MSER_
+#define _MSER_
+
+#define sref(a,i) a->data[i]
+
+#include "sdvbs_common.h"
+#define NMER_MAX 756
+
+typedef int val_t;
+
+typedef struct
+{
+    int width;
+    int data[];
+}iArray;
+
+typedef struct
+{
+    int width;
+    unsigned int data[];
+}uiArray;
+
+typedef struct
+{
+    int width;
+    long long int unsigned data[];
+}ulliArray;
+
+#define MIN(a,b) (a<b)?a:b
+#define MAX(a,b) (a>b)?a:b
+
+typedef int  unsigned idx_t ;
+typedef long long int unsigned acc_t ;
+
+/* pairs are used to sort the pixels */
+typedef struct 
+{
+  val_t value ; 
+  idx_t  index ;
+} pair_t ;
+
+/* forest node */
+typedef struct
+{
+  idx_t parent ;   /**< parent pixel         */
+  idx_t shortcut ; /**< shortcut to the root */
+  idx_t region ;   /**< index of the region  */
+  int   area ;     /**< area of the region   */
+#ifdef USE_RANK_UNION
+  int   height ;    /**< node height         */
+#endif
+} node_t ;
+
+/* extremal regions */
+typedef struct
+{
+  idx_t parent ;     /**< parent region                           */
+  idx_t index ;      /**< index of root pixel                     */
+  val_t value ;      /**< value of root pixel                     */
+  int   area ;       /**< area of the region                      */
+  int   area_top ;   /**< area of the region DELTA levels above   */
+  int   area_bot  ;  /**< area of the region DELTA levels below   */
+  float variation ;  /**< variation                               */
+  int   maxstable ;  /**< max stable number (=0 if not maxstable) */
+} region_t ;
+
+int script_mser();
+I2D* mser(I2D* I, int in_delta,  
+          iArray* subs_pt, iArray* nsubs_pt, iArray* strides_pt, iArray* visited_pt, iArray* dims, 
+          uiArray* joins_pt,
+          region_t* regions_pt, 
+          pair_t* pairs_pt,
+          node_t* forest_pt,
+          ulliArray* acc_pt, ulliArray* ell_pt,
+          I2D* out);
+
+#endif
+
+
diff --git a/SD-VBS/benchmarks/mser/src/c/script_mser.c b/SD-VBS/benchmarks/mser/src/c/script_mser.c
new file mode 100644
index 0000000..d4a98cd
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/c/script_mser.c
@@ -0,0 +1,120 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "mser.h"
+#include <malloc.h>
+#include "extra.h"
+#define min(a,b) (a<b)?a:b
+#define max(a,b) (a>b)?a:b
+
+int main(int argc, char* argv[])
+{
+    SET_UP
+    int which_image;
+    int i, j, k;
+    I2D *idx;
+    I2D *I;
+    I2D *It;
+    I2D *out;
+    int rows=196, cols=98;
+    int minVal = 1000;
+    int maxVal = -1000;
+    int lev = 10;
+
+    char im1[100], im2[100];
+
+    iArray *subs_pt, *nsubs_pt, *strides_pt, *visited_pt, *dims;   
+    uiArray* joins_pt;
+    ulliArray *acc_pt, *ell_pt;
+    region_t* regions_pt;
+    pair_t* pairs_pt;
+    node_t* forest_pt;
+
+    int ndims, nel, gdl, nmer;
+
+    printf("Input Image: ");
+    scanf("%s", im1);
+
+    I = readImage(im1);
+
+    rows = I->height;
+    cols = I->width;
+
+    It = readImage(im1);
+
+    k = 0;
+    for(i=0; i<cols; i++)
+    {
+        for(j=0; j<rows; j++)
+        {
+            asubsref(It,k++) = subsref(I,j,i);
+        }
+    }
+    
+    ndims = 2;
+    nel = It->height * It->width;
+    gdl = ndims * (ndims+1)/2 + ndims;
+    nmer = NMER_MAX;
+
+    dims = malloc(sizeof(iArray) + sizeof(int)*ndims);
+    /* allocate stuff */
+    subs_pt = malloc(sizeof(iArray) + sizeof(int)*ndims);
+    nsubs_pt = malloc(sizeof(iArray) + sizeof(int)*ndims);
+    strides_pt = malloc(sizeof(uiArray)+sizeof(unsigned int)*ndims);
+    visited_pt = malloc(sizeof(uiArray) + sizeof(unsigned int)*nel);
+    joins_pt = malloc(sizeof(uiArray) + sizeof(unsigned int)*nel);
+
+    regions_pt = (region_t*)malloc(sizeof(region_t)*nel);
+    pairs_pt = (pair_t*)malloc(sizeof(pair_t)*nel);
+    forest_pt = (node_t*)malloc(sizeof(node_t)*nel);
+
+    acc_pt = malloc(sizeof(ulliArray) + sizeof(acc_t)*nel) ;
+    ell_pt = malloc(sizeof(ulliArray) + sizeof(acc_t)*gdl*nmer) ; 
+
+
+    out = iMallocHandle(1, nmer);
+    printf("start\n");
+    for_each_job{
+        idx = mser(It, 2, subs_pt, nsubs_pt, strides_pt, visited_pt, dims, 
+                   joins_pt,
+                   regions_pt,
+                   pairs_pt,
+                   forest_pt,
+                   acc_pt, ell_pt,
+                   out);
+    }
+    printf("end..\n");
+    
+#ifdef CHECK   
+    /** Self checking - use expected.txt from data directory  **/
+    {
+        int tol, ret=0;
+        tol = 1;
+#ifdef GENERATE_OUTPUT
+        writeMatrix(idx, argv[1]);
+#endif
+        ret = selfCheck(idx, "expected_C.txt", tol);
+        if (ret == -1)
+            printf("Error in MSER\n");
+    }
+    /** Self checking done **/
+#endif    
+    free(dims);
+    free( forest_pt  ) ;
+    free( pairs_pt   ) ;
+    free( regions_pt ) ;
+    free( visited_pt ) ;
+    free( strides_pt ) ;
+    free( nsubs_pt   ) ;
+    free( subs_pt    ) ;
+    free( joins_pt    ) ;
+    free( acc_pt ) ;
+    free( ell_pt ) ;
+    iFreeHandle(idx);
+    iFreeHandle(I);
+    iFreeHandle(It);
+    WRITE_TO_FILE
+    return 0;
+}
+
diff --git a/SD-VBS/benchmarks/mser/src/matlab/Makefile b/SD-VBS/benchmarks/mser/src/matlab/Makefile
new file mode 100755
index 0000000..29c0982
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/Makefile
@@ -0,0 +1,123 @@
+# file:        Makefile
+# author:      Andrea Vedaldi
+# description: Build mex files
+
+# --------------------------------------------------------------------
+# 
+# --------------------------------------------------------------------
+
+# Determine on the flight the system we are running on
+Darwin_ARCH := mac
+Linux_ARCH  := glx
+ARCH := $($(shell uname)_ARCH)
+
+mac_CFLAGS       := -I. -pedantic -Wall -Wno-long-long
+mac_MEX_CFLAGS   := -g -O CFLAGS='$$CFLAGS $(mac_CFLAGS)'
+mac_MEX_SUFFIX   := mexmac
+
+glx_CFLAGS       := -I. -pedantic -Wall -Wno-long-long
+glx_MEX_CFLAGS   := -g -O CFLAGS='$$CFLAGS $(glx_CFLAGS)'
+glx_MEX_SUFFIX   := mexglx
+
+MEX_SUFFIX       := $($(ARCH)_MEX_SUFFIX)
+MEX_CFLAGS       := $($(ARCH)_MEX_CFLAGS)
+
+VER              := 0.4
+DIST             := mser-$(VER)
+BINDIST          := $(DIST)-$(ARCH)
+
+# --------------------------------------------------------------------
+#
+# --------------------------------------------------------------------
+
+vpath %.mex.c .
+
+src  := $(wildcard *.mex.c)
+msrc := $(wildcard *.m)
+stem := $(notdir $(basename $(basename $(src))))
+tgt  := $(addprefix ./, $(addsuffix .$(MEX_SUFFIX),$(stem)))
+
+%.$(MEX_SUFFIX) : %.mex.c
+        mex -I. $(MEX_CFLAGS) $< -output $*
+
+.PHONY: all
+all: $(tgt)
+
+.PHONY: info
+info :
+        @echo src  = $(src)
+        @echo stem = $(stem)
+        @echo tgt  = $(tgt)
+
+# PDF documentation
+.PHONY: doc
+doc: mser.html doc/mser.pdf
+
+mser.html : $(msrc)
+        mdoc --output=mser.html . \
+             --exclude='.*(_demo|_compile).*.m'
+
+.PHONY: clean
+clean:
+        rm -f $(tgt)
+        find . -name '.DS_Store' -exec rm -f \{\} \;
+        find . -name '.gdb_history' -exec rm -f \{\} \;
+        find . -name '*~' -exec rm -f \{\} \;
+        find . -name '*.bak' -exec rm -f \{\} \;
+        make -C doc/figures clean
+
+.PHONY: distclean
+distclean: clean
+        rm -f *.mexmac *.mexglx
+        rm -f mser.html
+        rm -f mser-*.tar.gz
+        rm -f doc/*.log
+        rm -f doc/*.aux
+        rm -f doc/*.toc
+        rm -f doc/*.bbl
+        rm -f doc/*.blg
+        rm -f doc/*.out
+        rm -f $(DIST).tar.gz
+        rm -f $(BINDIST).tar.gz
+        rm -rf $(BINDIST)
+
+.PHONY: dist
+dist: distclean
+        echo Version $(VER) >TIMESTAMP
+        echo Archive created on `date` >>TIMESTAMP
+        d=$(notdir $(CURDIR)) ; \
+        tar chzvf $(DIST).tar.gz \
+          --exclude mser_demo4.m \
+          --exclude data/seq.avi \
+          --exclude results \
+          ../$${d}
+
+.PHONY: bindist
+bindist: all
+        test -e $(BINDIST) || mkdir $(BINDIST)
+        cp *.$(MEX_SUFFIX) $(BINDIST)
+        cd $(BINDIST) ; strip -S *.$(MEX_SUFFIX)
+        tar chzvf $(BINDIST).tar.gz $(BINDIST)
+
+.PHONY: autorights
+autorights:
+        autorights . \
+          --verbose \
+          --recursive \
+          --template cal \
+          --years 2006 \
+          --authors "Andrea Vedaldi (UCLA VisionLab)" \
+          --program "Video Extremal Regions"
+
+doc/mser.pdf : doc/*.tex doc/*.bib doc/figures/*.fig
+        make -C doc/figures all
+        cd doc ; \
+        for k in 1 2 3 ; \
+        do \
+          pdflatex -file-line-error-style -interaction batchmode \
+            mser.tex ; \
+          if test "$$k" = '1' ; \
+          then \
+            bibtex mser.aux ; \
+          fi ; \
+        done
diff --git a/SD-VBS/benchmarks/mser/src/matlab/TIMESTAMP b/SD-VBS/benchmarks/mser/src/matlab/TIMESTAMP
new file mode 100755
index 0000000..1de1720
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/TIMESTAMP
@@ -0,0 +1,2 @@
+Version 0.4
+Archive created on Wed Feb 7 11:08:47 PST 2007
diff --git a/SD-VBS/benchmarks/mser/src/matlab/erfill.m b/SD-VBS/benchmarks/mser/src/matlab/erfill.m
new file mode 100755
index 0000000..6e11fc6
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/erfill.m
@@ -0,0 +1,13 @@
+% ERFILL  Fill extremal region
+%  MEMBERS=ERFILL(I,ER) returns the list MEMBERS of the pixels which
+%  belongs to the extremal region represented by the pixel ER.
+% 
+%  The selected region is the one that contains pixel ER and of
+%  inensity I(ER).
+%
+%  I must be of class UINT8 and ER must be a (scalar) index of the
+%  region representative point.
+%
+%  See also MSER().
+
+
diff --git a/SD-VBS/benchmarks/mser/src/matlab/erfill.mex.c b/SD-VBS/benchmarks/mser/src/matlab/erfill.mex.c
new file mode 100755
index 0000000..893d346
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/erfill.mex.c
@@ -0,0 +1,223 @@
+/* file:        erfill.mex.c
+** description: Extremal Regions filling
+** author:      Andrea Vedaldi
+**/
+
+/* AUTORIGHTS
+Copyright (C) 2006 Regents of the University of California
+All rights reserved
+
+Written by Andrea Vedaldi (UCLA VisionLab).
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met
+
+    * Redistributions of source code must retain the above copyright
+      notice, this list of conditions and the following disclaimer.
+    * Redistributions in binary form must reproduce the above copyright
+      notice, this list of conditions and the following disclaimer in the
+      documentation and/or other materials provided with the distribution.
+    * Neither the name of the University of California, Berkeley nor the
+      names of its contributors may be used to endorse or promote products
+      derived from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
+DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+*/
+
+/** @file
+ ** @brief Maximally Stable Extremal Regions - MEX implementation
+ **/
+
+#include<mexutils.c>
+#include<stdio.h>
+#include<stdlib.h>
+#include<math.h>
+#include<string.h>
+#include<assert.h>
+
+#define MIN(x,y) (((x)<(y))?(x):(y))
+#define MAX(x,y) (((x)>(y))?(x):(y))
+
+typedef char unsigned val_t ;
+typedef int  unsigned idx_t ;
+typedef long long int unsigned acc_t ;
+
+/* advance N-dimensional subscript */
+void
+adv(int const* dims, int ndims, int* subs_pt)
+{
+  int d = 0 ;
+  while(d < ndims) {
+    if( ++subs_pt[d]  < dims[d] ) return ;
+    subs_pt[d++] = 0 ;
+  }
+}
+
+/* driver */
+void
+mexFunction(int nout, mxArray *out[], 
+            int nin, const mxArray *in[])
+{
+
+  enum {IN_I=0, IN_ER} ;
+  enum {OUT_MEMBERS} ;
+
+  idx_t i ;
+  int k, nel, ndims ; 
+  int const * dims ;
+  val_t const * I_pt ;
+  int last = 0 ;
+  int last_expanded = 0 ;
+  val_t value = 0 ;
+
+  double const * er_pt ;
+
+  int*   subs_pt ;       /* N-dimensional subscript                 */
+  int*   nsubs_pt ;      /* diff-subscript to point to neigh.       */
+  idx_t* strides_pt ;    /* strides to move in image array          */
+  val_t* visited_pt ;    /* flag                                    */
+  idx_t* members_pt ;    /* region members                          */
+
+  /** -----------------------------------------------------------------
+   **                                               Check the arguments
+   ** -------------------------------------------------------------- */
+  if (nin != 2) {
+    mexErrMsgTxt("Two arguments required.") ;
+  } else if (nout > 4) {
+    mexErrMsgTxt("Too many output arguments.");
+  }
+  
+  if(mxGetClassID(in[IN_I]) != mxUINT8_CLASS) {
+    mexErrMsgTxt("I must be of class UINT8.") ;
+  }
+
+  if(!uIsRealScalar(in[IN_ER])) {
+    mexErrMsgTxt("ER must be a DOUBLE scalar.") ;
+  }
+
+  /* get dimensions */
+  nel   = mxGetNumberOfElements(in[IN_I]) ;
+  ndims = mxGetNumberOfDimensions(in[IN_I]) ;
+  dims  = mxGetDimensions(in[IN_I]) ;
+  I_pt  = mxGetData(in[IN_I]) ;
+
+  /* allocate stuff */
+  subs_pt    = mxMalloc( sizeof(int)      * ndims ) ;
+  nsubs_pt   = mxMalloc( sizeof(int)      * ndims ) ;
+  strides_pt = mxMalloc( sizeof(idx_t)    * ndims ) ;
+  visited_pt = mxMalloc( sizeof(val_t)    * nel   ) ;
+  members_pt = mxMalloc( sizeof(idx_t)    * nel   ) ;
+
+  er_pt = mxGetPr(in[IN_ER]) ;
+  
+  /* compute strides to move into the N-dimensional image array */
+  strides_pt [0] = 1 ;
+  for(k = 1 ; k < ndims ; ++k) {
+    strides_pt [k] = strides_pt [k-1] * dims [k-1] ;
+  }
+  
+  /* load first pixel */
+  memset(visited_pt, 0, sizeof(val_t) * nel) ;
+  {
+    idx_t idx = (idx_t) *er_pt ;
+    if( idx < 1 || idx > nel ) {
+      char buff[80] ;
+      snprintf(buff,80,"ER=%d out of range [1,%d]",idx,nel) ;    
+      mexErrMsgTxt(buff) ;
+    }
+    members_pt [last++] = idx - 1 ;
+  }
+  value = I_pt[ members_pt[0] ]  ;
+
+  /* -----------------------------------------------------------------
+   *                                                       Fill region
+   * -------------------------------------------------------------- */
+  while(last_expanded < last) {
+    
+    /* pop next node xi */
+    idx_t index = members_pt[last_expanded++] ;
+    
+    /* convert index into a subscript sub; also initialize nsubs 
+       to (-1,-1,...,-1) */
+    {
+      idx_t temp = index ;
+      for(k = ndims-1 ; k >=0 ; --k) {
+        nsubs_pt [k] = -1 ;
+        subs_pt  [k] = temp / strides_pt [k] ;
+        temp         = temp % strides_pt [k] ;
+      }
+    }
+    
+    /* process neighbors of xi */
+    while( true ) {
+      int good = true ;
+      idx_t nindex = 0 ;
+      
+      /* compute NSUBS+SUB, the correspoinding neighbor index NINDEX
+         and check that the pixel is within image boundaries. */
+      for(k = 0 ; k < ndims && good ; ++k) {
+        int temp = nsubs_pt [k] + subs_pt [k] ;
+        good &= 0 <= temp && temp < dims[k] ;
+        nindex += temp * strides_pt [k] ;
+      }      
+      
+      /* process neighbor
+         1 - the pixel is within image boundaries;
+         2 - the pixel is indeed different from the current node
+         (this happens when nsub=(0,0,...,0));
+         3 - the pixel has value not greather than val
+         is a pixel older than xi
+         4 - the pixel has not been visited yet
+      */
+      if(good 
+         && nindex != index 
+         && I_pt [nindex] <= value
+         && ! visited_pt [nindex] ) {
+        
+        /* mark as visited */
+        visited_pt [nindex] = 1 ;
+        
+        /* add to list */
+        members_pt [last++] = nindex ;
+      }
+      
+      /* move to next neighbor */      
+      k = 0 ;
+      while(++ nsubs_pt [k] > 1) {
+        nsubs_pt [k++] = -1 ;
+        if(k == ndims) goto done_all_neighbors ;
+      }
+    } /* next neighbor */
+  done_all_neighbors : ;
+  } /* goto pop next member */
+
+  /*
+   * Save results
+   */
+  {
+    int dims[2] ;
+    int unsigned * pt ;
+    dims[0] = last ;
+    out[OUT_MEMBERS] = mxCreateNumericArray(1,dims,mxUINT32_CLASS,mxREAL);
+    pt = mxGetData(out[OUT_MEMBERS]) ;
+    for (i = 0 ; i < last ; ++i) {
+      *pt++ = members_pt[i] + 1 ;
+    }
+  }
+  
+  /* free stuff */
+  mxFree( members_pt ) ;
+  mxFree( visited_pt ) ;
+  mxFree( strides_pt ) ;
+  mxFree( nsubs_pt   ) ;
+  mxFree( subs_pt    ) ;
+}
diff --git a/SD-VBS/benchmarks/mser/src/matlab/erfill.mexa64 b/SD-VBS/benchmarks/mser/src/matlab/erfill.mexa64
new file mode 100755
index 0000000..bc54d65
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/erfill.mexa64
diff --git a/SD-VBS/benchmarks/mser/src/matlab/erfill.mexglx b/SD-VBS/benchmarks/mser/src/matlab/erfill.mexglx
new file mode 100755
index 0000000..8eec110
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/erfill.mexglx
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mexutils.c b/SD-VBS/benchmarks/mser/src/matlab/mexutils.c
new file mode 100755
index 0000000..0fc664b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/mexutils.c
@@ -0,0 +1,111 @@
+/* file:        mexutils.c 
+** author:      Andrea Vedaldi
+** description: Utility functions to write MEX files.
+**/
+
+#include"mex.h"
+
+#undef M_PI
+#define M_PI 3.14159265358979
+
+/** @brief Is scalar?
+ **
+ ** @return @c true if the array @a A is a scalar.
+ **/
+int
+uIsScalar(const mxArray* A)
+{
+  return 
+    !mxIsComplex(A) &&
+    mxGetNumberOfDimensions(A) == 2 &&
+    mxGetM(A) == 1 &&
+    mxGetN(A) == 1 ;
+}
+
+/** @brief Is real scalar?
+ **
+ ** @return @c true if the array @a A is a real scalar.
+ **/
+int
+uIsRealScalar(const mxArray* A)
+{
+  return 
+    mxIsDouble(A) && 
+    !mxIsComplex(A) &&
+    mxGetNumberOfDimensions(A) == 2 &&
+    mxGetM(A) == 1 &&
+    mxGetN(A) == 1 ;
+}
+
+/** @brief Is real matrix?
+ **
+ ** The function checks wether the argument @a A is a real matrix.  In
+ ** addition, if @a M >= 0, it checks wether the number of rows is
+ ** equal to @a M and, if @a N >= 0, if the number of columns is equal
+ ** to @a N.
+ **
+ ** @param M number of rows.
+ ** @param N number of columns.
+ ** @return @c true if the array is a real matrix with the specified format.
+ **/
+int
+uIsRealMatrix(const mxArray* A, int M, int N)
+{
+  return  
+    mxIsDouble(A) &&
+    !mxIsComplex(A) &&
+    mxGetNumberOfDimensions(A) == 2 &&
+    ((M>=0)?(mxGetM(A) == M):1) &&
+    ((N>=0)?(mxGetN(A) == N):1) ;   
+}
+
+/** @brief Is real vector?
+ **
+ ** The function checks wether the argument  @a V is a real vector. By
+ ** definiton, a  matrix is a vector  if one of its  dimension is one.
+ ** In addition, if  @a D >= 0, it checks wether  the dimension of the
+ ** vecotr is equal to @a D.
+ **
+ ** @param D lenght of the vector.
+ ** @return @c true if the array is a real vector of the specified dimension.
+ **/
+int
+uIsRealVector(const mxArray* V, int D) 
+{
+  int M = mxGetM(V) ;
+  int N = mxGetN(V) ;
+  int is_vector = (N == 1) || (M == 1) ;
+  
+  return   
+    mxIsDouble(V) &&
+    !mxIsComplex(V) &&
+    mxGetNumberOfDimensions(V) == 2 &&
+    is_vector &&
+    ( D < 0 || N == D || M == D) ;
+}
+
+
+/** @brief Is a string?
+ **
+ ** The function checks wether the array @a S is a string. If
+ ** @a L is non-negative, it also check wether the strign has
+ ** length @a L.
+ **
+ ** @return @a c true if S is a string of the specified length.
+ **/
+int
+uIsString(const mxArray* S, int L)
+{
+  int M = mxGetM(S) ;
+  int N = mxGetN(S) ;
+
+  return 
+    mxIsChar(S) &&
+    M == 1 &&
+    (L < 0 || N == L) ;
+}
+
+/**
+ **
+ **/
+
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser.mex.c b/SD-VBS/benchmarks/mser/src/matlab/mser.mex.c
new file mode 100755
index 0000000..8473afe
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/mser.mex.c
@@ -0,0 +1,815 @@
+/* file:        mser.mex.c
+** description: Maximally Stable Extremal Regions
+** author:      Andrea Vedaldi
+**/
+
+/* AUTORIGHTS
+Copyright (C) 2006 Regents of the University of California
+All rights reserved
+
+Written by Andrea Vedaldi (UCLA VisionLab).
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met
+
+    * Redistributions of source code must retain the above copyright
+      notice, this list of conditions and the following disclaimer.
+    * Redistributions in binary form must reproduce the above copyright
+      notice, this list of conditions and the following disclaimer in the
+      documentation and/or other materials provided with the distribution.
+    * Neither the name of the University of California, Berkeley nor the
+      names of its contributors may be used to endorse or promote products
+      derived from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
+DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+*/
+
+/** @file
+ ** @brief Maximally Stable Extremal Regions - MEX implementation
+ **/
+
+#include<mexutils.c>
+#include<stdio.h>
+#include<stdlib.h>
+#include<math.h>
+#include<string.h>
+#include<assert.h>
+
+#define MIN(x,y) (((x)<(y))?(x):(y))
+#define MAX(x,y) (((x)>(y))?(x):(y))
+
+#define BUCKETS 256
+
+#define USE_BUCKET_SORT
+/*#define USE_RANK_UNION
+*/
+
+typedef char unsigned val_t ;
+typedef int  unsigned idx_t ;
+typedef long long int unsigned acc_t ;
+
+/* pairs are used to sort the pixels */
+typedef struct 
+{
+  val_t value ; 
+  idx_t  index ;
+} pair_t ;
+
+/* forest node */
+typedef struct
+{
+  idx_t parent ;   /**< parent pixel         */
+  idx_t shortcut ; /**< shortcut to the root */
+  idx_t region ;   /**< index of the region  */
+  int   area ;     /**< area of the region   */
+#ifdef USE_RANK_UNION
+  int   height ;    /**< node height         */
+#endif
+} node_t ;
+
+/* extremal regions */
+typedef struct
+{
+  idx_t parent ;     /**< parent region                           */
+  idx_t index ;      /**< index of root pixel                     */
+  val_t value ;      /**< value of root pixel                     */
+  int   area ;       /**< area of the region                      */
+  int   area_top ;   /**< area of the region DELTA levels above   */
+  int   area_bot  ;  /**< area of the region DELTA levels below   */
+  float variation ;  /**< variation                               */
+  int   maxstable ;  /**< max stable number (=0 if not maxstable) */
+} region_t ;
+
+/* predicate used to sort pixels by increasing intensity */
+int 
+cmp_pair(void const* a, void const* b) 
+{
+  pair_t* pa = (pair_t*) a;
+  pair_t* pb = (pair_t*) b;
+  return pa->value - pb->value ;
+}
+
+/* advance N-dimensional subscript */
+void
+adv(int const* dims, int ndims, int* subs_pt)
+{
+  int d = 0 ;
+  while(d < ndims) {
+    if( ++subs_pt[d]  < dims[d] ) return ;
+    subs_pt[d++] = 0 ;
+  }
+}
+
+/* driver */
+void
+mexFunction(int nout, mxArray *out[], 
+            int nin, const mxArray *in[])
+{
+  enum {IN_I=0, IN_DELTA} ;
+  enum {OUT_REGIONS=0, OUT_ELL, OUT_PARENTS, OUT_AREA} ;
+
+  idx_t i ;
+  idx_t rindex = 0 ;
+  int k ; 
+
+  /* configuration */
+  int verbose = 0 ;      /* be verbose                              */
+  int small_cleanup= 1 ; /* remove very small regions               */
+  int big_cleanup  = 1 ; /* remove very big regions                 */
+  int bad_cleanup  = 0 ; /* remove very bad regions                 */
+  int dup_cleanup  = 1 ; /* remove duplicates                       */
+  val_t delta ;          /* stability delta                         */
+
+  /* node value denoting a void node */
+  idx_t const node_is_void = 0xffffffff ;
+
+  int*   subs_pt ;       /* N-dimensional subscript                 */
+  int*   nsubs_pt ;      /* diff-subscript to point to neigh.       */
+  idx_t* strides_pt ;    /* strides to move in image array          */
+  idx_t* visited_pt ;    /* flag                                    */
+
+  int nel ;              /* number of image elements (pixels)       */
+  int ner = 0 ;          /* number of extremal regions              */
+  int nmer = 0 ;         /* number of maximally stable              */
+  int ndims ;            /* number of dimensions                    */
+  int const* dims ;      /* dimensions                              */
+  int njoins = 0 ;       /* number of join ops                      */
+
+  val_t const* I_pt ;    /* source image                            */
+  pair_t*   pairs_pt ;   /* scratch buffer to sort pixels           */
+  node_t*   forest_pt ;  /* the extremal regions forest             */
+  region_t* regions_pt ; /* list of extremal regions found          */ 
+
+  /* ellipses fitting */
+  acc_t* acc_pt ;        /* accumulator to integrate region moments */
+  acc_t* ell_pt ;        /* ellipses parameters                     */
+  int    gdl ;           /* number of parameters of an ellipse      */
+  idx_t* joins_pt ;      /* sequence of joins                       */
+  
+  /** -----------------------------------------------------------------
+   **                                               Check the arguments
+   ** -------------------------------------------------------------- */
+  if (nin != 2) {
+    mexErrMsgTxt("Two arguments required.") ;
+  } else if (nout > 4) {
+    mexErrMsgTxt("Too many output arguments.");
+  }
+  
+  if(mxGetClassID(in[IN_I]) != mxUINT8_CLASS) {
+    mexErrMsgTxt("I must be of class UINT8") ;
+  }
+
+  if(!uIsScalar(in[IN_DELTA])) {
+    mexErrMsgTxt("DELTA must be scalar") ;
+  }
+
+  delta = 0 ;
+  switch(mxGetClassID(in[IN_DELTA])) {
+  case mxUINT8_CLASS :
+    delta = * (val_t*) mxGetData(in[IN_DELTA]) ;
+    break ;
+    
+  case mxDOUBLE_CLASS :
+    {
+      double x = *mxGetPr(in[IN_DELTA])  ;
+      if(x < 0.0) {
+        mexErrMsgTxt("DELTA must be non-negative") ;
+      }
+      delta = (val_t) x ;      
+    }
+    break ;
+    
+  default :
+    mexErrMsgTxt("DELTA must be of class DOUBLE or UINT8") ;
+  }
+
+  /* get dimensions */
+  nel   = mxGetNumberOfElements(in[IN_I]) ;
+  ndims = mxGetNumberOfDimensions(in[IN_I]) ;
+  dims  = mxGetDimensions(in[IN_I]) ;
+  I_pt  = mxGetData(in[IN_I]) ;
+
+  /* allocate stuff */
+  subs_pt    = mxMalloc( sizeof(int)      * ndims ) ;
+  nsubs_pt   = mxMalloc( sizeof(int)      * ndims ) ;
+  strides_pt = mxMalloc( sizeof(idx_t)    * ndims ) ;
+  visited_pt = mxMalloc( sizeof(idx_t)    * nel   ) ;
+  regions_pt = mxMalloc( sizeof(region_t) * nel   ) ;
+  pairs_pt   = mxMalloc( sizeof(pair_t)   * nel   ) ;
+  forest_pt  = mxMalloc( sizeof(node_t)   * nel   ) ;
+  joins_pt   = mxMalloc( sizeof(idx_t)    * nel   ) ;
+  
+  /* compute strides to move into the N-dimensional image array */
+  strides_pt [0] = 1 ;
+  for(k = 1 ; k < ndims ; ++k) {
+    strides_pt [k] = strides_pt [k-1] * dims [k-1] ;
+  }
+
+  /* sort pixels by increasing intensity*/
+  verbose && mexPrintf("Sorting pixels ... ") ;
+  
+#ifndef USE_BUCKET_SORT
+  for(i = 0 ; i < nel ; ++i) {
+    pairs_pt [i].value = I_pt [i] ;
+    pairs_pt [i].index = i ;
+  }
+  qsort(pairs_pt, nel, sizeof(pair_t), cmp_pair) ;
+#else
+  {
+    int unsigned buckets [BUCKETS] ;
+    int unsigned v;
+    memset(buckets, 0, sizeof(int unsigned)*BUCKETS) ;
+    for(i = 0 ; i < nel ; ++i) {
+      v = (unsigned int)I_pt [i] ;
+      ++buckets[v] ;
+    }
+    for(i = 1 ; i < BUCKETS ; ++i) {
+      buckets[i] += buckets[i-1] ;
+    }
+    for(i = nel ; i >= 1 ; ) {
+      v = I_pt [--i] ;
+      idx_t j = --buckets [v] ;
+      pairs_pt [j].value = v ;
+      pairs_pt [j].index = i ;
+    }
+  }
+#endif
+  verbose && mexPrintf("done\n") ;
+
+  /* initialize the forest with all void nodes */
+  for(i = 0 ; i < nel ; ++i) {
+    forest_pt [i].parent = node_is_void  ;
+  }
+  
+  /* number of ellipse free parameters */
+  gdl = ndims*(ndims+1)/2 + ndims ;
+
+  /* -----------------------------------------------------------------
+   *                                     Compute extremal regions tree
+   * -------------------------------------------------------------- */
+  verbose && mexPrintf("Computing extremal regions ... ") ;
+  for(i = 0 ; i < nel ; ++i) {
+    
+    /* pop next node xi */
+    idx_t index = pairs_pt [i].index ;    
+    val_t value = pairs_pt [i].value ;
+      
+
+    /* this will be needed later */
+    rindex = index ;
+        
+    /* push it into the tree */
+    forest_pt [index] .parent   = index ;
+    forest_pt [index] .shortcut = index ;
+    forest_pt [index] .area     = 1 ;
+#ifdef USE_RANK_UNION
+    forest_pt [index] .height   = 1 ;
+#endif
+    
+    /* convert index into a subscript sub; also initialize nsubs 
+       to (-1,-1,...,-1) */
+    {
+      idx_t temp = index ;
+      for(k = ndims-1 ; k >=0 ; --k) {
+        nsubs_pt [k] = -1 ;
+        subs_pt  [k] = temp / strides_pt [k] ;
+        temp         = temp % strides_pt [k] ;
+      }
+    }
+    
+    /* process neighbors of xi */
+    while( true ) {
+      int good = true ;
+      idx_t nindex = 0 ;
+      
+      /* compute NSUBS+SUB, the correspoinding neighbor index NINDEX
+         and check that the pixel is within image boundaries. */
+      for(k = 0 ; k < ndims && good ; ++k) {
+        int temp = nsubs_pt [k] + subs_pt [k] ;
+        good &= 0 <= temp && temp < dims[k] ;
+        nindex += temp * strides_pt [k] ;
+      }      
+      
+      /* keep going only if
+         1 - the neighbor is within image boundaries;
+         2 - the neighbor is indeed different from the current node
+             (this happens when nsub=(0,0,...,0));
+         3 - the nieghbor is already in the tree, meaning that
+             is a pixel older than xi.
+      */
+      if(good && 
+         nindex != index &&
+         forest_pt[nindex].parent != node_is_void ) {
+        
+        idx_t nrindex = 0, nvisited ;
+        val_t nrvalue = 0 ;
+
+#ifdef USE_RANK_UNION
+        int height  = forest_pt [ rindex] .height ;
+        int nheight = forest_pt [nrindex] .height ;
+#endif
+        
+        /* RINDEX = ROOT(INDEX) might change as we merge trees, so we
+           need to update it after each merge */
+        
+        /* find the root of the current node */
+        /* also update the shortcuts */
+        nvisited = 0 ;
+        while( forest_pt[rindex].shortcut != rindex ) {          
+          visited_pt[ nvisited++ ] = rindex ;
+          rindex = forest_pt[rindex].shortcut ;
+        }      
+        while( nvisited-- ) {
+          forest_pt [ visited_pt[nvisited] ] .shortcut = rindex ;
+        }
+        
+        /* find the root of the neighbor */
+        nrindex  = nindex ;
+        nvisited = 0 ;
+        while( forest_pt[nrindex].shortcut != nrindex ) {          
+          visited_pt[ nvisited++ ] = nrindex ;
+          nrindex = forest_pt[nrindex].shortcut ;
+        }      
+        while( nvisited-- ) {
+          forest_pt [ visited_pt[nvisited] ] .shortcut = nrindex ;
+        }
+        
+        /*
+          Now we join the two subtrees rooted at
+          
+            RINDEX = ROOT(INDEX) and NRINDEX = ROOT(NINDEX).
+          
+          Only three things can happen:
+          
+          a - ROOT(INDEX) == ROOT(NRINDEX). In this case the two trees
+              have already been joined and we do not do anything.
+          
+          b - I(ROOT(INDEX)) == I(ROOT(NRINDEX)). In this case index
+              is extending an extremal region with the same
+              value. Since ROOT(NRINDEX) will NOT be an extremal
+              region of the full image, ROOT(INDEX) can be safely
+              addedd as children of ROOT(NRINDEX) if this reduces
+              the height according to union rank.
+               
+          c - I(ROOT(INDEX)) > I(ROOT(NRINDEX)) as index is extending
+              an extremal region, but increasing its level. In this
+              case ROOT(NRINDEX) WILL be an extremal region of the
+              final image and the only possibility is to add
+              ROOT(NRINDEX) as children of ROOT(INDEX).
+        */
+
+        if( rindex != nrindex ) {
+          /* this is a genuine join */
+          
+          nrvalue = I_pt [nrindex] ;
+          if( nrvalue == value 
+#ifdef USE_RANK_UNION             
+              && height < nheight
+#endif
+              ) {
+            /* ROOT(INDEX) becomes the child */
+            forest_pt[rindex] .parent   = nrindex ;
+            forest_pt[rindex] .shortcut = nrindex ;          
+            forest_pt[nrindex].area    += forest_pt[rindex].area ;
+
+#ifdef USE_RANK_UNION
+            forest_pt[nrindex].height = MAX(nheight, height+1) ;
+#endif
+
+            joins_pt[njoins++] = rindex ;
+
+          } else {
+            /* ROOT(index) becomes parent */
+            forest_pt[nrindex] .parent   = rindex ;
+            forest_pt[nrindex] .shortcut = rindex ;
+            forest_pt[rindex]  .area    += forest_pt[nrindex].area ;
+
+#ifdef USE_RANK_UNION
+            forest_pt[rindex].height = MAX(height, nheight+1) ;
+#endif
+            if( nrvalue != value ) {            
+              /* nrindex is extremal region: save for later */
+              forest_pt[nrindex].region = ner ;
+              regions_pt [ner] .index      = nrindex ;
+              regions_pt [ner] .parent     = ner ;
+              regions_pt [ner] .value      = nrvalue ;
+              regions_pt [ner] .area       = forest_pt [nrindex].area ;
+              regions_pt [ner] .area_top   = nel ;
+              regions_pt [ner] .area_bot   = 0 ;            
+              ++ner ;
+            }
+            
+            /* annote join operation for post-processing */
+            joins_pt[njoins++] = nrindex ;
+          }
+        }
+        
+      } /* neighbor done */
+      
+      /* move to next neighbor */      
+      k = 0 ;
+      while(++ nsubs_pt [k] > 1) {
+        nsubs_pt [k++] = -1 ;
+        if(k == ndims) goto done_all_neighbors ;
+      }
+    } /* next neighbor */
+  done_all_neighbors : ;
+  } /* next pixel */    
+    
+    
+  /* the root of the last processed pixel must be a region */
+  forest_pt [rindex].region = ner ;
+  regions_pt [ner] .index      = rindex ;
+  regions_pt [ner] .parent     = ner ;
+  regions_pt [ner] .value      = I_pt      [rindex] ;
+  regions_pt [ner] .area       = forest_pt [rindex] .area ;
+  regions_pt [ner] .area_top   = nel ;
+  regions_pt [ner] .area_bot   = 0 ;            
+  ++ner ;
+
+  verbose && mexPrintf("done\nExtremal regions: %d\n", ner) ;
+  
+  /* -----------------------------------------------------------------
+   *                                            Compute region parents
+   * -------------------------------------------------------------- */
+  for( i = 0 ; i < ner ; ++i) {
+    idx_t index  = regions_pt [i].index ;    
+    val_t value  = regions_pt [i].value ;
+    idx_t j      = i ;
+
+    while(j == i) {
+      idx_t pindex = forest_pt [index].parent ;
+      val_t pvalue = I_pt [pindex] ;
+
+      /* top of the tree */
+      if(index == pindex) {
+        j = forest_pt[index].region ;
+        break ;
+      }
+
+      /* if index is the root of a region, either this is still
+         i, or it is the parent region we are looking for. */
+      if(value < pvalue) {
+        j = forest_pt[index].region ;
+      }
+
+      index = pindex ;
+      value = pvalue ;
+    }
+    regions_pt[i]. parent = j ;
+  }
+  
+  /* -----------------------------------------------------------------
+   *                                 Compute areas of tops and bottoms
+   * -------------------------------------------------------------- */
+
+  /* We scan the list of regions from the bottom. Let x0 be the current
+     region and be x1 = PARENT(x0), x2 = PARENT(x1) and so on.
+     
+     Here we do two things:
+     
+     1) Look for regions x for which x0 is the BOTTOM. This requires
+        VAL(x0) <= VAL(x) - DELTA < VAL(x1).
+        We update AREA_BOT(x) for each of such x found.
+        
+     2) Look for the region y which is the TOP of x0. This requires
+          VAL(y) <= VAL(x0) + DELTA < VAL(y+1)
+          We update AREA_TOP(x0) as soon as we find such y.
+        
+  */
+
+  for( i = 0 ; i < ner ; ++i) {
+    /* fix xi as the region, then xj are the parents */
+    idx_t parent = regions_pt [i].parent ;
+    int   val0   = regions_pt [i].value ;
+    int   val1   = regions_pt [parent].value ;
+    int   val    = val0 ;
+    idx_t j = i ;
+
+    while(true) {
+      int valp = regions_pt [parent].value ;
+
+      /* i is the bottom of j */
+      if(val0 <= val - delta && val - delta < val1) {
+        regions_pt [j].area_bot  =
+          MAX(regions_pt [j].area_bot, regions_pt [i].area) ;
+      }
+      
+      /* j is the top of i */
+      if(val <= val0 + delta && val0 + delta < valp) {
+        regions_pt [i].area_top = regions_pt [j].area ;
+      }
+      
+      /* stop if going on is useless */
+      if(val1 <= val - delta && val0 + delta < val)
+        break ;
+
+      /* stop also if j is the root */
+      if(j == parent)
+        break ;
+      
+      /* next region upward */
+      j      = parent ;
+      parent = regions_pt [j].parent ;
+      val    = valp ;
+    }
+  }
+
+  /* -----------------------------------------------------------------
+   *                                                 Compute variation
+   * -------------------------------------------------------------- */
+  for(i = 0 ; i < ner ; ++i) {
+    int area     = regions_pt [i].area ;
+    int area_top = regions_pt [i].area_top ;
+    int area_bot = regions_pt [i].area_bot ;    
+    regions_pt [i].variation = 
+      (float)(area_top - area_bot) / (float)area ;
+
+    /* initialize .mastable to 1 for all nodes */
+    regions_pt [i].maxstable = 1 ;
+  }
+
+  /* -----------------------------------------------------------------
+   *                     Remove regions which are NOT maximally stable
+   * -------------------------------------------------------------- */
+  nmer = ner ;
+  for(i = 0 ; i < ner ; ++i) {
+    idx_t parent = regions_pt [i]      .parent ;
+    float var    = regions_pt [i]      .variation ;
+    float pvar   = regions_pt [parent] .variation ;
+    idx_t loser ;
+
+    /* decide which one to keep and put that in loser */
+    if(var < pvar) loser = parent ; else loser = i ;
+    
+    /* make loser NON maximally stable */
+    if(regions_pt [loser].maxstable) --nmer ;
+    regions_pt [loser].maxstable = 0 ;
+  }
+
+  verbose && mexPrintf("Maximally stable regions: %d (%.1f%%)\n", 
+                       nmer, 100.0 * (double) nmer / ner) ;
+
+  /* -----------------------------------------------------------------
+   *                                               Remove more regions
+   * -------------------------------------------------------------- */
+
+  /* it is critical for correct duplicate detection to remove regions
+     from the bottom (smallest one first) */
+
+  if( big_cleanup || small_cleanup || bad_cleanup || dup_cleanup ) {
+    int nbig   = 0 ;
+    int nsmall = 0 ;
+    int nbad   = 0 ;
+    int ndup   = 0 ;
+
+    /* scann all extremal regions */
+    for(i = 0 ; i < ner ; ++i) {
+      
+      /* process only maximally stable extremal regions */
+      if(! regions_pt [i].maxstable) continue ;
+      
+      if( bad_cleanup   && regions_pt[i].variation >= 1.0f  ) {
+        ++nbad ;
+        goto remove_this_region ;
+      }
+
+      if( big_cleanup   && regions_pt[i].area      >  nel/2 ) {
+        ++nbig ;
+        goto remove_this_region ;
+      }
+
+      if( small_cleanup && regions_pt[i].area      <  25    ) {
+        ++nsmall ;
+        goto remove_this_region ;
+      }
+      
+      /* 
+       * Remove duplicates 
+       */
+      if( dup_cleanup ) {
+        idx_t parent = regions_pt [i].parent ;
+        int area, parea ;
+        float change ;
+        
+        /* the search does not apply to root regions */
+        if(parent != i) {
+          
+          /* search for the maximally stable parent region */
+          while(! regions_pt[parent].maxstable) {
+            idx_t next = regions_pt[parent].parent ;
+            if(next == parent) break ;
+            parent = next ;
+          }
+          
+          /* compare with the parent region; if the current and parent
+             regions are too similar, keep only the parent */
+          area   = regions_pt [i].area ;
+          parea  = regions_pt [parent].area ;
+          change = (float)(parea - area)/area ;
+
+          if(change < 0.5)  {
+            ++ndup ;
+            goto remove_this_region ;
+          }
+
+        } /* drop duplicates */ 
+      }
+      continue ;
+    remove_this_region :
+      regions_pt[i].maxstable = false ;
+      --nmer ;      
+    } /* next region to cleanup */
+
+    if(verbose) {
+      mexPrintf("  Bad regions:        %d\n", nbad   ) ;
+      mexPrintf("  Small regions:      %d\n", nsmall ) ;
+      mexPrintf("  Big regions:        %d\n", nbig   ) ;
+      mexPrintf("  Duplicated regions: %d\n", ndup   ) ;
+    }
+  }
+
+  verbose && mexPrintf("Cleaned-up regions: %d (%.1f%%)\n", 
+                       nmer, 100.0 * (double) nmer / ner) ;
+
+  /* -----------------------------------------------------------------
+   *                                                      Fit ellipses
+   * -------------------------------------------------------------- */
+  
+  ell_pt = 0 ;
+  if (nout >= 1) {
+    int midx = 1 ;
+    int d, index, j ;
+    
+    verbose && mexPrintf("Fitting ellipses...\n") ;
+
+    /* enumerate maxstable regions */
+    for(i = 0 ; i < ner ; ++i) {      
+      if(! regions_pt [i].maxstable) continue ;
+      regions_pt [i].maxstable = midx++ ;
+    }
+    
+    /* allocate space */
+    acc_pt = mxMalloc(sizeof(acc_t) * nel) ;
+    ell_pt = mxMalloc(sizeof(acc_t) * gdl * nmer) ; 
+    
+    /* clear accumulators */
+    memset(ell_pt, 0, sizeof(int) * gdl * nmer) ;
+    
+    /* for each gdl */
+    for(d = 0 ; d < gdl ; ++d) {
+      /* initalize parameter */
+      memset(subs_pt, 0, sizeof(int) * ndims) ;
+      
+      if(d < ndims) {
+        verbose && mexPrintf(" mean %d\n",d) ;
+        for(index = 0 ; index < nel ; ++ index) {
+          acc_pt[index] = subs_pt[d] ;
+          adv(dims, ndims, subs_pt) ;
+        }
+
+      } else {
+
+        /* decode d-ndims into a (i,j) pair */
+        i = d-ndims ; 
+        j = 0 ;
+        while(i > j) {
+          i -= j + 1 ;
+          j ++ ;
+        }
+
+        verbose && mexPrintf(" corr (%d,%d)\n",i,j) ;
+
+        /* add x_i * x_j */
+        for(index = 0 ; index < nel ; ++ index){
+          acc_pt[index] = subs_pt[i]*subs_pt[j] ;
+          adv(dims, ndims, subs_pt) ;
+        }
+      }
+
+      /* integrate parameter */
+      for(i = 0 ; i < njoins ; ++i) {      
+        idx_t index  = joins_pt[i] ;
+        idx_t parent = forest_pt [ index ].parent ;
+        acc_pt[parent] += acc_pt[index] ;
+      }
+    
+      /* save back to ellpises */
+      for(i = 0 ; i < ner ; ++i) {
+        idx_t region = regions_pt [i].maxstable ;
+
+        /* skip if not extremal region */
+        if(region-- == 0) continue ;
+        ell_pt [d + gdl*region] = acc_pt [ regions_pt[i].index ] ;
+      }
+
+      /* next gdl */
+    }
+    mxFree(acc_pt) ;
+  }
+
+  
+  /* -----------------------------------------------------------------
+   *                                                Save back and exit
+   * -------------------------------------------------------------- */
+
+  /*
+   * Save extremal regions
+   */
+  {
+    int dims[2] ;
+    int unsigned * pt ;
+    dims[0] = nmer ;
+    out[OUT_REGIONS] = mxCreateNumericArray(1,dims,mxUINT32_CLASS,mxREAL);
+    pt = mxGetData(out[OUT_REGIONS]) ;
+    for (i = 0 ; i < ner ; ++i) {
+      if( regions_pt[i].maxstable ) {
+        /* adjust for MATLAB index compatibility */
+        *pt++ = regions_pt[i].index + 1 ;
+      }
+    }
+  }
+  
+  /*
+   * Save fitted ellipses
+   */
+  if(nout >= 2) {
+    int dims[2], d, j, index ;
+    double * pt ;
+    dims[0] = gdl ;
+    dims[1] = nmer ;
+     
+    out[OUT_ELL] = mxCreateNumericArray(2,dims,mxDOUBLE_CLASS,mxREAL) ;
+    pt = mxGetData(out[OUT_ELL]) ;
+
+    for(index = 0 ; index < nel ; ++index) {
+
+      idx_t region = regions_pt [index] .maxstable ;      
+      int   N      = regions_pt [index] .area ;
+
+      if(region-- == 0) continue ;
+
+      for(d = 0  ; d  < gdl ; ++d) {
+
+        pt[d] = (double) ell_pt[gdl*region  + d] / N ;
+
+        if(d < ndims) {
+          /* adjust for MATLAB coordinate frame convention */
+          pt[d] += 1 ; 
+        } else {
+          /* remove squared mean from moment to get variance */
+          i = d - ndims ; 
+          j = 0 ;
+          while(i > j) {
+            i -= j + 1 ;
+            j ++ ;
+          }
+          pt[d] -= (pt[i]-1)*(pt[j]-1) ;
+        }
+      }
+      pt += gdl ;
+    }
+    mxFree(ell_pt) ;
+  }
+  
+  if(nout >= 3)  {
+    int unsigned * pt ;
+    out[OUT_PARENTS] = mxCreateNumericArray(ndims,dims,mxUINT32_CLASS,mxREAL) ;
+    pt = mxGetData(out[OUT_PARENTS]) ;
+    for(i = 0 ; i < nel ; ++i) {
+      *pt++ = forest_pt[i].parent ;
+    }
+  }
+
+  if(nout >= 4) {
+    int dims[2] ;
+    int unsigned * pt ;
+    dims[0] = 3 ;
+    dims[1]= ner ;
+    out[OUT_AREA] = mxCreateNumericArray(2,dims,mxUINT32_CLASS,mxREAL);
+    pt = mxGetData(out[OUT_AREA]) ;
+    for( i = 0 ; i < ner ; ++i ) {
+      *pt++ = regions_pt [i]. area_bot ;
+      *pt++ = regions_pt [i]. area ;
+      *pt++ = regions_pt [i]. area_top ;      
+    }
+  }
+
+  /* free stuff */
+  mxFree( forest_pt  ) ;
+  mxFree( pairs_pt   ) ;
+  mxFree( regions_pt ) ;
+  mxFree( visited_pt ) ;
+  mxFree( strides_pt ) ;
+  mxFree( nsubs_pt   ) ;
+  mxFree( subs_pt    ) ;
+}
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser.mexa64 b/SD-VBS/benchmarks/mser/src/matlab/mser.mexa64
new file mode 100755
index 0000000..e3ca56b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/mser.mexa64
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser.mexglx b/SD-VBS/benchmarks/mser/src/matlab/mser.mexglx
new file mode 100755
index 0000000..b69e1d2
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/mser.mexglx
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser_compile.m b/SD-VBS/benchmarks/mser/src/matlab/mser_compile.m
new file mode 100755
index 0000000..5e3562b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/mser_compile.m
@@ -0,0 +1,7 @@
+function mser_compile(type)
+% MSER_COMPILE  Compile MEX files
+
+opts = { '-O', '-I.' } ;
+
+mex('mser.mex.c','-output', 'mser',opts{:}) ;
+mex('erfill.mex.c','-output', 'erfill',opts{:}) ;
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser_demo2.m b/SD-VBS/benchmarks/mser/src/matlab/mser_demo2.m
new file mode 100755
index 0000000..37a4ed1
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/mser_demo2.m
@@ -0,0 +1,62 @@
+% MSER_DEMO2  Demonstrate MSER code
+
+% AUTORIGHTS
+% Copyright (C) 2006 Regents of the University of California
+% All rights reserved
+% 
+% Written by Andrea Vedaldi (UCLA VisionLab).
+% 
+% Redistribution and use in source and binary forms, with or without
+% modification, are permitted provided that the following conditions are met
+% 
+%     * Redistributions of source code must retain the above copyright
+%       notice, this list of conditions and the following disclaimer.
+%     * Redistributions in binary form must reproduce the above copyright
+%       notice, this list of conditions and the following disclaimer in the
+%       documentation and/or other materials provided with the distribution.
+%     * Neither the name of the University of California, Berkeley nor the
+%       names of its contributors may be used to endorse or promote products
+%       derived from this software without specific prior written permission.
+% 
+% THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+% EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+% WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+% DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
+% DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+% (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+% LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+% ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+% (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+% SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+I = load('clown') ; I = uint8(I.X) ;
+figure(1) ; imagesc(I) ; colormap gray; hold on ;
+
+[M,N] = size(I) ;
+i = double(i) ;
+j = double(j) ;
+
+[r,ell] = mser(I,5) ;
+
+r=double(r) ;
+
+[i,j]=ind2sub(size(I),r) ;                    
+plot(j,i,'r*') ;
+
+ell = ell([2 1 5 4 3],:) ;
+plotframe(ell); 
+
+figure(2) ; 
+
+clear MOV ;
+K = size(ell,2) ;
+for k=1:K
+  clf ;
+  sel = erfill(I,r(k)) ;
+  mask = zeros(M,N) ; mask(sel) =1 ;
+  imagesc(cat(3,I,255*uint8(mask),I)) ; colormap gray ; hold on ;
+  set(gca,'position',[0 0 1 1]) ; axis off ; axis equal ;
+  plot(j(k),i(k),'r*') ;
+  plotframe(ell(:,k),'color','r') ;
+  MOV(k) = getframe(gca) ;
+end
diff --git a/SD-VBS/benchmarks/mser/src/matlab/mser_demo3.m b/SD-VBS/benchmarks/mser/src/matlab/mser_demo3.m
new file mode 100755
index 0000000..4669437
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/mser_demo3.m
@@ -0,0 +1,117 @@
+% MSER_DEMO3  Demonstrates MSER on a volumetric image
+
+% AUTORIGHTS
+% Copyright (C) 2006 Regents of the University of California
+% All rights reserved
+% 
+% Written by Andrea Vedaldi (UCLA VisionLab).
+% 
+% Redistribution and use in source and binary forms, with or without
+% modification, are permitted provided that the following conditions are met
+% 
+%     * Redistributions of source code must retain the above copyright
+%       notice, this list of conditions and the following disclaimer.
+%     * Redistributions in binary form must reproduce the above copyright
+%       notice, this list of conditions and the following disclaimer in the
+%       documentation and/or other materials provided with the distribution.
+%     * Neither the name of the University of California, Berkeley nor the
+%       names of its contributors may be used to endorse or promote products
+%       derived from this software without specific prior written permission.
+% 
+% THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+% EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+% WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+% DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
+% DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+% (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+% LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+% ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+% (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+% SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+% --------------------------------------------------------------------
+%                                                          Create data
+% --------------------------------------------------------------------
+
+% volumetric coordinate (x,y,z)
+x       = linspace(-1,1,50) ;
+[x,y,z] = meshgrid(x,x,x) ;
+
+% create funny volumetric image
+I   = sin(4*x).*cos(4*y).*sin(z) ;
+I   = I-min(I(:)) ;
+I   = I/max(I(:)) ;
+
+% quantize the image in 10 levels
+lev = 10 ;
+I   = lev*I ;
+Ir  = round(I) ;
+
+% --------------------------------------------------------------------
+%                                                      Compute regions
+% --------------------------------------------------------------------
+[idx,ell,p] = mser(uint8(Ir),1);
+
+% --------------------------------------------------------------------
+%                                                                Plots
+% --------------------------------------------------------------------
+
+% The image is quantized; store in LEV its range.
+lev = unique(Ir(idx)) ;
+
+figure(100); clf;
+K=min(length(lev),4) ;
+
+r=.99 ;
+
+% one level per time
+for k=1:K
+  tightsubplot(K,k) ;
+  [i,j,m] = ind2sub(size(I), idx(Ir(idx)==lev(k)) ) ;
+  
+  % compute level set of level LEV(k)
+  Is = double(Ir<=lev(k)) ;
+    
+  p1 = patch(isosurface(Is,r), ...
+             'FaceColor','blue','EdgeColor','none') ;
+  p2 = patch(isocaps(Is,r),...
+             'FaceColor','interp','EdgeColor','none') ;  
+  isonormals(I,p1)
+  hold on ;
+  
+  view(3); axis vis3d tight
+  camlight; lighting phong ;
+  
+  % find regions that have this level
+  sel = find( Ir(idx) == lev(k) ) ;
+  
+  % plot fitted ellipsoid
+  for r=sel'
+    E = ell(:,r) ;
+    c = E(1:3) ;
+    A = zeros(3) ;
+    A(1,1) = E(4) ;
+    A(1,2) = E(5) ;
+    A(2,2) = E(6) ;
+    A(1,3) = E(7) ;
+    A(2,3) = E(8) ;
+    A(3,3) = E(9) ;
+    
+    A = A + A' - diag(diag(A)) ;
+
+    % correct var. order
+    perm = [0 1 0 ; 1 0 0 ; 0 0 1] ;
+    A = perm*A*perm ;
+    
+    [V,D] = eig(A) ;
+    A = 2.5*V*sqrt(D) ;
+    
+    [x,y,z]=sphere ;
+    [P,Q]=size(x) ;    
+    X=A*[x(:)';y(:)';z(:)'] ;
+    x=reshape(X(1,:),P,Q)+c(2) ;
+    y=reshape(X(2,:),P,Q)+c(1) ;
+    z=reshape(X(3,:),P,Q)+c(3) ;
+    surf(x,y,z,'FaceAlpha',.5) ;        
+  end
+end
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/Makefile b/SD-VBS/benchmarks/mser/src/matlab/old/Makefile
new file mode 100755
index 0000000..29c0982
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/Makefile
@@ -0,0 +1,123 @@
+# file:        Makefile
+# author:      Andrea Vedaldi
+# description: Build mex files
+
+# --------------------------------------------------------------------
+# 
+# --------------------------------------------------------------------
+
+# Determine on the flight the system we are running on
+Darwin_ARCH := mac
+Linux_ARCH  := glx
+ARCH := $($(shell uname)_ARCH)
+
+mac_CFLAGS       := -I. -pedantic -Wall -Wno-long-long
+mac_MEX_CFLAGS   := -g -O CFLAGS='$$CFLAGS $(mac_CFLAGS)'
+mac_MEX_SUFFIX   := mexmac
+
+glx_CFLAGS       := -I. -pedantic -Wall -Wno-long-long
+glx_MEX_CFLAGS   := -g -O CFLAGS='$$CFLAGS $(glx_CFLAGS)'
+glx_MEX_SUFFIX   := mexglx
+
+MEX_SUFFIX       := $($(ARCH)_MEX_SUFFIX)
+MEX_CFLAGS       := $($(ARCH)_MEX_CFLAGS)
+
+VER              := 0.4
+DIST             := mser-$(VER)
+BINDIST          := $(DIST)-$(ARCH)
+
+# --------------------------------------------------------------------
+#
+# --------------------------------------------------------------------
+
+vpath %.mex.c .
+
+src  := $(wildcard *.mex.c)
+msrc := $(wildcard *.m)
+stem := $(notdir $(basename $(basename $(src))))
+tgt  := $(addprefix ./, $(addsuffix .$(MEX_SUFFIX),$(stem)))
+
+%.$(MEX_SUFFIX) : %.mex.c
+        mex -I. $(MEX_CFLAGS) $< -output $*
+
+.PHONY: all
+all: $(tgt)
+
+.PHONY: info
+info :
+        @echo src  = $(src)
+        @echo stem = $(stem)
+        @echo tgt  = $(tgt)
+
+# PDF documentation
+.PHONY: doc
+doc: mser.html doc/mser.pdf
+
+mser.html : $(msrc)
+        mdoc --output=mser.html . \
+             --exclude='.*(_demo|_compile).*.m'
+
+.PHONY: clean
+clean:
+        rm -f $(tgt)
+        find . -name '.DS_Store' -exec rm -f \{\} \;
+        find . -name '.gdb_history' -exec rm -f \{\} \;
+        find . -name '*~' -exec rm -f \{\} \;
+        find . -name '*.bak' -exec rm -f \{\} \;
+        make -C doc/figures clean
+
+.PHONY: distclean
+distclean: clean
+        rm -f *.mexmac *.mexglx
+        rm -f mser.html
+        rm -f mser-*.tar.gz
+        rm -f doc/*.log
+        rm -f doc/*.aux
+        rm -f doc/*.toc
+        rm -f doc/*.bbl
+        rm -f doc/*.blg
+        rm -f doc/*.out
+        rm -f $(DIST).tar.gz
+        rm -f $(BINDIST).tar.gz
+        rm -rf $(BINDIST)
+
+.PHONY: dist
+dist: distclean
+        echo Version $(VER) >TIMESTAMP
+        echo Archive created on `date` >>TIMESTAMP
+        d=$(notdir $(CURDIR)) ; \
+        tar chzvf $(DIST).tar.gz \
+          --exclude mser_demo4.m \
+          --exclude data/seq.avi \
+          --exclude results \
+          ../$${d}
+
+.PHONY: bindist
+bindist: all
+        test -e $(BINDIST) || mkdir $(BINDIST)
+        cp *.$(MEX_SUFFIX) $(BINDIST)
+        cd $(BINDIST) ; strip -S *.$(MEX_SUFFIX)
+        tar chzvf $(BINDIST).tar.gz $(BINDIST)
+
+.PHONY: autorights
+autorights:
+        autorights . \
+          --verbose \
+          --recursive \
+          --template cal \
+          --years 2006 \
+          --authors "Andrea Vedaldi (UCLA VisionLab)" \
+          --program "Video Extremal Regions"
+
+doc/mser.pdf : doc/*.tex doc/*.bib doc/figures/*.fig
+        make -C doc/figures all
+        cd doc ; \
+        for k in 1 2 3 ; \
+        do \
+          pdflatex -file-line-error-style -interaction batchmode \
+            mser.tex ; \
+          if test "$$k" = '1' ; \
+          then \
+            bibtex mser.aux ; \
+          fi ; \
+        done
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/TIMESTAMP b/SD-VBS/benchmarks/mser/src/matlab/old/TIMESTAMP
new file mode 100755
index 0000000..1de1720
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/TIMESTAMP
@@ -0,0 +1,2 @@
+Version 0.4
+Archive created on Wed Feb 7 11:08:47 PST 2007
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/erfill.m b/SD-VBS/benchmarks/mser/src/matlab/old/erfill.m
new file mode 100755
index 0000000..6e11fc6
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/erfill.m
@@ -0,0 +1,13 @@
+% ERFILL  Fill extremal region
+%  MEMBERS=ERFILL(I,ER) returns the list MEMBERS of the pixels which
+%  belongs to the extremal region represented by the pixel ER.
+% 
+%  The selected region is the one that contains pixel ER and of
+%  inensity I(ER).
+%
+%  I must be of class UINT8 and ER must be a (scalar) index of the
+%  region representative point.
+%
+%  See also MSER().
+
+
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mex.c b/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mex.c
new file mode 100755
index 0000000..893d346
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mex.c
@@ -0,0 +1,223 @@
+/* file:        erfill.mex.c
+** description: Extremal Regions filling
+** author:      Andrea Vedaldi
+**/
+
+/* AUTORIGHTS
+Copyright (C) 2006 Regents of the University of California
+All rights reserved
+
+Written by Andrea Vedaldi (UCLA VisionLab).
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met
+
+    * Redistributions of source code must retain the above copyright
+      notice, this list of conditions and the following disclaimer.
+    * Redistributions in binary form must reproduce the above copyright
+      notice, this list of conditions and the following disclaimer in the
+      documentation and/or other materials provided with the distribution.
+    * Neither the name of the University of California, Berkeley nor the
+      names of its contributors may be used to endorse or promote products
+      derived from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
+DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+*/
+
+/** @file
+ ** @brief Maximally Stable Extremal Regions - MEX implementation
+ **/
+
+#include<mexutils.c>
+#include<stdio.h>
+#include<stdlib.h>
+#include<math.h>
+#include<string.h>
+#include<assert.h>
+
+#define MIN(x,y) (((x)<(y))?(x):(y))
+#define MAX(x,y) (((x)>(y))?(x):(y))
+
+typedef char unsigned val_t ;
+typedef int  unsigned idx_t ;
+typedef long long int unsigned acc_t ;
+
+/* advance N-dimensional subscript */
+void
+adv(int const* dims, int ndims, int* subs_pt)
+{
+  int d = 0 ;
+  while(d < ndims) {
+    if( ++subs_pt[d]  < dims[d] ) return ;
+    subs_pt[d++] = 0 ;
+  }
+}
+
+/* driver */
+void
+mexFunction(int nout, mxArray *out[], 
+            int nin, const mxArray *in[])
+{
+
+  enum {IN_I=0, IN_ER} ;
+  enum {OUT_MEMBERS} ;
+
+  idx_t i ;
+  int k, nel, ndims ; 
+  int const * dims ;
+  val_t const * I_pt ;
+  int last = 0 ;
+  int last_expanded = 0 ;
+  val_t value = 0 ;
+
+  double const * er_pt ;
+
+  int*   subs_pt ;       /* N-dimensional subscript                 */
+  int*   nsubs_pt ;      /* diff-subscript to point to neigh.       */
+  idx_t* strides_pt ;    /* strides to move in image array          */
+  val_t* visited_pt ;    /* flag                                    */
+  idx_t* members_pt ;    /* region members                          */
+
+  /** -----------------------------------------------------------------
+   **                                               Check the arguments
+   ** -------------------------------------------------------------- */
+  if (nin != 2) {
+    mexErrMsgTxt("Two arguments required.") ;
+  } else if (nout > 4) {
+    mexErrMsgTxt("Too many output arguments.");
+  }
+  
+  if(mxGetClassID(in[IN_I]) != mxUINT8_CLASS) {
+    mexErrMsgTxt("I must be of class UINT8.") ;
+  }
+
+  if(!uIsRealScalar(in[IN_ER])) {
+    mexErrMsgTxt("ER must be a DOUBLE scalar.") ;
+  }
+
+  /* get dimensions */
+  nel   = mxGetNumberOfElements(in[IN_I]) ;
+  ndims = mxGetNumberOfDimensions(in[IN_I]) ;
+  dims  = mxGetDimensions(in[IN_I]) ;
+  I_pt  = mxGetData(in[IN_I]) ;
+
+  /* allocate stuff */
+  subs_pt    = mxMalloc( sizeof(int)      * ndims ) ;
+  nsubs_pt   = mxMalloc( sizeof(int)      * ndims ) ;
+  strides_pt = mxMalloc( sizeof(idx_t)    * ndims ) ;
+  visited_pt = mxMalloc( sizeof(val_t)    * nel   ) ;
+  members_pt = mxMalloc( sizeof(idx_t)    * nel   ) ;
+
+  er_pt = mxGetPr(in[IN_ER]) ;
+  
+  /* compute strides to move into the N-dimensional image array */
+  strides_pt [0] = 1 ;
+  for(k = 1 ; k < ndims ; ++k) {
+    strides_pt [k] = strides_pt [k-1] * dims [k-1] ;
+  }
+  
+  /* load first pixel */
+  memset(visited_pt, 0, sizeof(val_t) * nel) ;
+  {
+    idx_t idx = (idx_t) *er_pt ;
+    if( idx < 1 || idx > nel ) {
+      char buff[80] ;
+      snprintf(buff,80,"ER=%d out of range [1,%d]",idx,nel) ;    
+      mexErrMsgTxt(buff) ;
+    }
+    members_pt [last++] = idx - 1 ;
+  }
+  value = I_pt[ members_pt[0] ]  ;
+
+  /* -----------------------------------------------------------------
+   *                                                       Fill region
+   * -------------------------------------------------------------- */
+  while(last_expanded < last) {
+    
+    /* pop next node xi */
+    idx_t index = members_pt[last_expanded++] ;
+    
+    /* convert index into a subscript sub; also initialize nsubs 
+       to (-1,-1,...,-1) */
+    {
+      idx_t temp = index ;
+      for(k = ndims-1 ; k >=0 ; --k) {
+        nsubs_pt [k] = -1 ;
+        subs_pt  [k] = temp / strides_pt [k] ;
+        temp         = temp % strides_pt [k] ;
+      }
+    }
+    
+    /* process neighbors of xi */
+    while( true ) {
+      int good = true ;
+      idx_t nindex = 0 ;
+      
+      /* compute NSUBS+SUB, the correspoinding neighbor index NINDEX
+         and check that the pixel is within image boundaries. */
+      for(k = 0 ; k < ndims && good ; ++k) {
+        int temp = nsubs_pt [k] + subs_pt [k] ;
+        good &= 0 <= temp && temp < dims[k] ;
+        nindex += temp * strides_pt [k] ;
+      }      
+      
+      /* process neighbor
+         1 - the pixel is within image boundaries;
+         2 - the pixel is indeed different from the current node
+         (this happens when nsub=(0,0,...,0));
+         3 - the pixel has value not greather than val
+         is a pixel older than xi
+         4 - the pixel has not been visited yet
+      */
+      if(good 
+         && nindex != index 
+         && I_pt [nindex] <= value
+         && ! visited_pt [nindex] ) {
+        
+        /* mark as visited */
+        visited_pt [nindex] = 1 ;
+        
+        /* add to list */
+        members_pt [last++] = nindex ;
+      }
+      
+      /* move to next neighbor */      
+      k = 0 ;
+      while(++ nsubs_pt [k] > 1) {
+        nsubs_pt [k++] = -1 ;
+        if(k == ndims) goto done_all_neighbors ;
+      }
+    } /* next neighbor */
+  done_all_neighbors : ;
+  } /* goto pop next member */
+
+  /*
+   * Save results
+   */
+  {
+    int dims[2] ;
+    int unsigned * pt ;
+    dims[0] = last ;
+    out[OUT_MEMBERS] = mxCreateNumericArray(1,dims,mxUINT32_CLASS,mxREAL);
+    pt = mxGetData(out[OUT_MEMBERS]) ;
+    for (i = 0 ; i < last ; ++i) {
+      *pt++ = members_pt[i] + 1 ;
+    }
+  }
+  
+  /* free stuff */
+  mxFree( members_pt ) ;
+  mxFree( visited_pt ) ;
+  mxFree( strides_pt ) ;
+  mxFree( nsubs_pt   ) ;
+  mxFree( subs_pt    ) ;
+}
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mexa64 b/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mexa64
new file mode 100755
index 0000000..679e972
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/erfill.mexa64
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mexutils.c b/SD-VBS/benchmarks/mser/src/matlab/old/mexutils.c
new file mode 100755
index 0000000..0fc664b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/mexutils.c
@@ -0,0 +1,111 @@
+/* file:        mexutils.c 
+** author:      Andrea Vedaldi
+** description: Utility functions to write MEX files.
+**/
+
+#include"mex.h"
+
+#undef M_PI
+#define M_PI 3.14159265358979
+
+/** @brief Is scalar?
+ **
+ ** @return @c true if the array @a A is a scalar.
+ **/
+int
+uIsScalar(const mxArray* A)
+{
+  return 
+    !mxIsComplex(A) &&
+    mxGetNumberOfDimensions(A) == 2 &&
+    mxGetM(A) == 1 &&
+    mxGetN(A) == 1 ;
+}
+
+/** @brief Is real scalar?
+ **
+ ** @return @c true if the array @a A is a real scalar.
+ **/
+int
+uIsRealScalar(const mxArray* A)
+{
+  return 
+    mxIsDouble(A) && 
+    !mxIsComplex(A) &&
+    mxGetNumberOfDimensions(A) == 2 &&
+    mxGetM(A) == 1 &&
+    mxGetN(A) == 1 ;
+}
+
+/** @brief Is real matrix?
+ **
+ ** The function checks wether the argument @a A is a real matrix.  In
+ ** addition, if @a M >= 0, it checks wether the number of rows is
+ ** equal to @a M and, if @a N >= 0, if the number of columns is equal
+ ** to @a N.
+ **
+ ** @param M number of rows.
+ ** @param N number of columns.
+ ** @return @c true if the array is a real matrix with the specified format.
+ **/
+int
+uIsRealMatrix(const mxArray* A, int M, int N)
+{
+  return  
+    mxIsDouble(A) &&
+    !mxIsComplex(A) &&
+    mxGetNumberOfDimensions(A) == 2 &&
+    ((M>=0)?(mxGetM(A) == M):1) &&
+    ((N>=0)?(mxGetN(A) == N):1) ;   
+}
+
+/** @brief Is real vector?
+ **
+ ** The function checks wether the argument  @a V is a real vector. By
+ ** definiton, a  matrix is a vector  if one of its  dimension is one.
+ ** In addition, if  @a D >= 0, it checks wether  the dimension of the
+ ** vecotr is equal to @a D.
+ **
+ ** @param D lenght of the vector.
+ ** @return @c true if the array is a real vector of the specified dimension.
+ **/
+int
+uIsRealVector(const mxArray* V, int D) 
+{
+  int M = mxGetM(V) ;
+  int N = mxGetN(V) ;
+  int is_vector = (N == 1) || (M == 1) ;
+  
+  return   
+    mxIsDouble(V) &&
+    !mxIsComplex(V) &&
+    mxGetNumberOfDimensions(V) == 2 &&
+    is_vector &&
+    ( D < 0 || N == D || M == D) ;
+}
+
+
+/** @brief Is a string?
+ **
+ ** The function checks wether the array @a S is a string. If
+ ** @a L is non-negative, it also check wether the strign has
+ ** length @a L.
+ **
+ ** @return @a c true if S is a string of the specified length.
+ **/
+int
+uIsString(const mxArray* S, int L)
+{
+  int M = mxGetM(S) ;
+  int N = mxGetN(S) ;
+
+  return 
+    mxIsChar(S) &&
+    M == 1 &&
+    (L < 0 || N == L) ;
+}
+
+/**
+ **
+ **/
+
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mser.mex.c b/SD-VBS/benchmarks/mser/src/matlab/old/mser.mex.c
new file mode 100755
index 0000000..48c788e
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/mser.mex.c
@@ -0,0 +1,809 @@
+/* file:        mser.mex.c
+** description: Maximally Stable Extremal Regions
+** author:      Andrea Vedaldi
+**/
+
+/* AUTORIGHTS
+Copyright (C) 2006 Regents of the University of California
+All rights reserved
+
+Written by Andrea Vedaldi (UCLA VisionLab).
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met
+
+    * Redistributions of source code must retain the above copyright
+      notice, this list of conditions and the following disclaimer.
+    * Redistributions in binary form must reproduce the above copyright
+      notice, this list of conditions and the following disclaimer in the
+      documentation and/or other materials provided with the distribution.
+    * Neither the name of the University of California, Berkeley nor the
+      names of its contributors may be used to endorse or promote products
+      derived from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
+DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+*/
+
+/** @file
+ ** @brief Maximally Stable Extremal Regions - MEX implementation
+ **/
+
+#include<mexutils.c>
+#include<stdio.h>
+#include<stdlib.h>
+#include<math.h>
+#include<string.h>
+#include<assert.h>
+
+#define MIN(x,y) (((x)<(y))?(x):(y))
+#define MAX(x,y) (((x)>(y))?(x):(y))
+
+#define USE_BUCKET_SORT
+/*#define USE_RANK_UNION
+*/
+
+typedef char unsigned val_t ;
+typedef int  unsigned idx_t ;
+typedef long long int unsigned acc_t ;
+
+/* pairs are used to sort the pixels */
+typedef struct 
+{
+  val_t value ; 
+  idx_t  index ;
+} pair_t ;
+
+/* forest node */
+typedef struct
+{
+  idx_t parent ;   /**< parent pixel         */
+  idx_t shortcut ; /**< shortcut to the root */
+  idx_t region ;   /**< index of the region  */
+  int   area ;     /**< area of the region   */
+#ifdef USE_RANK_UNION
+  int   height ;    /**< node height         */
+#endif
+} node_t ;
+
+/* extremal regions */
+typedef struct
+{
+  idx_t parent ;     /**< parent region                           */
+  idx_t index ;      /**< index of root pixel                     */
+  val_t value ;      /**< value of root pixel                     */
+  int   area ;       /**< area of the region                      */
+  int   area_top ;   /**< area of the region DELTA levels above   */
+  int   area_bot  ;  /**< area of the region DELTA levels below   */
+  float variation ;  /**< variation                               */
+  int   maxstable ;  /**< max stable number (=0 if not maxstable) */
+} region_t ;
+
+/* predicate used to sort pixels by increasing intensity */
+int 
+cmp_pair(void const* a, void const* b) 
+{
+  pair_t* pa = (pair_t*) a;
+  pair_t* pb = (pair_t*) b;
+  return pa->value - pb->value ;
+}
+
+/* advance N-dimensional subscript */
+void
+adv(int const* dims, int ndims, int* subs_pt)
+{
+  int d = 0 ;
+  while(d < ndims) {
+    if( ++subs_pt[d]  < dims[d] ) return ;
+    subs_pt[d++] = 0 ;
+  }
+}
+
+/* driver */
+void
+mexFunction(int nout, mxArray *out[], 
+            int nin, const mxArray *in[])
+{
+  enum {IN_I=0, IN_DELTA} ;
+  enum {OUT_REGIONS=0, OUT_ELL, OUT_PARENTS, OUT_AREA} ;
+
+  idx_t i ;
+  idx_t rindex = 0 ;
+  int k ; 
+
+  /* configuration */
+  int verbose = 1 ;      /* be verbose                              */
+  int small_cleanup= 1 ; /* remove very small regions               */
+  int big_cleanup  = 1 ; /* remove very big regions                 */
+  int bad_cleanup  = 0 ; /* remove very bad regions                 */
+  int dup_cleanup  = 1 ; /* remove duplicates                       */
+  val_t delta ;          /* stability delta                         */
+
+  /* node value denoting a void node */
+  idx_t const node_is_void = 0xffffffff ;
+
+  int*   subs_pt ;       /* N-dimensional subscript                 */
+  int*   nsubs_pt ;      /* diff-subscript to point to neigh.       */
+  idx_t* strides_pt ;    /* strides to move in image array          */
+  idx_t* visited_pt ;    /* flag                                    */
+
+  int nel ;              /* number of image elements (pixels)       */
+  int ner = 0 ;          /* number of extremal regions              */
+  int nmer = 0 ;         /* number of maximally stable              */
+  int ndims ;            /* number of dimensions                    */
+  int const* dims ;      /* dimensions                              */
+  int njoins = 0 ;       /* number of join ops                      */
+
+  val_t const* I_pt ;    /* source image                            */
+  pair_t*   pairs_pt ;   /* scratch buffer to sort pixels           */
+  node_t*   forest_pt ;  /* the extremal regions forest             */
+  region_t* regions_pt ; /* list of extremal regions found          */ 
+
+  /* ellipses fitting */
+  acc_t* acc_pt ;        /* accumulator to integrate region moments */
+  acc_t* ell_pt ;        /* ellipses parameters                     */
+  int    gdl ;           /* number of parameters of an ellipse      */
+  idx_t* joins_pt ;      /* sequence of joins                       */
+  
+  /** -----------------------------------------------------------------
+   **                                               Check the arguments
+   ** -------------------------------------------------------------- */
+  if (nin != 2) {
+    mexErrMsgTxt("Two arguments required.") ;
+  } else if (nout > 4) {
+    mexErrMsgTxt("Too many output arguments.");
+  }
+  
+  if(mxGetClassID(in[IN_I]) != mxUINT8_CLASS) {
+    mexErrMsgTxt("I must be of class UINT8") ;
+  }
+
+  if(!uIsScalar(in[IN_DELTA])) {
+    mexErrMsgTxt("DELTA must be scalar") ;
+  }
+
+  delta = 0 ;
+  switch(mxGetClassID(in[IN_DELTA])) {
+  case mxUINT8_CLASS :
+    delta = * (val_t*) mxGetData(in[IN_DELTA]) ;
+    break ;
+    
+  case mxDOUBLE_CLASS :
+    {
+      double x = *mxGetPr(in[IN_DELTA])  ;
+      if(x < 0.0) {
+        mexErrMsgTxt("DELTA must be non-negative") ;
+      }
+      delta = (val_t) x ;      
+    }
+    break ;
+    
+  default :
+    mexErrMsgTxt("DELTA must be of class DOUBLE or UINT8") ;
+  }
+
+  /* get dimensions */
+  nel   = mxGetNumberOfElements(in[IN_I]) ;
+  ndims = mxGetNumberOfDimensions(in[IN_I]) ;
+  dims  = mxGetDimensions(in[IN_I]) ;
+  I_pt  = mxGetData(in[IN_I]) ;
+
+  /* allocate stuff */
+  subs_pt    = mxMalloc( sizeof(int)      * ndims ) ;
+  nsubs_pt   = mxMalloc( sizeof(int)      * ndims ) ;
+  strides_pt = mxMalloc( sizeof(idx_t)    * ndims ) ;
+  visited_pt = mxMalloc( sizeof(idx_t)    * nel   ) ;
+  regions_pt = mxMalloc( sizeof(region_t) * nel   ) ;
+  pairs_pt   = mxMalloc( sizeof(pair_t)   * nel   ) ;
+  forest_pt  = mxMalloc( sizeof(node_t)   * nel   ) ;
+  joins_pt   = mxMalloc( sizeof(idx_t)    * nel   ) ;
+  
+  /* compute strides to move into the N-dimensional image array */
+  strides_pt [0] = 1 ;
+  for(k = 1 ; k < ndims ; ++k) {
+    strides_pt [k] = strides_pt [k-1] * dims [k-1] ;
+  }
+
+  /* sort pixels by increasing intensity*/
+  verbose && mexPrintf("Sorting pixels ... ") ;
+
+#ifndef USE_BUCKETSORT
+  for(i = 0 ; i < nel ; ++i) {
+    pairs_pt [i].value = I_pt [i] ;
+    pairs_pt [i].index = i ;
+  }
+  qsort(pairs_pt, nel, sizeof(pair_t), cmp_pair) ;
+#else
+  {
+    int unsigned buckets [256] ;
+    memset(buckets, 0, sizeof(int unsigned)*256) ;
+    for(i = 0 ; i < nel ; ++i) {
+      val_t v = I_pt [i] ;
+      ++ buckets[v] ;
+    }
+    for(i = 1 ; i < 256 ; ++i) {
+      buckets[i] += buckets[i-1] ;
+    }
+    for(i = nel ; i >= 1 ; ) {
+      val_t v = I_pt [--i] ;
+      idx_t j = -- buckets [v] ;
+      pairs_pt [j].value = v ;
+      pairs_pt [j].index = i ;
+    }
+  }
+#endif
+  verbose && mexPrintf("done\n") ;
+
+  /* initialize the forest with all void nodes */
+  for(i = 0 ; i < nel ; ++i) {
+    forest_pt [i].parent = node_is_void  ;
+  }
+  
+  /* number of ellipse free parameters */
+  gdl = ndims*(ndims+1)/2 + ndims ;
+
+  /* -----------------------------------------------------------------
+   *                                     Compute extremal regions tree
+   * -------------------------------------------------------------- */
+  verbose && mexPrintf("Computing extremal regions ... ") ;
+  for(i = 0 ; i < nel ; ++i) {
+    
+    /* pop next node xi */
+    idx_t index = pairs_pt [i].index ;    
+    val_t value = pairs_pt [i].value ;
+
+    /* this will be needed later */
+    rindex = index ;
+    
+    /* push it into the tree */
+    forest_pt [index] .parent   = index ;
+    forest_pt [index] .shortcut = index ;
+    forest_pt [index] .area     = 1 ;
+#ifdef USE_RANK_UNION
+    forest_pt [index] .height   = 1 ;
+#endif
+    
+    /* convert index into a subscript sub; also initialize nsubs 
+       to (-1,-1,...,-1) */
+    {
+      idx_t temp = index ;
+      for(k = ndims-1 ; k >=0 ; --k) {
+        nsubs_pt [k] = -1 ;
+        subs_pt  [k] = temp / strides_pt [k] ;
+        temp         = temp % strides_pt [k] ;
+      }
+    }
+    
+    /* process neighbors of xi */
+    while( true ) {
+      int good = true ;
+      idx_t nindex = 0 ;
+      
+      /* compute NSUBS+SUB, the correspoinding neighbor index NINDEX
+         and check that the pixel is within image boundaries. */
+      for(k = 0 ; k < ndims && good ; ++k) {
+        int temp = nsubs_pt [k] + subs_pt [k] ;
+        good &= 0 <= temp && temp < dims[k] ;
+        nindex += temp * strides_pt [k] ;
+      }      
+      
+      /* keep going only if
+         1 - the neighbor is within image boundaries;
+         2 - the neighbor is indeed different from the current node
+             (this happens when nsub=(0,0,...,0));
+         3 - the nieghbor is already in the tree, meaning that
+             is a pixel older than xi.
+      */
+      if(good && 
+         nindex != index &&
+         forest_pt[nindex].parent != node_is_void ) {
+        
+        idx_t nrindex = 0, nvisited ;
+        val_t nrvalue = 0 ;
+
+#ifdef USE_RANK_UNION
+        int height  = forest_pt [ rindex] .height ;
+        int nheight = forest_pt [nrindex] .height ;
+#endif
+        
+        /* RINDEX = ROOT(INDEX) might change as we merge trees, so we
+           need to update it after each merge */
+        
+        /* find the root of the current node */
+        /* also update the shortcuts */
+        nvisited = 0 ;
+        while( forest_pt[rindex].shortcut != rindex ) {          
+          visited_pt[ nvisited++ ] = rindex ;
+          rindex = forest_pt[rindex].shortcut ;
+        }      
+        while( nvisited-- ) {
+          forest_pt [ visited_pt[nvisited] ] .shortcut = rindex ;
+        }
+        
+        /* find the root of the neighbor */
+        nrindex  = nindex ;
+        nvisited = 0 ;
+        while( forest_pt[nrindex].shortcut != nrindex ) {          
+          visited_pt[ nvisited++ ] = nrindex ;
+          nrindex = forest_pt[nrindex].shortcut ;
+        }      
+        while( nvisited-- ) {
+          forest_pt [ visited_pt[nvisited] ] .shortcut = nrindex ;
+        }
+        
+        /*
+          Now we join the two subtrees rooted at
+          
+            RINDEX = ROOT(INDEX) and NRINDEX = ROOT(NINDEX).
+          
+          Only three things can happen:
+          
+          a - ROOT(INDEX) == ROOT(NRINDEX). In this case the two trees
+              have already been joined and we do not do anything.
+          
+          b - I(ROOT(INDEX)) == I(ROOT(NRINDEX)). In this case index
+              is extending an extremal region with the same
+              value. Since ROOT(NRINDEX) will NOT be an extremal
+              region of the full image, ROOT(INDEX) can be safely
+              addedd as children of ROOT(NRINDEX) if this reduces
+              the height according to union rank.
+               
+          c - I(ROOT(INDEX)) > I(ROOT(NRINDEX)) as index is extending
+              an extremal region, but increasing its level. In this
+              case ROOT(NRINDEX) WILL be an extremal region of the
+              final image and the only possibility is to add
+              ROOT(NRINDEX) as children of ROOT(INDEX).
+        */
+
+        if( rindex != nrindex ) {
+          /* this is a genuine join */
+          
+          nrvalue = I_pt [nrindex] ;
+          if( nrvalue == value 
+#ifdef USE_RANK_UNION             
+              && height < nheight
+#endif
+              ) {
+            /* ROOT(INDEX) becomes the child */
+            forest_pt[rindex] .parent   = nrindex ;
+            forest_pt[rindex] .shortcut = nrindex ;          
+            forest_pt[nrindex].area    += forest_pt[rindex].area ;
+
+#ifdef USE_RANK_UNION
+            forest_pt[nrindex].height = MAX(nheight, height+1) ;
+#endif
+
+            joins_pt[njoins++] = rindex ;
+
+          } else {
+            /* ROOT(index) becomes parent */
+            forest_pt[nrindex] .parent   = rindex ;
+            forest_pt[nrindex] .shortcut = rindex ;
+            forest_pt[rindex]  .area    += forest_pt[nrindex].area ;
+
+#ifdef USE_RANK_UNION
+            forest_pt[rindex].height = MAX(height, nheight+1) ;
+#endif
+            if( nrvalue != value ) {            
+              /* nrindex is extremal region: save for later */
+              forest_pt[nrindex].region = ner ;
+              regions_pt [ner] .index      = nrindex ;
+              regions_pt [ner] .parent     = ner ;
+              regions_pt [ner] .value      = nrvalue ;
+              regions_pt [ner] .area       = forest_pt [nrindex].area ;
+              regions_pt [ner] .area_top   = nel ;
+              regions_pt [ner] .area_bot   = 0 ;            
+              ++ner ;
+/*                printf("ner = %d\n", ner);*/
+            }
+            
+            /* annote join operation for post-processing */
+            joins_pt[njoins++] = nrindex ;
+          }
+        }
+        
+      } /* neighbor done */
+      
+      /* move to next neighbor */      
+      k = 0 ;
+      while(++ nsubs_pt [k] > 1) {
+        nsubs_pt [k++] = -1 ;
+        if(k == ndims) goto done_all_neighbors ;
+      }
+    } /* next neighbor */
+  done_all_neighbors : ;
+  } /* next pixel */    
+    
+  /* the root of the last processed pixel must be a region */
+  forest_pt [rindex].region = ner ;
+  regions_pt [ner] .index      = rindex ;
+  regions_pt [ner] .parent     = ner ;
+  regions_pt [ner] .value      = I_pt      [rindex] ;
+  regions_pt [ner] .area       = forest_pt [rindex] .area ;
+  regions_pt [ner] .area_top   = nel ;
+  regions_pt [ner] .area_bot   = 0 ;            
+  ++ner ;
+
+  verbose && mexPrintf("done\nExtremal regions: %d\n", ner) ;
+  
+  /* -----------------------------------------------------------------
+   *                                            Compute region parents
+   * -------------------------------------------------------------- */
+  for( i = 0 ; i < ner ; ++i) {
+    idx_t index  = regions_pt [i].index ;    
+    val_t value  = regions_pt [i].value ;
+    idx_t j      = i ;
+
+    while(j == i) {
+      idx_t pindex = forest_pt [index].parent ;
+      val_t pvalue = I_pt [pindex] ;
+
+      /* top of the tree */
+      if(index == pindex) {
+        j = forest_pt[index].region ;
+        break ;
+      }
+
+      /* if index is the root of a region, either this is still
+         i, or it is the parent region we are looking for. */
+      if(value < pvalue) {
+        j = forest_pt[index].region ;
+      }
+
+      index = pindex ;
+      value = pvalue ;
+    }
+    regions_pt[i]. parent = j ;
+  }
+  
+  /* -----------------------------------------------------------------
+   *                                 Compute areas of tops and bottoms
+   * -------------------------------------------------------------- */
+
+  /* We scan the list of regions from the bottom. Let x0 be the current
+     region and be x1 = PARENT(x0), x2 = PARENT(x1) and so on.
+     
+     Here we do two things:
+     
+     1) Look for regions x for which x0 is the BOTTOM. This requires
+        VAL(x0) <= VAL(x) - DELTA < VAL(x1).
+        We update AREA_BOT(x) for each of such x found.
+        
+     2) Look for the region y which is the TOP of x0. This requires
+          VAL(y) <= VAL(x0) + DELTA < VAL(y+1)
+          We update AREA_TOP(x0) as soon as we find such y.
+        
+  */
+
+  for( i = 0 ; i < ner ; ++i) {
+    /* fix xi as the region, then xj are the parents */
+    idx_t parent = regions_pt [i].parent ;
+    int   val0   = regions_pt [i].value ;
+    int   val1   = regions_pt [parent].value ;
+    int   val    = val0 ;
+    idx_t j = i ;
+
+    while(true) {
+      int valp = regions_pt [parent].value ;
+
+      /* i is the bottom of j */
+      if(val0 <= val - delta && val - delta < val1) {
+        regions_pt [j].area_bot  =
+          MAX(regions_pt [j].area_bot, regions_pt [i].area) ;
+      }
+      
+      /* j is the top of i */
+      if(val <= val0 + delta && val0 + delta < valp) {
+        regions_pt [i].area_top = regions_pt [j].area ;
+      }
+      
+      /* stop if going on is useless */
+      if(val1 <= val - delta && val0 + delta < val)
+        break ;
+
+      /* stop also if j is the root */
+      if(j == parent)
+        break ;
+      
+      /* next region upward */
+      j      = parent ;
+      parent = regions_pt [j].parent ;
+      val    = valp ;
+    }
+  }
+
+  /* -----------------------------------------------------------------
+   *                                                 Compute variation
+   * -------------------------------------------------------------- */
+  for(i = 0 ; i < ner ; ++i) {
+    int area     = regions_pt [i].area ;
+    int area_top = regions_pt [i].area_top ;
+    int area_bot = regions_pt [i].area_bot ;    
+    regions_pt [i].variation = 
+      (float)(area_top - area_bot) / (float)area ;
+
+    /* initialize .mastable to 1 for all nodes */
+    regions_pt [i].maxstable = 1 ;
+  }
+
+  /* -----------------------------------------------------------------
+   *                     Remove regions which are NOT maximally stable
+   * -------------------------------------------------------------- */
+  nmer = ner ;
+  for(i = 0 ; i < ner ; ++i) {
+    idx_t parent = regions_pt [i]      .parent ;
+    float var    = regions_pt [i]      .variation ;
+    float pvar   = regions_pt [parent] .variation ;
+    idx_t loser ;
+
+    /* decide which one to keep and put that in loser */
+    if(var < pvar) loser = parent ; else loser = i ;
+    
+    /* make loser NON maximally stable */
+    if(regions_pt [loser].maxstable) --nmer ;
+    regions_pt [loser].maxstable = 0 ;
+  }
+
+  verbose && mexPrintf("Maximally stable regions: %d (%.1f%%)\n", 
+                       nmer, 100.0 * (double) nmer / ner) ;
+
+  /* -----------------------------------------------------------------
+   *                                               Remove more regions
+   * -------------------------------------------------------------- */
+
+  /* it is critical for correct duplicate detection to remove regions
+     from the bottom (smallest one first) */
+
+  if( big_cleanup || small_cleanup || bad_cleanup || dup_cleanup ) {
+    int nbig   = 0 ;
+    int nsmall = 0 ;
+    int nbad   = 0 ;
+    int ndup   = 0 ;
+
+    /* scann all extremal regions */
+    for(i = 0 ; i < ner ; ++i) {
+      
+      /* process only maximally stable extremal regions */
+      if(! regions_pt [i].maxstable) continue ;
+      
+      if( bad_cleanup   && regions_pt[i].variation >= 1.0f  ) {
+        ++nbad ;
+        goto remove_this_region ;
+      }
+
+      if( big_cleanup   && regions_pt[i].area      >  nel/2 ) {
+        ++nbig ;
+        goto remove_this_region ;
+      }
+
+      if( small_cleanup && regions_pt[i].area      <  25    ) {
+        ++nsmall ;
+        goto remove_this_region ;
+      }
+      
+      /* 
+       * Remove duplicates 
+       */
+      if( dup_cleanup ) {
+        idx_t parent = regions_pt [i].parent ;
+        int area, parea ;
+        float change ;
+        
+        /* the search does not apply to root regions */
+        if(parent != i) {
+          
+          /* search for the maximally stable parent region */
+          while(! regions_pt[parent].maxstable) {
+            idx_t next = regions_pt[parent].parent ;
+            if(next == parent) break ;
+            parent = next ;
+          }
+          
+          /* compare with the parent region; if the current and parent
+             regions are too similar, keep only the parent */
+          area   = regions_pt [i].area ;
+          parea  = regions_pt [parent].area ;
+          change = (float)(parea - area)/area ;
+
+          if(change < 0.5)  {
+            ++ndup ;
+            goto remove_this_region ;
+          }
+
+        } /* drop duplicates */ 
+      }
+      continue ;
+    remove_this_region :
+      regions_pt[i].maxstable = false ;
+      --nmer ;      
+    } /* next region to cleanup */
+
+    if(verbose) {
+      mexPrintf("  Bad regions:        %d\n", nbad   ) ;
+      mexPrintf("  Small regions:      %d\n", nsmall ) ;
+      mexPrintf("  Big regions:        %d\n", nbig   ) ;
+      mexPrintf("  Duplicated regions: %d\n", ndup   ) ;
+    }
+  }
+
+  verbose && mexPrintf("Cleaned-up regions: %d (%.1f%%)\n", 
+                       nmer, 100.0 * (double) nmer / ner) ;
+
+  /* -----------------------------------------------------------------
+   *                                                      Fit ellipses
+   * -------------------------------------------------------------- */
+  ell_pt = 0 ;
+  if (nout >= 1) {
+    int midx = 1 ;
+    int d, index, j ;
+    
+    verbose && mexPrintf("Fitting ellipses...\n") ;
+
+    /* enumerate maxstable regions */
+    for(i = 0 ; i < ner ; ++i) {      
+      if(! regions_pt [i].maxstable) continue ;
+      regions_pt [i].maxstable = midx++ ;
+    }
+    
+    /* allocate space */
+    acc_pt = mxMalloc(sizeof(acc_t) * nel) ;
+    ell_pt = mxMalloc(sizeof(acc_t) * gdl * nmer) ; 
+    
+    /* clear accumulators */
+    memset(ell_pt, 0, sizeof(int) * gdl * nmer) ;
+    
+    /* for each gdl */
+    for(d = 0 ; d < gdl ; ++d) {
+      /* initalize parameter */
+      memset(subs_pt, 0, sizeof(int) * ndims) ;
+      
+      if(d < ndims) {
+        verbose && mexPrintf(" mean %d\n",d) ;
+        for(index = 0 ; index < nel ; ++ index) {
+          acc_pt[index] = subs_pt[d] ;
+          adv(dims, ndims, subs_pt) ;
+        }
+
+      } else {
+
+        /* decode d-ndims into a (i,j) pair */
+        i = d-ndims ; 
+        j = 0 ;
+        while(i > j) {
+          i -= j + 1 ;
+          j ++ ;
+        }
+
+        verbose && mexPrintf(" corr (%d,%d)\n",i,j) ;
+
+        /* add x_i * x_j */
+        for(index = 0 ; index < nel ; ++ index){
+          acc_pt[index] = subs_pt[i]*subs_pt[j] ;
+          adv(dims, ndims, subs_pt) ;
+        }
+      }
+
+      /* integrate parameter */
+      for(i = 0 ; i < njoins ; ++i) {      
+        idx_t index  = joins_pt[i] ;
+        idx_t parent = forest_pt [ index ].parent ;
+        acc_pt[parent] += acc_pt[index] ;
+      }
+    
+      /* save back to ellpises */
+      for(i = 0 ; i < ner ; ++i) {
+        idx_t region = regions_pt [i].maxstable ;
+
+        /* skip if not extremal region */
+        if(region-- == 0) continue ;
+        ell_pt [d + gdl*region] = acc_pt [ regions_pt[i].index ] ;
+      }
+
+      /* next gdl */
+    }
+    mxFree(acc_pt) ;
+  }
+  
+  /* -----------------------------------------------------------------
+   *                                                Save back and exit
+   * -------------------------------------------------------------- */
+
+  /*
+   * Save extremal regions
+   */
+  {
+    int dims[2] ;
+    int unsigned * pt ;
+    dims[0] = nmer ;
+    out[OUT_REGIONS] = mxCreateNumericArray(1,dims,mxUINT32_CLASS,mxREAL);
+    pt = mxGetData(out[OUT_REGIONS]) ;
+    for (i = 0 ; i < ner ; ++i) {
+      if( regions_pt[i].maxstable ) {
+        /* adjust for MATLAB index compatibility */
+        *pt++ = regions_pt[i].index + 1 ;
+      }
+    }
+  }
+  
+  /*
+   * Save fitted ellipses
+   */
+  if(nout >= 2) {
+    int dims[2], d, j, index ;
+    double * pt ;
+    dims[0] = gdl ;
+    dims[1] = nmer ;
+     
+    out[OUT_ELL] = mxCreateNumericArray(2,dims,mxDOUBLE_CLASS,mxREAL) ;
+    pt = mxGetData(out[OUT_ELL]) ;
+
+    for(index = 0 ; index < nel ; ++index) {
+
+      idx_t region = regions_pt [index] .maxstable ;      
+      int   N      = regions_pt [index] .area ;
+
+      if(region-- == 0) continue ;
+
+      for(d = 0  ; d  < gdl ; ++d) {
+
+        pt[d] = (double) ell_pt[gdl*region  + d] / N ;
+
+        if(d < ndims) {
+          /* adjust for MATLAB coordinate frame convention */
+          pt[d] += 1 ; 
+        } else {
+          /* remove squared mean from moment to get variance */
+          i = d - ndims ; 
+          j = 0 ;
+          while(i > j) {
+            i -= j + 1 ;
+            j ++ ;
+          }
+          pt[d] -= (pt[i]-1)*(pt[j]-1) ;
+        }
+      }
+      pt += gdl ;
+    }
+    mxFree(ell_pt) ;
+  }
+  
+  if(nout >= 3)  {
+    int unsigned * pt ;
+    out[OUT_PARENTS] = mxCreateNumericArray(ndims,dims,mxUINT32_CLASS,mxREAL) ;
+    pt = mxGetData(out[OUT_PARENTS]) ;
+    for(i = 0 ; i < nel ; ++i) {
+      *pt++ = forest_pt[i].parent ;
+    }
+  }
+
+  if(nout >= 4) {
+    int dims[2] ;
+    int unsigned * pt ;
+    dims[0] = 3 ;
+    dims[1]= ner ;
+    out[OUT_AREA] = mxCreateNumericArray(2,dims,mxUINT32_CLASS,mxREAL);
+    pt = mxGetData(out[OUT_AREA]) ;
+    for( i = 0 ; i < ner ; ++i ) {
+      *pt++ = regions_pt [i]. area_bot ;
+      *pt++ = regions_pt [i]. area ;
+      *pt++ = regions_pt [i]. area_top ;      
+    }
+  }
+
+  /* free stuff */
+  mxFree( forest_pt  ) ;
+  mxFree( pairs_pt   ) ;
+  mxFree( regions_pt ) ;
+  mxFree( visited_pt ) ;
+  mxFree( strides_pt ) ;
+  mxFree( nsubs_pt   ) ;
+  mxFree( subs_pt    ) ;
+}
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mser.mexa64 b/SD-VBS/benchmarks/mser/src/matlab/old/mser.mexa64
new file mode 100755
index 0000000..fb9fb0b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/mser.mexa64
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mser_compile.m b/SD-VBS/benchmarks/mser/src/matlab/old/mser_compile.m
new file mode 100755
index 0000000..5e3562b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/mser_compile.m
@@ -0,0 +1,7 @@
+function mser_compile(type)
+% MSER_COMPILE  Compile MEX files
+
+opts = { '-O', '-I.' } ;
+
+mex('mser.mex.c','-output', 'mser',opts{:}) ;
+mex('erfill.mex.c','-output', 'erfill',opts{:}) ;
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo2.m b/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo2.m
new file mode 100755
index 0000000..37a4ed1
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo2.m
@@ -0,0 +1,62 @@
+% MSER_DEMO2  Demonstrate MSER code
+
+% AUTORIGHTS
+% Copyright (C) 2006 Regents of the University of California
+% All rights reserved
+% 
+% Written by Andrea Vedaldi (UCLA VisionLab).
+% 
+% Redistribution and use in source and binary forms, with or without
+% modification, are permitted provided that the following conditions are met
+% 
+%     * Redistributions of source code must retain the above copyright
+%       notice, this list of conditions and the following disclaimer.
+%     * Redistributions in binary form must reproduce the above copyright
+%       notice, this list of conditions and the following disclaimer in the
+%       documentation and/or other materials provided with the distribution.
+%     * Neither the name of the University of California, Berkeley nor the
+%       names of its contributors may be used to endorse or promote products
+%       derived from this software without specific prior written permission.
+% 
+% THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+% EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+% WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+% DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
+% DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+% (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+% LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+% ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+% (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+% SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+I = load('clown') ; I = uint8(I.X) ;
+figure(1) ; imagesc(I) ; colormap gray; hold on ;
+
+[M,N] = size(I) ;
+i = double(i) ;
+j = double(j) ;
+
+[r,ell] = mser(I,5) ;
+
+r=double(r) ;
+
+[i,j]=ind2sub(size(I),r) ;                    
+plot(j,i,'r*') ;
+
+ell = ell([2 1 5 4 3],:) ;
+plotframe(ell); 
+
+figure(2) ; 
+
+clear MOV ;
+K = size(ell,2) ;
+for k=1:K
+  clf ;
+  sel = erfill(I,r(k)) ;
+  mask = zeros(M,N) ; mask(sel) =1 ;
+  imagesc(cat(3,I,255*uint8(mask),I)) ; colormap gray ; hold on ;
+  set(gca,'position',[0 0 1 1]) ; axis off ; axis equal ;
+  plot(j(k),i(k),'r*') ;
+  plotframe(ell(:,k),'color','r') ;
+  MOV(k) = getframe(gca) ;
+end
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo3.m b/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo3.m
new file mode 100755
index 0000000..4669437
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/mser_demo3.m
@@ -0,0 +1,117 @@
+% MSER_DEMO3  Demonstrates MSER on a volumetric image
+
+% AUTORIGHTS
+% Copyright (C) 2006 Regents of the University of California
+% All rights reserved
+% 
+% Written by Andrea Vedaldi (UCLA VisionLab).
+% 
+% Redistribution and use in source and binary forms, with or without
+% modification, are permitted provided that the following conditions are met
+% 
+%     * Redistributions of source code must retain the above copyright
+%       notice, this list of conditions and the following disclaimer.
+%     * Redistributions in binary form must reproduce the above copyright
+%       notice, this list of conditions and the following disclaimer in the
+%       documentation and/or other materials provided with the distribution.
+%     * Neither the name of the University of California, Berkeley nor the
+%       names of its contributors may be used to endorse or promote products
+%       derived from this software without specific prior written permission.
+% 
+% THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+% EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+% WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+% DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
+% DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+% (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+% LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+% ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+% (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+% SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+% --------------------------------------------------------------------
+%                                                          Create data
+% --------------------------------------------------------------------
+
+% volumetric coordinate (x,y,z)
+x       = linspace(-1,1,50) ;
+[x,y,z] = meshgrid(x,x,x) ;
+
+% create funny volumetric image
+I   = sin(4*x).*cos(4*y).*sin(z) ;
+I   = I-min(I(:)) ;
+I   = I/max(I(:)) ;
+
+% quantize the image in 10 levels
+lev = 10 ;
+I   = lev*I ;
+Ir  = round(I) ;
+
+% --------------------------------------------------------------------
+%                                                      Compute regions
+% --------------------------------------------------------------------
+[idx,ell,p] = mser(uint8(Ir),1);
+
+% --------------------------------------------------------------------
+%                                                                Plots
+% --------------------------------------------------------------------
+
+% The image is quantized; store in LEV its range.
+lev = unique(Ir(idx)) ;
+
+figure(100); clf;
+K=min(length(lev),4) ;
+
+r=.99 ;
+
+% one level per time
+for k=1:K
+  tightsubplot(K,k) ;
+  [i,j,m] = ind2sub(size(I), idx(Ir(idx)==lev(k)) ) ;
+  
+  % compute level set of level LEV(k)
+  Is = double(Ir<=lev(k)) ;
+    
+  p1 = patch(isosurface(Is,r), ...
+             'FaceColor','blue','EdgeColor','none') ;
+  p2 = patch(isocaps(Is,r),...
+             'FaceColor','interp','EdgeColor','none') ;  
+  isonormals(I,p1)
+  hold on ;
+  
+  view(3); axis vis3d tight
+  camlight; lighting phong ;
+  
+  % find regions that have this level
+  sel = find( Ir(idx) == lev(k) ) ;
+  
+  % plot fitted ellipsoid
+  for r=sel'
+    E = ell(:,r) ;
+    c = E(1:3) ;
+    A = zeros(3) ;
+    A(1,1) = E(4) ;
+    A(1,2) = E(5) ;
+    A(2,2) = E(6) ;
+    A(1,3) = E(7) ;
+    A(2,3) = E(8) ;
+    A(3,3) = E(9) ;
+    
+    A = A + A' - diag(diag(A)) ;
+
+    % correct var. order
+    perm = [0 1 0 ; 1 0 0 ; 0 0 1] ;
+    A = perm*A*perm ;
+    
+    [V,D] = eig(A) ;
+    A = 2.5*V*sqrt(D) ;
+    
+    [x,y,z]=sphere ;
+    [P,Q]=size(x) ;    
+    X=A*[x(:)';y(:)';z(:)'] ;
+    x=reshape(X(1,:),P,Q)+c(2) ;
+    y=reshape(X(2,:),P,Q)+c(1) ;
+    z=reshape(X(3,:),P,Q)+c(3) ;
+    surf(x,y,z,'FaceAlpha',.5) ;        
+  end
+end
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/overview_mser.m b/SD-VBS/benchmarks/mser/src/matlab/old/overview_mser.m
new file mode 100755
index 0000000..b7fcf2b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/overview_mser.m
@@ -0,0 +1,8 @@
+% OVERVIEW_MSER  Maximally Stable Extremal Regions
+%   This is a MATLAB/MEX implementation of Maximally Stable Extremal
+%   Regions (MSER). You can:
+%
+%   * Use MSER() to extract the maximally stable extremal regions from
+%     a given image.
+%
+%   For practical coding example, see MSER_DEMO() and MSER_DEMO3().
diff --git a/SD-VBS/benchmarks/mser/src/matlab/old/script_run_profile.m b/SD-VBS/benchmarks/mser/src/matlab/old/script_run_profile.m
new file mode 100755
index 0000000..bdb2c04
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/old/script_run_profile.m
@@ -0,0 +1,137 @@
+function script_run_profile(dataDir, resultDir, type, common,toolDir)
+
+path(path, common);
+
+% MSER_DEMO  Demonstrates MSER 
+
+% AUTORIGHTS
+% Copyright (C) 2006 Regents of the University of California
+% All rights reserved
+% 
+% Written by Andrea Vedaldi (UCLA VisionLab).
+% 
+% Redistribution and use in source and binary forms, with or without
+% modification, are permitted provided that the following conditions are met
+% 
+%     * Redistributions of source code must retain the above copyright
+%       notice, this list of conditions and the following disclaimer.
+%     * Redistributions in binary form must reproduce the above copyright
+%       notice, this list of conditions and the following disclaimer in the
+%       documentation and/or other materials provided with the distribution.
+%     * Neither the name of the University of California, Berkeley nor the
+%       names of its contributors may be used to endorse or promote products
+%       derived from this software without specific prior written permission.
+% 
+% THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+% EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+% WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+% DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
+% DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+% (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+% LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+% ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+% (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+% SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+which_image = 3 ;
+
+% --------------------------------------------------------------------
+%                                                          Create data
+% --------------------------------------------------------------------
+switch which_image
+  case 1
+    I   = rand(200,200) ;
+    I   = imsmooth(I,10) ;
+    I   = I-min(I(:)) ;
+    I   = I/max(I(:)) ;
+    lev = 10 ;
+    I   = uint8(round(I*lev)) ;
+  
+  case 2    
+    I = zeros(200,200) ;
+    I(50:150,50:150)=5 ;
+    I = imsmooth(I,10) ;
+    I = uint8(round(I)) ;
+    
+  case 3
+    Files = dir([dataDir,'/1.bmp']);
+    I=readImage(fullfile(dataDir,Files(1).name));
+
+%    if(ndims(Image) > 2)
+%
+%    for i=1:size(Image,1)
+%        for j=1:size(Image,2)
+%            I(i,j) = (Image(i,j,1) + Image(i,j,2)*6 + Image(i,j,3)*3)/10;
+%        end
+%    end
+%    
+%    else
+%    I = Image;
+%    end
+    disp(size(I));
+end
+
+% --------------------------------------------------------------------
+%                                                        Compute MSERs
+% --------------------------------------------------------------------
+
+%% Self check params
+tol = 0.1;
+elapsed = zeros(1,2);
+
+%% Timing
+start = photonStartTiming;
+
+[idx,ell,p,a] = mser(uint8(I), 2) ;
+
+%% Timing
+stop = photonEndTiming;
+    
+temp = photonReportTiming(start, stop);
+elapsed(1) = elapsed(1) + temp(1);
+elapsed(2) = elapsed(2) + temp(2);
+
+ %% Self checking
+ writeMatrix(idx, dataDir);
+ ret = selfCheck(idx, dataDir, tol);
+ if(ret == -1)
+     disp('Error in MSER');
+ end
+
+%% Timing
+photonPrintTiming(elapsed);
+
+%% --------------------------------------------------------------------
+%%                                                                Plots
+%% --------------------------------------------------------------------
+%[i,j] = ind2sub(size(I),idx) ;
+%
+%figure(100) ; clf ; imagesc(I) ; hold on ;
+%set(gca,'Position',[0 0 1 1]) ;
+%plot(j,i,'g*') ; colormap gray ;
+%
+%% swap x with y
+%ell = ell([2 1 5 4 3],:) ;
+%
+%for k=1:size(ell,2)
+%  E = ell(:,k) ;
+%  c = E(1:2) ;
+%  A = zeros(2) ;
+%  A(1,1) = E(3) ;
+%  A(1,2) = E(4) ;
+%  A(2,2) = E(5) ;  
+%  A = A + A' - diag(diag(A)) ;
+%  
+%  [V,D] = eig(A) ;
+%  A = 2.5*V*sqrt(D) ;
+%  
+%  X = A*[cos(linspace(0,2*pi,30)) ; sin(linspace(0,2*pi,30)) ;] ;
+%  X(1,:) = X(1,:) + c(1) ;
+%  X(2,:) = X(2,:) + c(2) ;
+%
+%  plot(X(1,:),X(2,:),'r-','LineWidth',2) ;
+%  plot(c(1),c(2),'r.') ;
+%  plot(j(k),i(k),'g*') ;
+%end
+%
+%line([j'; ell(1,:)],[i'; ell(2,:)],'color','b') ;
diff --git a/SD-VBS/benchmarks/mser/src/matlab/overview_mser.m b/SD-VBS/benchmarks/mser/src/matlab/overview_mser.m
new file mode 100755
index 0000000..b7fcf2b
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/overview_mser.m
@@ -0,0 +1,8 @@
+% OVERVIEW_MSER  Maximally Stable Extremal Regions
+%   This is a MATLAB/MEX implementation of Maximally Stable Extremal
+%   Regions (MSER). You can:
+%
+%   * Use MSER() to extract the maximally stable extremal regions from
+%     a given image.
+%
+%   For practical coding example, see MSER_DEMO() and MSER_DEMO3().
diff --git a/SD-VBS/benchmarks/mser/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/mser/src/matlab/script_run_profile.m
new file mode 100755
index 0000000..ec06539
--- /dev/null
+++ b/SD-VBS/benchmarks/mser/src/matlab/script_run_profile.m
@@ -0,0 +1,126 @@
+function script_run_profile(dataDir, resultDir, type, common,toolDir)
+
+mser_compile;
+path(path, common);
+
+% MSER_DEMO  Demonstrates MSER 
+
+% AUTORIGHTS
+% Copyright (C) 2006 Regents of the University of California
+% All rights reserved
+% 
+% Written by Andrea Vedaldi (UCLA VisionLab).
+% 
+% Redistribution and use in source and binary forms, with or without
+% modification, are permitted provided that the following conditions are met
+% 
+%     * Redistributions of source code must retain the above copyright
+%       notice, this list of conditions and the following disclaimer.
+%     * Redistributions in binary form must reproduce the above copyright
+%       notice, this list of conditions and the following disclaimer in the
+%       documentation and/or other materials provided with the distribution.
+%     * Neither the name of the University of California, Berkeley nor the
+%       names of its contributors may be used to endorse or promote products
+%       derived from this software without specific prior written permission.
+% 
+% THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND ANY
+% EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+% WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+% DISCLAIMED. IN NO EVENT SHALL THE REGENTS AND CONTRIBUTORS BE LIABLE FOR ANY
+% DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+% (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+% LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+% ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+% (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+% SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+which_image = 3 ;
+
+% --------------------------------------------------------------------
+%                                                          Create data
+% --------------------------------------------------------------------
+switch which_image
+  case 1
+    I   = rand(200,200) ;
+    I   = imsmooth(I,10) ;
+    I   = I-min(I(:)) ;
+    I   = I/max(I(:)) ;
+    lev = 10 ;
+    I   = uint8(round(I*lev)) ;
+  
+  case 2    
+    I = zeros(200,200) ;
+    I(50:150,50:150)=5 ;
+    I = imsmooth(I,10) ;
+    I = uint8(round(I)) ;
+    
+  case 3
+    Files = dir([dataDir,'/1.bmp']);
+    I=readImage(fullfile(dataDir,Files(1).name));
+end
+
+% --------------------------------------------------------------------
+%                                                        Compute MSERs
+% --------------------------------------------------------------------
+
+%% Self check params
+tol = 0.1;
+elapsed = zeros(1,2);
+
+rows = size(I,1);
+cols = size(I,2);
+
+fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
+
+%% Timing
+start = photonStartTiming;
+
+[idx] = mser(uint8(I), 2) ;
+
+%% Timing
+stop = photonEndTiming;
+    
+temp = photonReportTiming(start, stop);
+elapsed(1) = elapsed(1) + temp(1);
+elapsed(2) = elapsed(2) + temp(2);
+
+ %% Self checking
+ writeMatrix(idx, dataDir);
+
+%% Timing
+photonPrintTiming(elapsed);
+
+%% --------------------------------------------------------------------
+%%                                                                Plots
+%% --------------------------------------------------------------------
+%[i,j] = ind2sub(size(I),idx) ;
+%
+%figure(100) ; clf ; imagesc(I) ; hold on ;
+%set(gca,'Position',[0 0 1 1]) ;
+%plot(j,i,'g*') ; colormap gray ;
+%
+%% swap x with y
+%ell = ell([2 1 5 4 3],:) ;
+%
+%for k=1:size(ell,2)
+%  E = ell(:,k) ;
+%  c = E(1:2) ;
+%  A = zeros(2) ;
+%  A(1,1) = E(3) ;
+%  A(1,2) = E(4) ;
+%  A(2,2) = E(5) ;  
+%  A = A + A' - diag(diag(A)) ;
+%  
+%  [V,D] = eig(A) ;
+%  A = 2.5*V*sqrt(D) ;
+%  
+%  X = A*[cos(linspace(0,2*pi,30)) ; sin(linspace(0,2*pi,30)) ;] ;
+%  X(1,:) = X(1,:) + c(1) ;
+%  X(2,:) = X(2,:) + c(2) ;
+%
+%  plot(X(1,:),X(2,:),'r-','LineWidth',2) ;
+%  plot(c(1),c(2),'r.') ;
+%  plot(j(k),i(k),'g*') ;
+%end
+%
+%line([j'; ell(1,:)],[i'; ell(2,:)],'color','b') ;
diff --git a/SD-VBS/benchmarks/multi_ncut/Makefile b/SD-VBS/benchmarks/multi_ncut/Makefile
new file mode 100644
index 0000000..60cc0ec
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/Makefile
@@ -0,0 +1,3 @@
+include ../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/multi_ncut/data/Makefile b/SD-VBS/benchmarks/multi_ncut/data/Makefile
new file mode 100644
index 0000000..ba33d35
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/Makefile
@@ -0,0 +1,3 @@
+include ../../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/multi_ncut/data/cif/1.bmp b/SD-VBS/benchmarks/multi_ncut/data/cif/1.bmp
new file mode 100644
index 0000000..b27d654
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/cif/1.bmp
diff --git a/SD-VBS/benchmarks/multi_ncut/data/cif/Makefile b/SD-VBS/benchmarks/multi_ncut/data/cif/Makefile
new file mode 100644
index 0000000..a8d3300
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/cif/Makefile
@@ -0,0 +1,7 @@
+INPUT=cif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=multi_ncut
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/multi_ncut/data/cif/expected.m b/SD-VBS/benchmarks/multi_ncut/data/cif/expected.m
new file mode 100644
index 0000000..4faf6a8
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/cif/expected.m
@@ -0,0 +1,264 @@
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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diff --git a/SD-VBS/benchmarks/multi_ncut/data/cif/multi_ncut b/SD-VBS/benchmarks/multi_ncut/data/cif/multi_ncut
new file mode 100755
index 0000000..fb5ad83
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/cif/multi_ncut
diff --git a/SD-VBS/benchmarks/multi_ncut/data/fullhd/1.bmp b/SD-VBS/benchmarks/multi_ncut/data/fullhd/1.bmp
new file mode 100644
index 0000000..bf52473
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/fullhd/1.bmp
diff --git a/SD-VBS/benchmarks/multi_ncut/data/fullhd/Makefile b/SD-VBS/benchmarks/multi_ncut/data/fullhd/Makefile
new file mode 100644
index 0000000..6f3beea
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/fullhd/Makefile
@@ -0,0 +1,7 @@
+INPUT=fullhd
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=multi_ncut
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/multi_ncut/data/fullhd/multi_ncut b/SD-VBS/benchmarks/multi_ncut/data/fullhd/multi_ncut
new file mode 100755
index 0000000..8b51e3f
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/fullhd/multi_ncut
diff --git a/SD-VBS/benchmarks/multi_ncut/data/qcif/1.bmp b/SD-VBS/benchmarks/multi_ncut/data/qcif/1.bmp
new file mode 100644
index 0000000..6fd58aa
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/qcif/1.bmp
diff --git a/SD-VBS/benchmarks/multi_ncut/data/qcif/Makefile b/SD-VBS/benchmarks/multi_ncut/data/qcif/Makefile
new file mode 100644
index 0000000..920774e
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/qcif/Makefile
@@ -0,0 +1,6 @@
+INPUT=qcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=multi_ncut
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/multi_ncut/data/qcif/expected.m b/SD-VBS/benchmarks/multi_ncut/data/qcif/expected.m
new file mode 100644
index 0000000..5b8caa7
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/qcif/expected.m
@@ -0,0 +1,132 @@
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diff --git a/SD-VBS/benchmarks/multi_ncut/data/qcif/multi_ncut b/SD-VBS/benchmarks/multi_ncut/data/qcif/multi_ncut
new file mode 100755
index 0000000..fdf8017
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/qcif/multi_ncut
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sim/1.bmp b/SD-VBS/benchmarks/multi_ncut/data/sim/1.bmp
new file mode 100644
index 0000000..0bb4340
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sim/1.bmp
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sim/Makefile b/SD-VBS/benchmarks/multi_ncut/data/sim/Makefile
new file mode 100644
index 0000000..4db75cd
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sim/Makefile
@@ -0,0 +1,7 @@
+
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=multi_ncut
+INPUT=sim
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sim/expected.m b/SD-VBS/benchmarks/multi_ncut/data/sim/expected.m
new file mode 100644
index 0000000..6cf8bbf
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sim/expected.m
@@ -0,0 +1,72 @@
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+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      -1      
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sim/multi_ncut b/SD-VBS/benchmarks/multi_ncut/data/sim/multi_ncut
new file mode 100755
index 0000000..d093576
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sim/multi_ncut
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sim_fast/1.bmp b/SD-VBS/benchmarks/multi_ncut/data/sim_fast/1.bmp
new file mode 100644
index 0000000..852626f
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sim_fast/1.bmp
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sim_fast/Makefile b/SD-VBS/benchmarks/multi_ncut/data/sim_fast/Makefile
new file mode 100644
index 0000000..5ac027c
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sim_fast/Makefile
@@ -0,0 +1,6 @@
+INPUT=sim_fast
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=multi_ncut
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sim_fast/expected.m b/SD-VBS/benchmarks/multi_ncut/data/sim_fast/expected.m
new file mode 100644
index 0000000..3af3518
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sim_fast/expected.m
@@ -0,0 +1,33 @@
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       0       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       0       0       0       0       1       1       1       1       1       
+0       0       0       0       0       0       0       0       0       1       1       1       1       1       1       1       1       1       1       1       0       0       0       0       0       0       1       1       1       0       0       0       0       0       0       0       0       0       0       0       0       0       1       1       
+0       0       0       0       0       0       0       0       0       0       1       1       1       1       1       1       1       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       1       0       0       0       0       1       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sim_fast/multi_ncut b/SD-VBS/benchmarks/multi_ncut/data/sim_fast/multi_ncut
new file mode 100755
index 0000000..fb5ad83
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sim_fast/multi_ncut
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sqcif/1.bmp b/SD-VBS/benchmarks/multi_ncut/data/sqcif/1.bmp
new file mode 100644
index 0000000..ffb0ea5
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sqcif/1.bmp
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sqcif/Makefile b/SD-VBS/benchmarks/multi_ncut/data/sqcif/Makefile
new file mode 100644
index 0000000..55458a4
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sqcif/Makefile
@@ -0,0 +1,6 @@
+INPUT=sqcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=multi_ncut
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sqcif/expected.m b/SD-VBS/benchmarks/multi_ncut/data/sqcif/expected.m
new file mode 100644
index 0000000..1adb845
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sqcif/expected.m
@@ -0,0 +1,96 @@
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       2       2       2       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       2       2       2       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       2       2       2       2       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       8       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
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+19      19      19      19      16      16      16      16      16      19      12      12      3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       12      12      12      10      12      12      12      12      12      12      12      12      7       7       5       5       5       5       5       6       6       6       6       6       6       6       6       13      13      13      13      13      13      13      13      13      13      
+19      19      19      19      19      19      16      19      19      12      12      19      3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       10      10      10      10      10      10      10      12      12      12      12      12      7       5       5       10      6       6       6       6       6       6       6       6       6       6       6       6       13      13      13      13      13      13      13      17      17      
+19      19      19      19      19      19      19      19      19      3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       11      19      19      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       10      10      10      10      10      10      10      10      10      10      1       1       1       1       10      10      10      10      10      10      10      10      10      12      12      12      12      10      10      10      10      6       6       6       6       6       6       6       6       6       6       6       6       13      13      13      13      13      17      17      17      17      
+19      19      19      19      19      19      19      19      19      19      19      19      3       3       19      19      19      19      3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       3       19      19      19      19      19      19      19      11      11      11      11      11      11      11      11      11      11      11      11      11      11      11      1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      1       10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      6       6       6       6       6       6       6       6       17      17      13      13      17      17      17      17      
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      11      11      11      11      11      15      15      15      15      15      1       1       1       1       1       1       1       1       1       1       1       1       15      10      10      10      10      10      10      10      10      10      10      10      10      16      16      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      6       6       6       6       6       6       6       6       6       6       6       17      17      17      17      17      17      
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      1       1       15      15      15      1       15      15      1       15      10      10      10      10      10      10      10      10      10      10      10      16      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      6       6       6       6       6       6       6       6       6       17      17      17      17      17      17      17      
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      1       15      15      15      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      17      6       6       6       6       17      6       17      17      17      17      17      17      17      17      17      
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      17      17      17      17      17      17      6       17      17      17      17      17      17      17      17      17      17      17      
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      4       4       4       10      10      10      10      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      10      4       4       4       4       10      10      10      10      10      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       10      10      10      10      10      10      10      10      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       17      17      17      17      17      17      17      17      17      17      17      17      17      17      17      4       4       17      
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       
+19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      19      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      15      4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       4       
diff --git a/SD-VBS/benchmarks/multi_ncut/data/sqcif/multi_ncut b/SD-VBS/benchmarks/multi_ncut/data/sqcif/multi_ncut
new file mode 100755
index 0000000..8b51e3f
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/sqcif/multi_ncut
diff --git a/SD-VBS/benchmarks/multi_ncut/data/test/1.bmp b/SD-VBS/benchmarks/multi_ncut/data/test/1.bmp
new file mode 100644
index 0000000..b222b0a
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/test/1.bmp
diff --git a/SD-VBS/benchmarks/multi_ncut/data/test/Makefile b/SD-VBS/benchmarks/multi_ncut/data/test/Makefile
new file mode 100644
index 0000000..3719d30
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/test/Makefile
@@ -0,0 +1,8 @@
+
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=multi_ncut
+INPUT=test
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/multi_ncut/data/test/expected.m b/SD-VBS/benchmarks/multi_ncut/data/test/expected.m
new file mode 100644
index 0000000..df75d27
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/test/expected.m
@@ -0,0 +1,18 @@
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       
+1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       1       0       1       1       1       
+0       0       0       0       0       0       1       1       1       1       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
+0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       
diff --git a/SD-VBS/benchmarks/multi_ncut/data/test/multi_ncut b/SD-VBS/benchmarks/multi_ncut/data/test/multi_ncut
new file mode 100755
index 0000000..8b51e3f
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/test/multi_ncut
diff --git a/SD-VBS/benchmarks/multi_ncut/data/vga/1.bmp b/SD-VBS/benchmarks/multi_ncut/data/vga/1.bmp
new file mode 100644
index 0000000..8982485
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/vga/1.bmp
diff --git a/SD-VBS/benchmarks/multi_ncut/data/vga/Makefile b/SD-VBS/benchmarks/multi_ncut/data/vga/Makefile
new file mode 100644
index 0000000..1989543
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/vga/Makefile
@@ -0,0 +1,7 @@
+INPUT=vga
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=multi_ncut
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/multi_ncut/data/vga/expected.m b/SD-VBS/benchmarks/multi_ncut/data/vga/expected.m
new file mode 100644
index 0000000..c0a27cd
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/vga/expected.m
@@ -0,0 +1,480 @@
+2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
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2       2       2       2       2       2       2       2       2       2       2       2       2       2       2       
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diff --git a/SD-VBS/benchmarks/multi_ncut/data/vga/multi_ncut b/SD-VBS/benchmarks/multi_ncut/data/vga/multi_ncut
new file mode 100755
index 0000000..8b51e3f
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/data/vga/multi_ncut
diff --git a/SD-VBS/benchmarks/multi_ncut/src/c/.computeMultiW.c.swp b/SD-VBS/benchmarks/multi_ncut/src/c/.computeMultiW.c.swp
new file mode 100644
index 0000000..a3b35c6
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/src/c/.computeMultiW.c.swp
diff --git a/SD-VBS/benchmarks/multi_ncut/src/c/script_multi_ncut.c b/SD-VBS/benchmarks/multi_ncut/src/c/script_multi_ncut.c
new file mode 100644
index 0000000..e4f7912
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/src/c/script_multi_ncut.c
@@ -0,0 +1,90 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "segment.h"
+#include "extra.h"
+#define MAX_EDGE 500000
+int main(int argc, char* argv[])
+{
+    SET_UP
+    float sigma = 0.6;
+    float k = 4;
+    int min_size = 10;
+    char im1[256];
+    int num_ccs[1] = {0};
+    I2D *out;
+    I2D* im;
+    I2D* seg;
+    I2D* kernel;
+    I2D* ind;
+    I2D* output;
+    int ret;
+    int *segments;
+    edge* edges;
+    universe* u;
+
+    F2D *imageOut, *tempOut;
+    F2D *edgeWeights, *in;
+    printf("Input image: ");
+    scanf("%s", im1);
+    im = readImage(im1);
+
+
+    int height, width, num_edges, num_vertices;
+    height = im->height;
+    width = im->width;
+    num_edges = MAX_EDGE;
+    num_vertices = width * height;
+    segments = (int *) malloc(height*width*sizeof(int));
+    edges = (edge*)malloc(sizeof(edge)*width*height*4);
+    imageOut = fSetArray(height, width, 0);
+    tempOut = fSetArray(height, width, 0);
+    kernel = iMallocHandle(1,5);
+    edgeWeights = fMallocHandle(1, num_edges);
+    in = fDeepCopy(edgeWeights);
+    ind = fMallocHandle(1, num_edges);
+    u = (universe*)malloc(sizeof(universe));
+    u->elts = (uni_elt*)malloc(sizeof(uni_elt)*num_vertices);
+    output = iMallocHandle(height, width);
+
+    printf("start\n");
+    for_each_job{
+        seg = segment_image(im, sigma, k, min_size, num_ccs, segments, edges, imageOut, tempOut, kernel, edgeWeights, in, ind, u, output);
+        out = seg;
+    }
+    printf("end..\n");
+#ifdef CHECK   
+    /** Self checking - use expected.txt from data directory  **/
+    {
+        int ret=0;
+        float tol = 0;
+        
+#ifdef GENERATE_OUTPUT
+        writeMatrix(out, argv[1]);
+#endif
+ 
+    ret = selfCheck(out, "./expected_C.txt", tol);
+    if(ret < 0)
+        printf("Error in Multi N Cut\n");
+    }
+#endif
+
+    iFreeHandle(im); 
+    free(edges);
+    free(segments);
+    free(tempOut);
+    free(imageOut);
+    free(edgeWeights);
+    free(in);
+    free(ind);
+    free(output);
+    free(u->elts);
+    free(u);
+    WRITE_TO_FILE
+    return 0;
+}
+
+
diff --git a/SD-VBS/benchmarks/multi_ncut/src/c/segment-graph.c b/SD-VBS/benchmarks/multi_ncut/src/c/segment-graph.c
new file mode 100644
index 0000000..13b219b
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/src/c/segment-graph.c
@@ -0,0 +1,95 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "segment.h"
+
+// threshold function
+#define THRESHOLD(size, c) (c/size)
+
+int find(universe* u, int x)
+{
+    int y=x;
+    while (y != u->elts[y].p)
+        y = u->elts[y].p;
+    u->elts[x].p = y;
+    return y;
+}
+
+void join(universe* u, int x, int y)
+{
+    if (u->elts[x].rank > u->elts[y].rank) 
+    {
+        u->elts[y].p = x;
+        u->elts[x].size += u->elts[y].size;
+    } 
+    else 
+    {
+        u->elts[x].p = y;
+        u->elts[y].size += u->elts[x].size;
+        if (u->elts[x].rank == u->elts[y].rank)
+            u->elts[y].rank++;
+    }
+    u->num--;
+    return ;
+}
+
+universe *segment_graph(int num_vertices, int num_edges, edge *edges, float c, F2D* edgeWeights, F2D* in, I2D* ind,
+                        universe* u)
+{ 
+    float threshold[num_vertices];
+    int i, a, b, j, k;
+    //universe *u;
+    //F2D *edgeWeights;
+    I2D *indices;
+
+    edgeWeights = fResetHandle(edgeWeights,1,num_edges);
+
+    for(i=0; i<num_edges; i++)
+        asubsref(edgeWeights,i) = edges[i].w;
+
+    // sort edges by weight
+    indices = fResortIndices(edgeWeights,1, in, ind);
+
+    // make a disjoint-set forest
+    //u = (universe*)malloc(sizeof(universe));
+    //u->elts = (uni_elt*)malloc(sizeof(uni_elt)*num_vertices);
+    u->num = num_vertices;
+    for(i=0; i<num_vertices; i++)
+    {
+        u->elts[i].rank = 0;
+        u->elts[i].size = 1;
+        u->elts[i].p = i;
+    }
+
+    // init thresholds
+    for (i = 0; i < num_vertices; i++)
+        arrayref(threshold,i) = THRESHOLD(1,c);
+
+    // for each edge, in non-decreasing weight order...
+    for (i = 0; i < num_edges; i++)
+    {
+        edge *pedge = &edges[ asubsref(indices,i) ];
+    
+        // components conected by this edge
+        a = find(u, pedge->a);
+        b = find(u, pedge->b);
+        if (a != b) 
+        {
+            if ((pedge->w <= arrayref(threshold,a)) && (pedge->w <= arrayref(threshold,b))) 
+            {
+                    join(u, a, b);
+                    a = find(u, a);
+                    arrayref(threshold,a) = pedge->w + THRESHOLD(u->elts[a].size, c);
+            }
+        }
+    }
+
+    //fFreeHandle(edgeWeights);
+    //iFreeHandle(indices);
+
+  return u;
+}
+
diff --git a/SD-VBS/benchmarks/multi_ncut/src/c/segment-image.c b/SD-VBS/benchmarks/multi_ncut/src/c/segment-image.c
new file mode 100644
index 0000000..72bc16f
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/src/c/segment-image.c
@@ -0,0 +1,142 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <time.h>
+#include "segment.h"
+
+#ifndef M_PI
+#define M_PI 3.141592653589793
+#endif
+
+// dissimilarity measure between pixels
+float diff(F2D *r, int x1, int y1, int x2, int y2) 
+{
+  return sqrt(abs(( subsref(r,y1,x1) * subsref(r,y1,x1)) - ( subsref(r,y2,x2) * subsref(r,y2,x2))));
+}
+
+I2D *segment_image(I2D* im, float sigma, float c, int min_size, int *num_ccs, 
+                   int* segments, edge* edges,
+                   F2D* imageOut, F2D* tempOut, I2D* kernel, 
+                   F2D* edgeWeights, F2D* in, I2D* ind,
+                   universe* u,
+                   I2D* output)
+{
+    int width = im->width;
+    int height = im->height;
+    int num = 0, x, y, i;
+    F2D* smooth_im;
+    //I2D *output;
+    //edge* edges;
+    int components = 0;
+/*  int *colors = (int *) malloc(width*height*sizeof(int)); */
+    //segments = (int *) malloc(height*width*sizeof(int));
+
+    // smooth each color channel  
+    smooth_im = imageReblur(im, imageOut, tempOut, kernel);
+
+    //build graph
+    //edges = (edge*)malloc(sizeof(edge)*width*height*4);
+
+    for (y = 0; y < height; y++) 
+    {
+        for (x = 0; x < width; x++) 
+        {
+            segments[y*width+x] = -1;
+            if (x < width-1) 
+            {
+                    edges[num].a = y * width + x;
+                    edges[num].b = y * width + (x+1);
+                    edges[num].w = diff(smooth_im, x, y, x+1, y);
+                    num++;
+            }
+
+            if (y < height-1) 
+            {
+                    edges[num].a = y * width + x;
+                    edges[num].b = (y+1) * width + x;
+                    edges[num].w = diff(smooth_im, x, y, x, y+1);
+                    num++;
+            }
+
+            if ((x < width-1) && (y < height-1)) 
+            {
+                    edges[num].a = y * width + x;
+                    edges[num].b = (y+1) * width + (x+1);
+                    edges[num].w = diff(smooth_im, x, y, x+1, y+1);
+                    num++;
+            }
+
+            if ((x < width-1) && (y > 0)) 
+            {
+                    edges[num].a = y * width + x;
+                    edges[num].b = (y-1) * width + (x+1);
+                    edges[num].w = diff(smooth_im, x, y, x+1, y-1);
+                    num++;
+            }
+        }
+    }
+
+    //free(smooth_im);
+
+    // segment
+    u = segment_graph(width*height, num, edges, c, edgeWeights, in, ind, u);
+  
+    // post process small components
+    for (i = 0; i < num; i++) 
+    {
+        int a, b;
+        a = find(u,edges[i].a);
+        b = find(u,edges[i].b);
+        if ((a != b) && ((u->elts[a].size < min_size) || (u->elts[b].size < min_size)))
+            join(u, a, b);
+    }
+
+    //free(edges);
+    arrayref(num_ccs,0) = u->num;
+
+    // pick random colors for each component
+    //output = iMallocHandle(height, width);
+
+/*    srand(time(0));
+    for (i = 0; i < width*height; i++)
+    {
+        float temp;
+        temp = rand()/((float)RAND_MAX);
+        colors[i] = (int)(temp*255);
+    }
+*/
+   
+    for (y = 0; y < height; y++) 
+    {
+        for (x = 0; x < width; x++) 
+        {
+            int comp;
+            comp = find(u, y * width + x);
+            if(segments[comp] == -1)
+                segments[comp] = components++;
+            subsref(output, y, x) = segments[comp];
+        }
+    }  
+  
+/*
+    for (y = 0; y < height; y++) 
+    {
+        for (x = 0; x < width; x++) 
+        {
+            int comp;
+            comp = find(u, y * width + x);
+            subsref(output, y, x) = colors[comp];
+        }
+    }  
+*/
+    //free(u->elts);
+    //free(u);
+    //free(segments);
+    
+    return output;
+}
+
+
diff --git a/SD-VBS/benchmarks/multi_ncut/src/c/segment.h b/SD-VBS/benchmarks/multi_ncut/src/c/segment.h
new file mode 100644
index 0000000..73ed8de
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/src/c/segment.h
@@ -0,0 +1,46 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#ifndef SEGMENT
+#define SEGMENT
+
+#include "sdvbs_common.h"
+
+typedef struct
+{
+  float w;
+  int a, b;
+} edge;
+
+typedef struct 
+{
+  int rank;
+  int p;
+  int size;
+} uni_elt;
+
+typedef struct
+{
+    uni_elt *elts;
+    int num;
+}universe;
+
+/* use imRef to access image data. */
+#define imRef(im, x, y) (im->data[y*im->width+x])
+
+I2D *segment_image(I2D *im, float sigma, float c, int min_size, int *num_ccs, 
+                   int* segments, edge* edges,
+                   F2D* imageOut, F2D* tempOut, I2D* kernel, F2D* edgeWeights, F2D* in, I2D* ind,
+                   universe* u,
+                   I2D* output);
+universe *segment_graph(int num_vertices, int num_edges, edge *edges, float c, F2D* edgeWeights, F2D* in, I2D* ind,
+                        universe* u);
+void join(universe* u, int x, int y);
+int find(universe* u, int x);
+float diff(F2D *r, int x1, int y1, int x2, int y2);
+
+
+#endif
+
+
diff --git a/SD-VBS/benchmarks/multi_ncut/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/multi_ncut/src/matlab/script_run_profile.m
new file mode 100755
index 0000000..7624137
--- /dev/null
+++ b/SD-VBS/benchmarks/multi_ncut/src/matlab/script_run_profile.m
@@ -0,0 +1,78 @@
+% MNcutDemo.m
+% created by song, 06/13/2005
+%  an exmaple of how to use and display MNcut
+
+
+function script_run_profile(dataDir, resultDir, type, common, toolDir)
+
+%% Input parameters
+
+if(nargin == 0)
+    data_set='test';    
+end
+if(nargin <=2)
+    imageSize = 100;
+end
+
+num_segs = 20;
+if(strcmp(type, 'test'))
+    num_segs = 1;
+elseif(strcmp(type, 'sim_fast'))
+    num_segs = 1;
+elseif(strcmp(type, 'sim'))
+    num_segs = 2;
+elseif(strcmp(type, 'sqcif'))
+    num_segs = 3;
+elseif(strcmp(type, 'qcif'))
+    num_segs = 4;
+elseif(strcmp(type, 'cif'))
+    num_segs = 8;
+elseif(strcmp(type, 'vga'))
+    num_segs = 13;
+elseif(strcmp(type, 'wuxga'))
+    num_segs = 32;
+end
+
+path(path, [toolDir,'/MultiNcut']);
+path(path, common);
+
+img_filename = [dataDir, '/1.bmp'];
+%I=imread(img_filename);
+%I = rgb2gray(I);
+
+I = readImage(img_filename);
+
+%% Self check params
+tol = 0.1;
+elapsed = zeros(1,2);
+rows = size(I,1);
+cols = size(I,2);    
+fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
+
+%% Timing
+start = photonStartTiming;
+
+[SegLabel,eigenVectors,eigenValues]= MNcut(I,num_segs);
+
+%% Timing
+stop = photonEndTiming;
+    
+temp = photonReportTiming(start, stop);
+elapsed(1) = elapsed(1) + temp(1);
+elapsed(2) = elapsed(2) + temp(2);
+
+%% Self checking
+writeMatrix(SegLabel, dataDir);
+
+%% Timing
+photonPrintTiming(elapsed);
+
+for j=1:size(SegLabel,3),
+   [gx,gy] = gradient(SegLabel(:,:,j));
+   bw = (abs(gx)>0.1) + (abs(gy) > 0.1);
+
+   figure(1);clf; J1=showmask(double(I),bw); imagesc(J1);axis image; axis off;
+   set(gca, 'Position', [0 0 1 1]);
+end
+
+
diff --git a/SD-VBS/benchmarks/pca/Makefile b/SD-VBS/benchmarks/pca/Makefile
new file mode 100644
index 0000000..60cc0ec
--- /dev/null
+++ b/SD-VBS/benchmarks/pca/Makefile
@@ -0,0 +1,3 @@
+include ../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/pca/data/sat.trn b/SD-VBS/benchmarks/pca/data/sat.trn
new file mode 100644
index 0000000..7d38147
--- /dev/null
+++ b/SD-VBS/benchmarks/pca/data/sat.trn
@@ -0,0 +1,4436 @@
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diff --git a/SD-VBS/benchmarks/pca/data/sat.tst b/SD-VBS/benchmarks/pca/data/sat.tst
new file mode 100644
index 0000000..4754fb0
--- /dev/null
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diff --git a/SD-VBS/benchmarks/pca/src/pca b/SD-VBS/benchmarks/pca/src/pca
new file mode 100755
index 0000000..15b5908
--- /dev/null
+++ b/SD-VBS/benchmarks/pca/src/pca
diff --git a/SD-VBS/benchmarks/pca/src/pca.c b/SD-VBS/benchmarks/pca/src/pca.c
new file mode 100644
index 0000000..4637e7c
--- /dev/null
+++ b/SD-VBS/benchmarks/pca/src/pca.c
@@ -0,0 +1,694 @@
+/***********************  Contents  ****************************************
+ * Principal Components Analysis: C, 638 lines. ****************************
+ * Sample input data set (final 36 lines). *********************************
+ ***************************************************************************
+ */
+
+/*********************************/
+/* Principal Components Analysis */
+/*********************************/
+
+/*********************************************************************/
+/* Principal Components Analysis or the Karhunen-Loeve expansion is a
+   classical method for dimensionality reduction or exploratory data
+   analysis.  One reference among many is: F. Murtagh and A. Heck,
+   Multivariate Data Analysis, Kluwer Academic, Dordrecht, 1987.
+
+Author:
+F. Murtagh
+Phone:        + 49 89 32006298 (work)
++ 49 89 965307 (home)
+Earn/Bitnet:  fionn@dgaeso51,  fim@dgaipp1s,  murtagh@stsci
+Span:         esomc1::fionn
+Internet:     murtagh@scivax.stsci.edu
+
+F. Murtagh, Munich, 6 June 1989                                   */   
+/*********************************************************************/
+
+#include <stdio.h>
+#include <string.h>
+#include <math.h>
+
+#define SIGN(a, b) ( (b) < 0 ? -fabs(a) : fabs(a) )
+
+main(argc, argv)
+  int argc;
+  char *argv[];
+
+{
+  FILE *stream;
+  int  n, m,  i, j, k, k2;
+  float **data, **matrix(), **symmat, **symmat2, *vector(), *evals, *interm;
+  void free_matrix(), free_vector(), corcol(), covcol(), scpcol();
+  void tred2(), tqli();
+  float in_value;
+  char option, *strncpy();
+
+  /*********************************************************************
+    Get from command line:
+    input data file name, #rows, #cols, option.
+
+    Open input file: fopen opens the file whose name is stored in the
+    pointer argv[argc-1]; if unsuccessful, error message is printed to
+    stderr.
+   *********************************************************************/
+
+  if (argc !=  5)
+  {
+    printf("Syntax help: PCA filename #rows #cols option\n\n");
+    printf("(filename -- give full path name,\n");
+    printf(" #rows                          \n");
+    printf(" #cols    -- integer values,\n");                  
+    printf(" option   -- R (recommended) for correlation analysis,\n");
+    printf("             V for variance/covariance analysis\n");
+    printf("             S for SSCP analysis.)\n");
+    exit(1);
+  }
+
+  n = atoi(argv[2]);              /* # rows */
+  m = atoi(argv[3]);              /* # columns */
+  strncpy(&option,argv[4],1);     /* Analysis option */
+
+  printf("No. of rows: %d, no. of columns: %d.\n",n,m);
+  printf("Input file: %s.\n",argv[1]);
+
+  if ((stream = fopen(argv[1],"r")) == NULL)
+  {
+    fprintf(stderr, "Program %s : cannot open file %s\n",
+        argv[0], argv[1]);
+    fprintf(stderr, "Exiting to system.");
+    exit(1);
+    /* Note: in versions of DOS prior to 3.0, argv[0] contains the
+       string "C". */
+  }
+
+  /* Now read in data. */
+
+  data = matrix(n, m);  /* Storage allocation for input data */
+
+  for (i = 1; i <= n; i++)
+  {
+    for (j = 1; j <= m; j++)
+    {
+      fscanf(stream, "%f", &in_value);
+      data[i][j] = in_value;
+      printf("at row %d column %d is %lf\n",i,j,data[i][j]);
+    }
+  }
+
+
+
+  /* Check on (part of) input data.
+     for (i = 1; i <= 18; i++) {for (j = 1; j <= 8; j++)  {
+     printf("%7.1f", data[i][j]);  }  printf("\n");  }
+     */
+
+
+
+  symmat = matrix(m, m);  /* Allocation of correlation (etc.) matrix */
+
+  /* Look at analysis option; branch in accordance with this. */
+
+  switch(option)
+  {
+    case 'R':
+    case 'r':
+      printf("Analysis of correlations chosen.\n");
+      corcol(data, n, m, symmat);
+
+      /* Output correlation matrix.
+         for (i = 1; i <= m; i++) {
+         for (j = 1; j <= 8; j++)  {
+         printf("%7.4f", symmat[i][j]);  }
+         printf("\n");  }
+         */
+      break;
+    case 'V':
+    case 'v':
+      printf("Analysis of variances-covariances chosen.\n");
+      covcol(data, n, m, symmat);
+
+      /* Output variance-covariance matrix.
+         for (i = 1; i <= m; i++) {
+         for (j = 1; j <= 8; j++)  {
+         printf("%7.1f", symmat[i][j]);  }
+         printf("\n");  }
+         */
+      break;
+    case 'S':
+    case 's':
+      printf("Analysis of sums-of-squares-cross-products");
+      printf(" matrix chosen.\n");
+      scpcol(data, n, m, symmat);
+
+      /* Output SSCP matrix.
+         for (i = 1; i <= m; i++) {
+         for (j = 1; j <= 8; j++)  {
+         printf("%7.1f", symmat[i][j]);  }
+         printf("\n");  }
+         */
+      break;
+    default:
+      printf("Option: %s\n",option);
+      printf("For option, please type R, V, or S\n");
+      printf("(upper or lower case).\n");
+      printf("Exiting to system.\n");
+      exit(1);
+      break;
+  }
+
+  /*********************************************************************
+    Eigen-reduction
+   **********************************************************************/
+
+  /* Allocate storage for dummy and new vectors. */
+  evals = vector(m);     /* Storage alloc. for vector of eigenvalues */
+  printf("the vector storage size is %d\n",m);
+  interm = vector(m);    /* Storage alloc. for 'intermediate' vector */
+  symmat2 = matrix(m, m);  /* Duplicate of correlation (etc.) matrix */
+  for (i = 1; i <= m; i++) {
+    for (j = 1; j <= m; j++) {
+      symmat2[i][j] = symmat[i][j]; /* Needed below for col. projections */
+    }
+  }
+  tred2(symmat, m, evals, interm);  /* Triangular decomposition */
+  printf("eval value at 0 is %lf\n",evals[0]);
+  printf("eval value at 1 is %lf\n",evals[1]);
+  printf("eval value at 2 is %lf\n",evals[2]);
+
+  printf("m/height is %lf \n",m);
+
+  printf("m/height is %d \n",m);
+  printf("m/height is %d \n",n);
+  printf("m/height is %d \n",n);
+
+
+  tqli(evals, interm, m, symmat);   /* Reduction of sym. trid. matrix */
+  /* evals now contains the eigenvalues,
+     columns of symmat now contain the associated eigenvectors. */
+
+  printf("\nEigenvalues:\n");
+  for (j = m; j >= 1; j--) {
+    printf("%18.5f\n", evals[j]); }
+  printf("\n(Eigenvalues should be strictly positive; limited\n");
+  printf("precision machine arithmetic may affect this.\n");
+  printf("Eigenvalues are often expressed as cumulative\n");
+  printf("percentages, representing the 'percentage variance\n");
+  printf("explained' by the associated axis or principal component.)\n");
+
+  printf("\nEigenvectors:\n");
+  printf("(First three; their definition in terms of original vbes.)\n");
+  for (j = 1; j <= m; j++) {
+    for (i = 1; i <= 3; i++)  {
+      printf("%12.4f", symmat[j][m-i+1]);  }
+    printf("\n");  }
+
+
+
+
+  /* Form projections of row-points on first three prin. components. */
+  /* Store in 'data', overwriting original data. */
+  for (i = 1; i <= n; i++) {
+    for (j = 1; j <= m; j++) {
+      interm[j] = data[i][j];
+     printf("Iteration i=%d j=%d data = %lf\n\n", i,j,data[i][j]);
+
+    }   
+    for (k = 1; k <= 3; k++) {
+      data[i][k] = 0.0;
+      for (k2 = 1; k2 <= m; k2++) {
+        data[i][k] += interm[k2] * symmat[k2][m-k+1]; 
+     printf("Iteration i= %d, j = %d k=%d, k2=%d : data = %lf\n",i,j,k, k2,data[i][k]);
+
+      }
+     printf("\n");
+
+    }
+  }
+
+
+
+
+
+
+
+
+
+
+
+  printf("\nProjections of row-points on first 3 prin. comps.:\n");
+  for (i = 1; i <= n; i++) {
+    for (j = 1; j <= 3; j++)  {
+      printf("%12.4f", data[i][j]);  }
+    printf("\n");  }
+return;
+
+  /* Form projections of col.-points on first three prin. components. */
+  /* Store in 'symmat2', overwriting what was stored in this. */
+  for (j = 1; j <= m; j++) {
+    for (k = 1; k <= m; k++) {
+      interm[k] = symmat2[j][k]; }  /*symmat2[j][k] will be overwritten*/
+    for (i = 1; i <= 3; i++) {
+      symmat2[j][i] = 0.0;
+      for (k2 = 1; k2 <= m; k2++) {
+        symmat2[j][i] += interm[k2] * symmat[k2][m-i+1]; }
+      if (evals[m-i+1] > 0.0005)   /* Guard against zero eigenvalue */
+        symmat2[j][i] /= sqrt(evals[m-i+1]);   /* Rescale */
+      else
+        symmat2[j][i] = 0.0;    /* Standard kludge */
+    }
+  }
+
+  printf("\nProjections of column-points on first 3 prin. comps.:\n");
+  for (j = 1; j <= m; j++) {
+    for (k = 1; k <= 3; k++)  {
+      printf("%12.4f", symmat2[j][k]);  }
+    printf("\n");  }
+
+  free_matrix(data, n, m);
+  free_matrix(symmat, m, m);
+  free_matrix(symmat2, m, m);
+  free_vector(evals, m);
+  free_vector(interm, m);
+
+}
+
+/**  Correlation matrix: creation  ***********************************/
+
+void corcol(data, n, m, symmat)
+  float **data, **symmat;
+  int n, m;
+  /* Create m * m correlation matrix from given n * m data matrix. */
+{
+  float eps = 0.005;
+  float x, *mean, *stddev, *vector();
+  int i, j, j1, j2;
+
+  /* Allocate storage for mean and std. dev. vectors */
+
+  mean = vector(m);
+  stddev = vector(m);
+
+  /* Determine mean of column vectors of input data matrix */
+
+  for (j = 1; j <= m; j++)
+  {
+    mean[j] = 0.0;
+    for (i = 1; i <= n; i++)
+    {
+      mean[j] += data[i][j];
+    }
+    mean[j] /= (float)n;
+  }
+
+  printf("\nMeans of column vectors:\n");
+  for (j = 1; j <= m; j++)  {
+    printf("%7.1f",mean[j]);  }   printf("\n");
+
+  /* Determine standard deviations of column vectors of data matrix. */
+
+  for (j = 1; j <= m; j++)
+  {
+    stddev[j] = 0.0;
+    for (i = 1; i <= n; i++)
+    {
+      stddev[j] += (   ( data[i][j] - mean[j] ) *
+          ( data[i][j] - mean[j] )  );
+    }
+    stddev[j] /= (float)n;
+    stddev[j] = sqrt(stddev[j]);
+    /* The following in an inelegant but usual way to handle
+       near-zero std. dev. values, which below would cause a zero-
+       divide. */
+    if (stddev[j] <= eps) stddev[j] = 1.0;
+  }
+
+  printf("\nStandard deviations of columns:\n");
+  for (j = 1; j <= m; j++) { printf("%7.1f", stddev[j]); }
+  printf("\n");
+
+  /* Center and reduce the column vectors. */
+
+  for (i = 1; i <= n; i++)
+  {
+    for (j = 1; j <= m; j++)
+    {
+      data[i][j] -= mean[j];
+      x = sqrt((float)n);
+      x *= stddev[j];
+      data[i][j] /= x;
+      printf("value is %lf\n",data[i][j]);
+    }
+  }
+
+  /* Calculate the m * m correlation matrix. */
+  for (j1 = 1; j1 <= m-1; j1++)
+  {
+    symmat[j1][j1] = 1.0;
+    for (j2 = j1+1; j2 <= m; j2++)
+    {
+      symmat[j1][j2] = 0.0;
+      for (i = 1; i <= n; i++)
+      {
+        symmat[j1][j2] += ( data[i][j1] * data[i][j2]);
+          printf("multiplying values [%d][%d] * [%d][%d]\n",i,j1,i,j2);
+          printf("Multiplying %lf and %lf\n",data[i][j1],data[i][j2]);
+
+          printf("Value at %d %d = %lf\n",j1,j2,symmat[j1][j2]);
+      }
+      printf("**SPLIT**\n");
+      printf("swapping [%d] [%d] = [%d] [%d]\n",j2,j1, j1,j2);
+
+      symmat[j2][j1] = symmat[j1][j2];
+    }
+  }
+  symmat[m][m] = 1.0;
+
+
+  return;
+
+}
+
+/**  Variance-covariance matrix: creation  *****************************/
+
+void covcol(data, n, m, symmat)
+  float **data, **symmat;
+  int n, m;
+  /* Create m * m covariance matrix from given n * m data matrix. */
+{
+  float *mean, *vector();
+  int i, j, j1, j2;
+
+  /* Allocate storage for mean vector */
+
+  mean = vector(m);
+
+  /* Determine mean of column vectors of input data matrix */
+
+  for (j = 1; j <= m; j++)
+  {
+    mean[j] = 0.0;
+    for (i = 1; i <= n; i++)
+    {
+      mean[j] += data[i][j];
+    }
+    mean[j] /= (float)n;
+  }
+
+  printf("\nMeans of column vectors:\n");
+  for (j = 1; j <= m; j++)  {
+    printf("%7.1f",mean[j]);  }   printf("\n");
+
+  /* Center the column vectors. */
+
+  for (i = 1; i <= n; i++)
+  {
+    for (j = 1; j <= m; j++)
+    {
+      data[i][j] -= mean[j];
+    }
+  }
+
+  /* Calculate the m * m covariance matrix. */
+  for (j1 = 1; j1 <= m; j1++)
+  {
+    for (j2 = j1; j2 <= m; j2++)
+    {
+      symmat[j1][j2] = 0.0;
+      for (i = 1; i <= n; i++)
+      {
+        symmat[j1][j2] += data[i][j1] * data[i][j2];
+      }
+      symmat[j2][j1] = symmat[j1][j2];
+    }
+  }
+
+  return;
+
+}
+
+/**  Sums-of-squares-and-cross-products matrix: creation  **************/
+
+void scpcol(data, n, m, symmat)
+  float **data, **symmat;
+  int n, m;
+  /* Create m * m sums-of-cross-products matrix from n * m data matrix. */
+{
+  int i, j1, j2;
+
+  /* Calculate the m * m sums-of-squares-and-cross-products matrix. */
+
+  for (j1 = 1; j1 <= m; j1++)
+  {
+    for (j2 = j1; j2 <= m; j2++)
+    {
+      symmat[j1][j2] = 0.0;
+      for (i = 1; i <= n; i++)
+      {
+        symmat[j1][j2] += data[i][j1] * data[i][j2];
+      }
+      symmat[j2][j1] = symmat[j1][j2];
+    }
+  }
+
+  return;
+
+}
+
+/**  Error handler  **************************************************/
+
+void erhand(err_msg)
+  char err_msg[];
+  /* Error handler */
+{
+  fprintf(stderr,"Run-time error:\n");
+  fprintf(stderr,"%s\n", err_msg);
+  fprintf(stderr,"Exiting to system.\n");
+  exit(1);
+}
+
+/**  Allocation of vector storage  ***********************************/
+
+float *vector(n)
+  int n;
+  /* Allocates a float vector with range [1..n]. */
+{
+
+  float *v;
+
+  v = (float *) malloc ((unsigned) n*sizeof(float));
+  if (!v) erhand("Allocation failure in vector().");
+  return v-1;
+
+}
+
+/**  Allocation of float matrix storage  *****************************/
+
+float **matrix(n,m)
+  int n, m;
+  /* Allocate a float matrix with range [1..n][1..m]. */
+{
+  int i;
+  float **mat;
+
+  /* Allocate pointers to rows. */
+  mat = (float **) malloc((unsigned) (n)*sizeof(float*));
+  if (!mat) erhand("Allocation failure 1 in matrix().");
+  mat -= 1;
+
+  /* Allocate rows and set pointers to them. */
+  for (i = 1; i <= n; i++)
+  {
+    mat[i] = (float *) malloc((unsigned) (m)*sizeof(float));
+    if (!mat[i]) erhand("Allocation failure 2 in matrix().");
+    mat[i] -= 1;
+  }
+
+  /* Return pointer to array of pointers to rows. */
+  return mat;
+
+}
+
+/**  Deallocate vector storage  *********************************/
+
+void free_vector(v,n)
+  float *v;
+  int n;
+  /* Free a float vector allocated by vector(). */
+{
+  free((char*) (v+1));
+}
+
+/**  Deallocate float matrix storage  ***************************/
+
+void free_matrix(mat,n,m)
+  float **mat;
+  int n, m;
+  /* Free a float matrix allocated by matrix(). */
+{
+  int i;
+
+  for (i = n; i >= 1; i--)
+  {
+    free ((char*) (mat[i]+1));
+  }
+  free ((char*) (mat+1));
+}
+
+/**  Reduce a real, symmetric matrix to a symmetric, tridiag. matrix. */
+
+void tred2(a, n, d, e)
+  float **a, *d, *e;
+  /* float **a, d[], e[]; */
+  int n;
+  /* Householder reduction of matrix a to tridiagonal form.
+Algorithm: Martin et al., Num. Math. 11, 181-195, 1968.
+Ref: Smith et al., Matrix Eigensystem Routines -- EISPACK Guide
+Springer-Verlag, 1976, pp. 489-494.
+W H Press et al., Numerical Recipes in C, Cambridge U P,
+1988, pp. 373-374.  */
+{
+  int l, k, j, i;
+  float scale, hh, h, g, f;
+
+  for (i = n; i >= 2; i--)
+  {
+    l = i - 1;
+    h = scale = 0.0;
+    if (l > 1)
+    {
+      for (k = 1; k <= l; k++)
+        scale += fabs(a[i][k]);
+      if (scale == 0.0)
+        e[i] = a[i][l];
+      else
+      {
+        for (k = 1; k <= l; k++)
+        {
+          a[i][k] /= scale;
+          h += a[i][k] * a[i][k];
+        }
+        f = a[i][l];
+        g = f>0 ? -sqrt(h) : sqrt(h);
+        e[i] = scale * g;
+        h -= f * g;
+        a[i][l] = f - g;
+        f = 0.0;
+        for (j = 1; j <= l; j++)
+        {
+          a[j][i] = a[i][j]/h;
+          g = 0.0;
+          for (k = 1; k <= j; k++)
+            g += a[j][k] * a[i][k];
+          for (k = j+1; k <= l; k++)
+            g += a[k][j] * a[i][k];
+          e[j] = g / h;
+          f += e[j] * a[i][j];
+        }
+        hh = f / (h + h);
+        for (j = 1; j <= l; j++)
+        {
+          f = a[i][j];
+          e[j] = g = e[j] - hh * f;
+          for (k = 1; k <= j; k++)
+            a[j][k] -= (f * e[k] + g * a[i][k]);
+        }
+      }
+    }
+    else
+      e[i] = a[i][l];
+    d[i] = h;
+  }
+  d[1] = 0.0;
+  e[1] = 0.0;
+  for (i = 1; i <= n; i++)
+  {
+    l = i - 1;
+    if (d[i])
+    {
+      for (j = 1; j <= l; j++)
+      {
+        g = 0.0;
+        for (k = 1; k <= l; k++)
+          g += a[i][k] * a[k][j];
+        for (k = 1; k <= l; k++)
+          a[k][j] -= g * a[k][i];
+      }
+    }
+    d[i] = a[i][i];
+    a[i][i] = 1.0;
+    for (j = 1; j <= l; j++)
+      a[j][i] = a[i][j] = 0.0;
+  }
+}
+
+/**  Tridiagonal QL algorithm -- Implicit  **********************/
+
+void tqli(d, e, n, z)
+  float d[], e[], **z;
+  int n;
+{
+  int m, l, iter, i, k;
+  float s, r, p, g, f, dd, c, b;
+  void erhand();
+
+  for (i = 2; i <= n; i++)
+    e[i-1] = e[i];
+  e[n] = 0.0;
+  for (l = 1; l <= n; l++)
+  {
+    iter = 0;
+    do
+    {
+      for (m = l; m <= n-1; m++)
+      {
+        dd = fabs(d[m]) + fabs(d[m+1]);
+        if (fabs(e[m]) + dd == dd) break;
+      }
+      if (m != l)
+      {
+        if (iter++ == 30) erhand("No convergence in TLQI.");
+        g = (d[l+1] - d[l]) / (2.0 * e[l]);
+        r = sqrt((g * g) + 1.0);
+        g = d[m] - d[l] + e[l] / (g + SIGN(r, g));
+        s = c = 1.0;
+        p = 0.0;
+        for (i = m-1; i >= l; i--)
+        {
+          f = s * e[i];
+          b = c * e[i];
+          if (fabs(f) >= fabs(g))
+          {
+            c = g / f;
+            r = sqrt((c * c) + 1.0);
+            e[i+1] = f * r;
+            c *= (s = 1.0/r);
+          }
+          else
+          {
+            s = f / g;
+            r = sqrt((s * s) + 1.0);
+            e[i+1] = g * r;
+            s *= (c = 1.0/r);
+          }
+          g = d[i+1] - p;
+          r = (d[i] - g) * s + 2.0 * c * b;
+          p = s * r;
+          d[i+1] = g + p;
+          g = c * r - b;
+          for (k = 1; k <= n; k++)
+          {
+            f = z[k][i+1];
+            z[k][i+1] = s * z[k][i] + c * f;
+            z[k][i] = c * z[k][i] - s * f;
+          }
+        }
+        d[l] = d[l] - p;
+        e[l] = g;
+        e[m] = 0.0;
+      }
+    }  while (m != l);
+  }
+}
+
+
diff --git a/SD-VBS/benchmarks/sift/Makefile b/SD-VBS/benchmarks/sift/Makefile
new file mode 100644
index 0000000..60cc0ec
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/Makefile
@@ -0,0 +1,3 @@
+include ../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/sift/data/Makefile b/SD-VBS/benchmarks/sift/data/Makefile
new file mode 100644
index 0000000..ba33d35
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/Makefile
@@ -0,0 +1,3 @@
+include ../../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/sift/data/cif/1.bmp b/SD-VBS/benchmarks/sift/data/cif/1.bmp
new file mode 100644
index 0000000..510ee1e
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/cif/1.bmp
diff --git a/SD-VBS/benchmarks/sift/data/cif/Makefile b/SD-VBS/benchmarks/sift/data/cif/Makefile
new file mode 100644
index 0000000..f9f69ad
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/cif/Makefile
@@ -0,0 +1,7 @@
+INPUT=cif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=sift
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/sift/data/cif/expected.m b/SD-VBS/benchmarks/sift/data/cif/expected.m
new file mode 100644
index 0000000..af2bf0d
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/cif/expected.m
@@ -0,0 +1,3 @@
+136.999167      77.000720       83.999729       112.000277      121.000620      39.000176       51.001094       43.999857       61.998244       13.999880       25.000228       47.997497       33.001164       55.999991       20.001724       54.000010       3.999342        5.000423        20.000317       43.000814       14.996794       15.002251       26.996749       19.002418       
+112.999914      76.000321       129.999754      130.999869      109.999693      139.999571      14.999954       8.999146        17.000011       60.999649       13.999972       50.998759       37.000079       49.999613       52.000721       20.998285       4.001589        67.002178       28.000061       31.999063       14.997124       26.998721       15.996770       21.000680       
+0.000541        2.000809        2.000690        1.999219        1.999901        1.999766        -0.000501       1.001493        0.997885        2.002503        2.001009        2.000486        0.000857        0.000447        0.999257        1.001282        1.999210        2.004933        1.998901        2.002017        0.000844        0.002754        0.003280        0.999702        
diff --git a/SD-VBS/benchmarks/sift/data/cif/sift b/SD-VBS/benchmarks/sift/data/cif/sift
new file mode 100755
index 0000000..bb1cb68
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/cif/sift
diff --git a/SD-VBS/benchmarks/sift/data/fullhd/1.bmp b/SD-VBS/benchmarks/sift/data/fullhd/1.bmp
new file mode 100644
index 0000000..a9113a9
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/fullhd/1.bmp
diff --git a/SD-VBS/benchmarks/sift/data/fullhd/Makefile b/SD-VBS/benchmarks/sift/data/fullhd/Makefile
new file mode 100644
index 0000000..0a2f146
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/fullhd/Makefile
@@ -0,0 +1,7 @@
+INPUT=fullhd
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=sift
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/sift/data/fullhd/expected.m b/SD-VBS/benchmarks/sift/data/fullhd/expected.m
new file mode 100644
index 0000000..186fa90
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/fullhd/expected.m
@@ -0,0 +1,3 @@
+414.999928      4.000992        4.001288        123.000042      71.999940       78.999870       104.999905      112.999724      48.002433       12.999701       42.000432       59.002691       23.000113       28.000855       46.001861       31.000996       52.998290       19.001083       50.999850       3.998759        4.998837        18.999829       40.999310       24.995970       18.001268       
+2156.000398     535.996659      265.997001      73.999950       70.999681       121.999948      123.000221      104.000345      13.999844       58.000118       8.999411        14.999927       14.000431       51.000060       47.999387       35.000137       46.000387       49.000452       19.002464       4.001419        62.999499       26.000252       29.000954       16.000873       19.999109       
+1.000357        1.997461        1.997128        0.999547        2.002183        2.002401        2.001073        2.000907        0.000804        0.997062        1.001759        1.000496        2.001831        1.997246        2.000260        0.000086        -0.000249       0.998226        0.997202        1.998000        2.001326        1.997402        2.001034        0.002951        0.995889        
diff --git a/SD-VBS/benchmarks/sift/data/fullhd/out b/SD-VBS/benchmarks/sift/data/fullhd/out
new file mode 100644
index 0000000..39c7bad
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/fullhd/out
@@ -0,0 +1,22344 @@
+
+Benchmark               - sift
+Data set                - fullhd
+ BEFORE OFRAMES PRINT = 3       20369   3840    2160
+30      5.000000        9905.000000
+31      5.000000        9943.000000
+32      5.000000        9951.000000
+33      5.000000        9954.000000
+34      5.000000        9969.000000
+35      5.000000        9981.000000
+36      5.000000        9985.000000
+37      5.000000        10001.000000
+38      5.000000        10005.000000
+39      5.000000        10081.000000
+40      5.000000        11404.000000
+41      5.000000        11423.000000
+42      5.000000        11425.000000
+43      5.000000        11430.000000
+44      5.000000        11452.000000
+45      5.000000        11462.000000
+46      5.000000        11467.000000
+47      5.000000        11471.000000
+48      5.000000        11481.000000
+49      5.000000        11486.000000
+50      5.000000        11500.000000
+51      5.000000        11502.000000
+52      5.000000        11506.000000
+53      5.000000        11509.000000
+54      5.000000        11519.000000
+55      5.000000        11524.000000
+56      5.000000        11530.000000
+57      5.000000        11534.000000
+58      5.000000        11540.000000
+59      5.000000        11544.000000
+60      5.000000        11549.000000
+61      5.000000        11567.000000
+62      5.000000        11569.000000
+63      5.000000        11574.000000
+64      5.000000        11582.000000
+65      5.000000        11585.000000
+66      5.000000        11587.000000
+67      5.000000        11592.000000
+68      5.000000        11596.000000
+69      5.000000        11599.000000
+70      5.000000        11604.000000
+71      5.000000        11606.000000
+72      5.000000        11631.000000
+73      5.000000        11636.000000
+74      5.000000        11642.000000
+75      5.000000        11655.000000
+76      6.000000        11541.000000
+77      6.000000        11545.000000
+78      6.000000        11550.000000
+79      6.000000        11560.000000
+80      6.000000        11567.000000
+81      6.000000        11573.000000
+82      6.000000        11583.000000
+83      6.000000        11592.000000
+84      6.000000        11598.000000
+85      6.000000        11607.000000
+86      6.000000        11613.000000
+87      6.000000        11617.000000
+88      6.000000        11637.000000
+89      6.000000        11753.000000
+90      6.000000        11807.000000
+91      6.000000        11809.000000
+92      6.000000        13055.000000
+93      6.000000        13080.000000
+94      6.000000        13138.000000
+95      6.000000        13172.000000
+96      6.000000        13176.000000
+97      6.000000        13196.000000
+98      6.000000        13238.000000
+99      6.000000        13243.000000
+100     6.000000        13292.000000
+101     6.000000        13300.000000
+102     6.000000        13302.000000
+103     6.000000        13306.000000
+104     7.000000        13235.000000
+105     7.000000        13249.000000
+106     8.000000        16078.000000
+107     9.000000        16642.000000
+108     10.000000       18298.000000
+109     10.000000       18319.000000
+110     10.000000       19424.000000
+111     10.000000       19462.000000
+112     10.000000       19598.000000
+113     11.000000       19959.000000
+114     11.000000       19972.000000
+115     11.000000       19975.000000
+116     11.000000       19983.000000
+117     11.000000       19996.000000
+118     12.000000       21627.000000
+119     12.000000       21631.000000
+120     12.000000       21707.000000
+121     14.000000       26132.000000
+122     14.000000       26135.000000
+123     15.000000       27983.000000
+124     16.000000       29529.000000
+125     16.000000       29580.000000
+126     20.000000       36477.000000
+127     21.000000       38049.000000
+128     22.000000       39681.000000
+129     23.000000       41265.000000
+130     23.000000       41383.000000
+131     23.000000       41457.000000
+132     30.000000       53163.000000
+133     34.000000       59824.000000
+134     37.000000       64836.000000
+135     37.000000       64846.000000
+136     37.000000       64860.000000
+137     37.000000       64893.000000
+138     38.000000       66513.000000
+139     44.000000       76721.000000
+140     45.000000       78238.000000
+141     45.000000       78286.000000
+142     45.000000       78290.000000
+143     46.000000       79989.000000
+144     47.000000       81704.000000
+145     51.000000       88356.000000
+146     53.000000       91732.000000
+147     68.000000       116896.000000
+148     69.000000       118580.000000
+149     429.000000      722306.000000
+150     431.000000      725654.000000
+151     431.000000      725672.000000
+152     431.000000      725685.000000
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+169     148.000000      31311.000000
+170     148.000000      31316.000000
+171     148.000000      31332.000000
+172     148.000000      31343.000000
+173     148.000000      31348.000000
+174     148.000000      31351.000000
+175     148.000000      31359.000000
+176     148.000000      31364.000000
+177     148.000000      31367.000000
+178     148.000000      31375.000000
+179     148.000000      31380.000000
+180     148.000000      31383.000000
+181     148.000000      31391.000000
+182     148.000000      31396.000000
+183     148.000000      31399.000000
+184     148.000000      31407.000000
+185     148.000000      31412.000000
+186     148.000000      31415.000000
+187     148.000000      31423.000000
+188     148.000000      31428.000000
+189     148.000000      31431.000000
+190     148.000000      31439.000000
+191     148.000000      31444.000000
+192     151.000000      32186.000000
+193     152.000000      31943.000000
+194     152.000000      31951.000000
+195     152.000000      31959.000000
+196     152.000000      31967.000000
+197     152.000000      31975.000000
+198     152.000000      31983.000000
+199     243.000000      51032.000000
+200     263.000000      55232.000000
+201     4.000000        845.000000
+202     4.000000        1315.000000
+203     19.000000       4465.000000
+204     22.000000       4625.000000
+205     27.000000       5798.000000
+206     27.000000       5814.000000
+207     27.000000       5830.000000
+208     27.000000       5958.000000
+209     27.000000       5974.000000
+210     27.000000       5990.000000
+211     27.000000       6006.000000
+212     27.000000       6022.000000
+213     34.000000       7145.000000
+214     35.000000       7825.000000
+215     49.000000       10765.000000
+216     52.000000       10925.000000
+217     64.000000       13445.000000
+218     64.000000       13915.000000
+219     79.000000       17065.000000
+220     87.000000       18396.000000
+221     87.000000       18412.000000
+222     87.000000       18556.000000
+223     87.000000       18572.000000
+224     93.000000       20005.000000
+225     109.000000      23365.000000
+226     174.000000      36544.000000
+227     184.000000      38644.000000
+228     199.000000      42264.000000
+229     203.000000      42634.000000
+230     207.000000      43571.000000
+231     207.000000      43579.000000
+232     207.000000      43587.000000
+233     207.000000      43595.000000
+234     207.000000      43603.000000
+235     207.000000      43739.000000
+236     207.000000      43747.000000
+237     207.000000      43755.000000
+238     207.000000      43763.000000
+239     207.000000      43779.000000
+240     207.000000      43787.000000
+241     213.000000      44734.000000
+242     214.000000      45414.000000
+243     229.000000      48564.000000
+244     234.000000      49144.000000
+245     245.000000      51454.000000
+246     259.000000      54864.000000
+247     262.000000      55024.000000
+249     4.000000        847.000000
+250     6.000000        1733.000000
+251     20.000000       4673.000000
+252     35.000000       7823.000000
+253     51.000000       11183.000000
+254     65.000000       14123.000000
+255     80.000000       17273.000000
+256     95.000000       20423.000000
+257     109.000000      23363.000000
+258     112.000000      23526.000000
+259     125.000000      26256.000000
+260     125.000000      26723.000000
+261     139.000000      29663.000000
+262     142.000000      29826.000000
+263     154.000000      32346.000000
+264     154.000000      32813.000000
+265     172.000000      36126.000000
+266     176.000000      36970.000000
+267     185.000000      38856.000000
+268     201.000000      42216.000000
+269     214.000000      44946.000000
+270     231.000000      48516.000000
+271     244.000000      51246.000000
+272     261.000000      54816.000000
+
+oframes size = 3        0
+ OFRAMES PRINT
+inside oframes 
+ BEFORE OFRAMES PRINT = 3       137     240     135
+0       15.000000       1586.000000
+1       15.000000       1594.000000
+2       15.000000       1602.000000
+3       15.000000       1610.000000
+4       15.000000       1618.000000
+5       15.000000       1626.000000
+6       15.000000       1634.000000
+7       15.000000       1642.000000
+8       15.000000       1650.000000
+9       15.000000       1658.000000
+10      15.000000       1666.000000
+11      15.000000       1674.000000
+12      15.000000       1682.000000
+13      15.000000       1690.000000
+14      15.000000       1698.000000
+15      15.000000       1706.000000
+16      15.000000       1714.000000
+17      15.000000       1722.000000
+18      15.000000       1730.000000
+19      15.000000       1738.000000
+20      15.000000       1746.000000
+21      15.000000       1754.000000
+22      15.000000       1762.000000
+23      15.000000       1770.000000
+24      15.000000       1778.000000
+25      15.000000       1786.000000
+26      15.000000       1794.000000
+27      15.000000       1802.000000
+28      105.000000      11050.000000
+29      105.000000      11066.000000
+30      105.000000      11082.000000
+31      105.000000      11098.000000
+32      105.000000      11114.000000
+33      105.000000      11130.000000
+34      105.000000      11146.000000
+35      105.000000      11210.000000
+36      105.000000      11226.000000
+37      105.000000      11242.000000
+38      106.000000      11267.000000
+39      106.000000      11283.000000
+40      106.000000      11299.000000
+41      44.000000       4645.000000
+42      45.000000       4758.000000
+43      45.000000       4766.000000
+44      46.000000       4927.000000
+45      46.000000       4959.000000
+46      76.000000       8071.000000
+47      76.000000       8103.000000
+48      77.000000       8256.000000
+49      104.000000      10938.000000
+50      105.000000      11059.000000
+51      106.000000      11228.000000
+52      106.000000      11260.000000
+53      35.000000       3726.000000
+54      92.000000       9756.000000
+68      10.000000       1287.000000
+69      25.000000       2862.000000
+70      43.000000       4561.000000
+71      43.000000       4625.000000
+72      43.000000       4673.000000
+73      43.000000       4689.000000
+74      46.000000       5035.000000
+75      72.000000       7796.000000
+76      73.000000       7709.000000
+77      73.000000       7712.000000
+78      73.000000       7720.000000
+79      73.000000       7725.000000
+80      73.000000       7728.000000
+81      73.000000       7741.000000
+82      73.000000       7744.000000
+83      73.000000       7752.000000
+84      73.000000       7757.000000
+85      73.000000       7773.000000
+86      73.000000       7776.000000
+87      73.000000       7800.000000
+88      73.000000       7805.000000
+89      73.000000       7808.000000
+90      73.000000       7816.000000
+91      73.000000       7821.000000
+92      73.000000       7824.000000
+93      73.000000       7832.000000
+94      73.000000       7837.000000
+95      73.000000       7840.000000
+96      76.000000       8179.000000
+97      76.000000       8216.000000
+98      77.000000       8108.000000
+99      123.000000      12917.000000
+101     9.000000        1180.000000
+102     13.000000       1445.000000
+103     18.000000       1895.000000
+104     24.000000       2755.000000
+105     33.000000       3470.000000
+106     39.000000       4330.000000
+107     43.000000       4593.000000
+108     43.000000       4721.000000
+109     84.000000       8824.000000
+110     100.000000      10734.000000
+111     102.000000      10843.000000
+112     102.000000      10851.000000
+113     102.000000      10853.000000
+114     103.000000      10876.000000
+115     106.000000      11327.000000
+116     108.000000      11344.000000
+117     114.000000      11974.000000
+118     114.000000      12204.000000
+119     124.000000      13024.000000
+120     130.000000      13884.000000
+122     9.000000        1178.000000
+123     12.000000       1416.000000
+124     24.000000       2753.000000
+125     39.000000       4328.000000
+126     54.000000       5903.000000
+127     65.000000       6831.000000
+128     69.000000       7478.000000
+129     79.000000       8301.000000
+130     87.000000       9286.000000
+131     87.000000       9294.000000
+132     95.000000       9981.000000
+133     109.000000      11451.000000
+134     117.000000      12434.000000
+135     117.000000      12442.000000
+136     124.000000      13026.000000
+
+oframes size = 3        0
+ OFRAMES PRINT
+inside oframes 
+ BEFORE OFRAMES PRINT = 3       63      120     68
+0       7.000000        415.000000
+1       8.000000        427.000000
+2       8.000000        435.000000
+3       8.000000        443.000000
+4       8.000000        451.000000
+5       8.000000        459.000000
+6       8.000000        475.000000
+7       8.000000        483.000000
+8       8.000000        491.000000
+9       8.000000        499.000000
+10      8.000000        507.000000
+11      8.000000        515.000000
+12      8.000000        523.000000
+13      52.000000       2721.000000
+14      52.000000       2729.000000
+15      52.000000       2737.000000
+16      52.000000       2745.000000
+17      52.000000       2753.000000
+18      52.000000       2761.000000
+19      52.000000       2801.000000
+20      52.000000       2809.000000
+21      53.000000       2821.000000
+22      53.000000       2829.000000
+23      53.000000       2837.000000
+24      53.000000       2845.000000
+25      66.000000       3528.000000
+26      24.000000       1265.000000
+27      24.000000       1273.000000
+28      24.000000       1337.000000
+29      36.000000       1891.000000
+30      37.000000       1975.000000
+31      37.000000       2015.000000
+32      10.000000       570.000000
+33      12.000000       713.000000
+34      33.000000       1808.000000
+35      50.000000       2650.000000
+36      50.000000       2690.000000
+37      4.000000        323.000000
+38      4.000000        325.000000
+39      12.000000       739.000000
+40      20.000000       1078.000000
+41      64.000000       3330.000000
+42      64.000000       3332.000000
+43      65.000000       3494.000000
+46      19.000000       1103.000000
+47      29.000000       1594.000000
+48      46.000000       2469.000000
+49      55.000000       2864.000000
+52      15.000000       891.000000
+53      18.000000       969.000000
+54      18.000000       1049.000000
+55      20.000000       1072.000000
+56      23.000000       1234.000000
+57      30.000000       1673.000000
+58      36.000000       1882.000000
+59      37.000000       1930.000000
+60      40.000000       2116.000000
+61      55.000000       2866.000000
+62      55.000000       2895.000000
+
+oframes size = 3        0
+ OFRAMES PRINT
+inside oframes 
+ BEFORE OFRAMES PRINT = 3       13      60      34
+2       6.000000        166.000000
+3       6.000000        181.000000
+4       6.000000        196.000000
+5       26.000000       722.000000
+6       30.000000       803.000000
+10      31.000000       810.000000
+11      33.000000       860.000000
+12      33.000000       864.000000
+
+oframes size = 3        0
+ OFRAMES PRINT
+inside oframes 
+Input size              - (1920x1080)
+Cycles elapsed          - 42694634832
+
diff --git a/SD-VBS/benchmarks/sift/data/fullhd/sift b/SD-VBS/benchmarks/sift/data/fullhd/sift
new file mode 100755
index 0000000..dbf91fd
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/fullhd/sift
diff --git a/SD-VBS/benchmarks/sift/data/qcif/1.bmp b/SD-VBS/benchmarks/sift/data/qcif/1.bmp
new file mode 100644
index 0000000..4fdba98
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/qcif/1.bmp
diff --git a/SD-VBS/benchmarks/sift/data/qcif/Makefile b/SD-VBS/benchmarks/sift/data/qcif/Makefile
new file mode 100644
index 0000000..617e3c1
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/qcif/Makefile
@@ -0,0 +1,8 @@
+INPUT=qcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=sift
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
+
diff --git a/SD-VBS/benchmarks/sift/data/qcif/VBS_Ver1 b/SD-VBS/benchmarks/sift/data/qcif/VBS_Ver1
new file mode 100755
index 0000000..6e9d761
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/qcif/VBS_Ver1
diff --git a/SD-VBS/benchmarks/sift/data/qcif/expected.m b/SD-VBS/benchmarks/sift/data/qcif/expected.m
new file mode 100644
index 0000000..265db16
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/qcif/expected.m
@@ -0,0 +1,3 @@
+136.999609      75.999406       83.999897       112.000750      119.999331      122.000419      132.000337      39.000010       51.001873       44.000020       61.999391       14.000416       25.000425       47.998145       33.000173       55.999848       20.001075       21.999253       53.998983       3.998740        4.999613        19.999868       43.000763       14.997708       15.002952       26.998145       19.002013       
+113.000088      76.000660       129.999841      130.999945      109.999738      96.999934       132.000066      139.999331      15.000735       8.999283        17.000513       60.999702       14.000113       50.999175       36.999671       49.000425       52.000482       59.000256       20.997062       4.001153        67.001962       27.999830       31.000904       14.998128       26.998973       15.997683       21.000467       
+0.000275        2.000956        2.000776        1.999298        1.999671        1.999964        2.002015        1.999710        0.000119        1.001356        0.997834        2.002273        2.001115        2.000370        0.001001        0.000664        0.999350        1.000703        1.000935        1.999379        2.004628        1.998750        2.002175        0.000899        0.002673        0.003054        0.999563        
diff --git a/SD-VBS/benchmarks/sift/data/qcif/im1_qcif.tif b/SD-VBS/benchmarks/sift/data/qcif/im1_qcif.tif
new file mode 100755
index 0000000..d6e7b06
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/qcif/im1_qcif.tif
diff --git a/SD-VBS/benchmarks/sift/data/qcif/sift b/SD-VBS/benchmarks/sift/data/qcif/sift
new file mode 100755
index 0000000..90502d9
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/qcif/sift
diff --git a/SD-VBS/benchmarks/sift/data/sim/1.bmp b/SD-VBS/benchmarks/sift/data/sim/1.bmp
new file mode 100644
index 0000000..52b45d6
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sim/1.bmp
diff --git a/SD-VBS/benchmarks/sift/data/sim/Makefile b/SD-VBS/benchmarks/sift/data/sim/Makefile
new file mode 100644
index 0000000..f4682f1
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sim/Makefile
@@ -0,0 +1,7 @@
+INPUT=sim
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=sift
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/sift/data/sim/expected.m b/SD-VBS/benchmarks/sift/data/sim/expected.m
new file mode 100644
index 0000000..c6fa41b
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sim/expected.m
@@ -0,0 +1,3 @@
+38.000255       43.999064       10.997433       22.000307       42.000304       55.002080       24.998365       26.999151       48.002129       17.000593       47.999165       48.999650       17.000126       30.001099       3.996419        37.998273       16.998723       
+6.999158        11.997409       53.999909       10.999926       45.000550       12.999159       46.999620       24.998259       26.999954       45.999281       16.999859       43.000301       24.000730       60.001463       58.998050       26.999739       18.999517       
+-0.001414       -0.000176       0.998619        0.999565        0.997222        1.001923        1.999310        1.999673        1.999408        0.000973        -0.000146       -0.001587       1.001611        1.001263        1.997816        1.999161        0.001112        
diff --git a/SD-VBS/benchmarks/sift/data/sim/out b/SD-VBS/benchmarks/sift/data/sim/out
new file mode 100644
index 0000000..3382a8a
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sim/out
@@ -0,0 +1,64 @@
+Executing Matlab version of the benchmark sift
+sift
+
+                                                                                              < M A T L A B >
+                                                                                  Copyright 1984-2006 The MathWorks, Inc.
+                                                                                        Version 7.3.0.298 (R2006b)
+                                                                                              August 03, 2006
+
+ 
+  To get started, type one of these: helpwin, helpdesk, or demo.
+  For product information, visit www.mathworks.com.
+ 
+Warning: Function /h/g2/kvs/Desktop/VBS_Ver1.1/common/randn.m has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.
+> In path at 113
+  In script_run_profile at 3
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+ We need pathName and fileName as inputs here
+     6
+
+2.015874        1.259921        -1.000000       0.500000        -1.000000       1.249000
+Dsigma for octave  1.259921     0.000000        1.226273        1.226273
+Dsigma for octave  1.259921     1.000000        1.226273        1.545008
+Dsigma for octave  1.259921     2.000000        1.226273        1.946588
+Dsigma for octave  1.259921     3.000000        1.226273        2.452547
+Dsigma for octave  1.259921     4.000000        1.226273        3.090016
+Const Dimensions = 64
+Const Dimensions = 64
+Const Dimensions = 5
+Const Dimensions = 64
+Const Dimensions = 64
+Const Dimensions = 5
+Params here
+    64    64     5
+
+Size of oframes_ = 3    18
+../data/sim/expected.m
+Const Dimensions = 32
+Const Dimensions = 32
+Const Dimensions = 5
+Const Dimensions = 32
+Const Dimensions = 32
+Const Dimensions = 5
+Params here
+    32    32     5
+
+Size of oframes_ = 3    4
+../data/sim/expected.m
diff --git a/SD-VBS/benchmarks/sift/data/sim/outpt b/SD-VBS/benchmarks/sift/data/sim/outpt
new file mode 100644
index 0000000..688b5d9
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sim/outpt
@@ -0,0 +1,3 @@
+gcc -DGCC -DCHECK -Dsim -lm -O2 -I../../../C_common -I../../C ../../../C_common/calcSobel_dX.c ../../../C_common/calcSobel_dY.c ../../../C_common/fDeepCopy.c ../../../C_common/fDeepCopyRange.c ../../../C_common/fDivide.c ../../../C_common/ffConv2.c ../../../C_common/ffConv2_dY.c ../../../C_common/ffDivide.c ../../../C_common/ffiConv2.c ../../../C_common/fFind3.c ../../../C_common/ffTimes.c ../../../C_common/ffVertcat.c ../../../C_common/fHorzcat.c ../../../C_common/fiConv2.c ../../../C_common/fiDeepCopy.c ../../../C_common/fMallocHandle.c ../../../C_common/fMdivide.c ../../../C_common/fMinus.c ../../../C_common/fMtimes.c ../../../C_common/fPlus.c ../../../C_common/fReshape.c ../../../C_common/fSelfCheck.c ../../../C_common/fSetArray.c ../../../C_common/fSort.c ../../../C_common/fSortIndices.c ../../../C_common/fSum2.c ../../../C_common/fSum.c ../../../C_common/fTimes.c ../../../C_common/fTranspose.c ../../../C_common/fWriteMatrix.c ../../../C_common/horzcat.c ../../../C_common/iDeepCopy.c ../../../C_common/iDeepCopyRange.c ../../../C_common/ifDeepCopy.c ../../../C_common/iHorzcat.c ../../../C_common/iiConv2.c ../../../C_common/imageBlur.c ../../../C_common/imageResize.c ../../../C_common/iMallocHandle.c ../../../C_common/iMinus.c ../../../C_common/iReshape.c ../../../C_common/iSetArray.c ../../../C_common/isMinus.c ../../../C_common/iSort.c ../../../C_common/iSortIndices.c ../../../C_common/isPlus.c ../../../C_common/iTimes.c ../../../C_common/iTranspose.c ../../../C_common/makeImage.c ../../../C_common/photonEndTiming.c ../../../C_common/photonPrintTiming.c ../../../C_common/photonReportTiming.c ../../../C_common/photonStartTiming.c ../../../C_common/randnWrapper.c ../../../C_common/randWrapper.c ../../../C_common/readFile.c ../../../C_common/readImage.c ../../../C_common/selfCheck.c ../../C/diffss.c ../../C/doubleSize.c ../../C/fHalveSize.c ../../C/filter_boundary_points.c ../../C/gaussianss.c ../../C/iHalveSize.c ../../C/imsmooth.c ../../C/script_sift.c ../../C/sift.c ../../C/siftlocalmax.c ../../C/siftrefinemx.c -o sift
+Running C Version of the benchmark
+./sift ../../data/sim ../result
diff --git a/SD-VBS/benchmarks/sift/data/sim/sift b/SD-VBS/benchmarks/sift/data/sim/sift
new file mode 100755
index 0000000..54a4156
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sim/sift
diff --git a/SD-VBS/benchmarks/sift/data/sim_fast/1.bmp b/SD-VBS/benchmarks/sift/data/sim_fast/1.bmp
new file mode 100644
index 0000000..b7f0f28
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sim_fast/1.bmp
diff --git a/SD-VBS/benchmarks/sift/data/sim_fast/Makefile b/SD-VBS/benchmarks/sift/data/sim_fast/Makefile
new file mode 100644
index 0000000..1f2273f
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sim_fast/Makefile
@@ -0,0 +1,7 @@
+INPUT=sim_fast
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=sift
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/sift/data/sim_fast/expected.m b/SD-VBS/benchmarks/sift/data/sim_fast/expected.m
new file mode 100644
index 0000000..dc3d5d5
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sim_fast/expected.m
@@ -0,0 +1,3 @@
+16.003646       
+18.997463       
+0.001157        
diff --git a/SD-VBS/benchmarks/sift/data/sim_fast/sift b/SD-VBS/benchmarks/sift/data/sim_fast/sift
new file mode 100755
index 0000000..54a4156
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sim_fast/sift
diff --git a/SD-VBS/benchmarks/sift/data/sqcif/1.bmp b/SD-VBS/benchmarks/sift/data/sqcif/1.bmp
new file mode 100644
index 0000000..e81e1fc
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sqcif/1.bmp
diff --git a/SD-VBS/benchmarks/sift/data/sqcif/Makefile b/SD-VBS/benchmarks/sift/data/sqcif/Makefile
new file mode 100644
index 0000000..1d4e009
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sqcif/Makefile
@@ -0,0 +1,7 @@
+INPUT=sqcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=sift
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/sift/data/sqcif/expected.m b/SD-VBS/benchmarks/sift/data/sqcif/expected.m
new file mode 100644
index 0000000..140643b
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sqcif/expected.m
@@ -0,0 +1,3 @@
+183.000403      51.001171       55.999927       79.999487       87.000171       88.000835       73.999127       57.999392       67.000131       44.000999       74.001196       26.999298       43.999218       72.001323       8.998266        17.001107       31.999034       40.995249       19.998951       20.003080       35.998479       13.001442       35.001360       28.997337       25.999158       31.000511       
+150.000063      49.999426       87.000198       72.999307       51.999937       88.000170       87.000970       12.000201       18.999405       48.000347       66.000128       69.000323       49.999689       27.000191       41.000470       9.000107        33.999173       10.999689       19.999543       35.999525       20.998161       18.998984       14.001576       20.998481       28.000519       43.994983       
+1.000056        -0.000244       0.000069        -0.001128       0.000711        0.000815        1.004050        2.000387        2.001282        1.000891        1.001405        2.000524        1.999328        2.001783        0.000885        0.000626        -0.001537       0.004831        0.999517        1.000593        1.001016        -0.000170       -0.000697       0.997790        2.001555        1.997893        
diff --git a/SD-VBS/benchmarks/sift/data/sqcif/sift b/SD-VBS/benchmarks/sift/data/sqcif/sift
new file mode 100755
index 0000000..90502d9
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/sqcif/sift
diff --git a/SD-VBS/benchmarks/sift/data/test/1.bmp b/SD-VBS/benchmarks/sift/data/test/1.bmp
new file mode 100644
index 0000000..c108692
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/test/1.bmp
diff --git a/SD-VBS/benchmarks/sift/data/test/Makefile b/SD-VBS/benchmarks/sift/data/test/Makefile
new file mode 100644
index 0000000..b447b82
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/test/Makefile
@@ -0,0 +1,6 @@
+INPUT=test
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=sift
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/sift/data/test/expected.m b/SD-VBS/benchmarks/sift/data/test/expected.m
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/test/expected.m
diff --git a/SD-VBS/benchmarks/sift/data/test/sift b/SD-VBS/benchmarks/sift/data/test/sift
new file mode 100755
index 0000000..5c6751c
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/test/sift
diff --git a/SD-VBS/benchmarks/sift/data/vga/1.bmp b/SD-VBS/benchmarks/sift/data/vga/1.bmp
new file mode 100644
index 0000000..a290698
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/vga/1.bmp
diff --git a/SD-VBS/benchmarks/sift/data/vga/Makefile b/SD-VBS/benchmarks/sift/data/vga/Makefile
new file mode 100644
index 0000000..e5d965a
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/vga/Makefile
@@ -0,0 +1,7 @@
+INPUT=vga
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=sift
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/sift/data/vga/expected.m b/SD-VBS/benchmarks/sift/data/vga/expected.m
new file mode 100644
index 0000000..370de8f
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/vga/expected.m
@@ -0,0 +1,3 @@
+4.001077        64.000256       71.000653       101.000887      102.000626      109.999989      92.999469       56.000010       93.000993       37.000265       41.999736       52.000374       12.001936       21.000447       39.997204       25.001418       26.000761       44.998359       16.999495       45.994780       4.002647        16.999300       44.000076       36.000974       48.999853       
+235.996913      62.999531       108.999989      91.999832       80.999901       109.999804      109.000675      60.000270       83.000089       8.000430        11.998686       14.000111       50.999512       12.000354       43.000622       44.999225       25.000619       26.999477       43.999443       16.997934       56.003364       23.000953       17.999300       26.000489       3.997675        
+1.997221        0.999963        1.000744        0.999331        0.999509        1.001213        2.004579        2.000446        2.001272        -0.000525       0.000666        -0.004113       1.000090        1.000093        0.999601        2.001059        2.000230        2.000452        0.000450        -0.002223       1.006566        1.000414        0.998869        1.998115        2.003538        
diff --git a/SD-VBS/benchmarks/sift/data/vga/sift b/SD-VBS/benchmarks/sift/data/vga/sift
new file mode 100755
index 0000000..54a4156
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/data/vga/sift
diff --git a/SD-VBS/benchmarks/sift/src/c/diffss.c b/SD-VBS/benchmarks/sift/src/c/diffss.c
new file mode 100644
index 0000000..683cbe7
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/diffss.c
@@ -0,0 +1,53 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "sift.h"
+
+/**
+    DIFFSS  Difference of scale space
+    Returns a scale space DSS obtained by subtracting
+    consecutive levels of the scale space SS.
+
+    In SIFT, this function is used to compute the difference of
+    Gaussian scale space from the Gaussian scale space of an image.
+**/
+
+F2D** diffss(F2D** ss, int num, int intervals)
+{
+    F2D** dss;
+    int o, sizeM, sizeN, s, i, j; 
+    F2D *current, *in1, *in2;
+
+    dss = malloc(num*intervals*sizeof(F2D*));
+
+    for(o=0; o<num; o++)
+    {
+        for(s=0; s<(intervals-1); s++)
+        {
+            sizeM = ss[o*intervals+s]->height;
+            sizeN = ss[o*intervals+s]->width;
+
+            dss[o*intervals+s] = fMallocHandle(sizeM, sizeN);
+
+            current = dss[o*intervals+s];
+            in1 = ss[o*intervals+s+1];
+            in2 = ss[o*intervals+s];
+            
+            for(i=0; i<sizeM; i++)
+            {
+                for(j=0; j<sizeN; j++)
+                {
+                    subsref(current,i,j) = subsref(in1,i,j) - subsref(in2,i,j);
+                }
+            }
+        }
+    }
+
+    return dss;
+
+}
+
+
+
+
diff --git a/SD-VBS/benchmarks/sift/src/c/doubleSize.c b/SD-VBS/benchmarks/sift/src/c/doubleSize.c
new file mode 100644
index 0000000..dd17f77
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/doubleSize.c
@@ -0,0 +1,55 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "sift.h"
+
+F2D* doubleSize(F2D* I)
+{
+    F2D *J;
+    int M, N, i, j;
+
+    M = I->height;
+    N = I->width;
+    J = fSetArray(2*M, 2*N, 0);
+
+    for(i=0; i<M; i++)
+    {
+        for(j=0; j<N; j++)
+        {
+            subsref(J,2*i,j*2) = subsref(I,i,j);
+        }
+    }
+    
+    for(i=0; i<M-1; i++)
+    {
+        for(j=0; j<N-1; j++)
+        {
+            subsref(J,i*2+1,j*2+1) = (0.25 * (subsref(I,i,j) + subsref(I,i+1,j) + subsref(I,i,j+1) + subsref(I,(i+1),j+1)));
+        }
+    }
+
+    for(i=0; i<M-1; i++)
+    {
+        for(j=0; j<N; j++)
+        {
+            subsref(J,i*2+1,j*2) = (0.5 * (subsref(I,i,j) + subsref(I,i+1,j)));
+        }
+    }
+   
+    for(i=0; i<M; i++)
+    {
+        for(j=0; j<N-1; j++)
+        {
+            subsref(J,i*2,j*2+1) = (0.5 * (subsref(I,i,j) + subsref(I,i,j+1)));
+        }
+    }
+    
+    return J;
+}
+
+
+
+
+
+
diff --git a/SD-VBS/benchmarks/sift/src/c/filterBoundaryPoints.c b/SD-VBS/benchmarks/sift/src/c/filterBoundaryPoints.c
new file mode 100644
index 0000000..c68e717
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/filterBoundaryPoints.c
@@ -0,0 +1,61 @@
+#include "sift.h"
+
+/**
+    Filter out points on the boundaries. 
+    The function returns oframes, which
+    contains the row, col and the interval number 
+**/
+
+F2D* filterBoundaryPoints(int M, int N, F2D* oframes) 
+{
+    int i, k=0, m=0;
+        int cnt;
+    I2D* sel;
+    F2D *ret;
+    
+    cnt = 0;
+    for(i=0; i<oframes->width; i++)
+        {
+        if(asubsref(oframes,i)>3 && asubsref(oframes,i)<(N-3) && 
+                        subsref(oframes,1,i)>3 && subsref(oframes,1,i)<(M-3))
+                {
+            cnt++;
+                }
+        }
+
+    sel = iSetArray(cnt, 1, 0);
+    for(i=0; i<oframes->width; i++)
+    {
+        if(asubsref(oframes,i)>3 && asubsref(oframes,i)<(N-3) && 
+                        subsref(oframes,1,i)>3 && subsref(oframes,1,i)<(M-3))
+        {
+            asubsref(sel,k) = i;
+            k++;
+        }
+        m++;
+    }
+   
+    if( sel->height > 0)
+    {
+        ret = fSetArray(oframes->height, sel->height, 0);
+        {
+            for(i=0; i<sel->height; i++)
+            {
+                subsref(ret,0,i) = subsref(oframes,0,asubsref(sel,i));
+                subsref(ret,1,i) = subsref(oframes,1,asubsref(sel,i));
+                subsref(ret,2,i) = subsref(oframes,2,asubsref(sel,i));
+            }
+        }
+    }
+    else
+        ret = fSetArray(1,1,0);
+
+    iFreeHandle(sel);
+    return ret;
+}
+
+
+
+
+
+
diff --git a/SD-VBS/benchmarks/sift/src/c/gaussianss.c b/SD-VBS/benchmarks/sift/src/c/gaussianss.c
new file mode 100644
index 0000000..52dd95b
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/gaussianss.c
@@ -0,0 +1,185 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "sift.h"
+
+F2D* resizeArray(F2D* array, int omin) 
+{
+        F2D* prev = NULL;
+        F2D* current = array;
+        int o;
+    if(omin<0)
+    {
+        for(o=1; o>=-omin; o--)
+        {
+                        prev = current;
+            current = doubleSize(current);
+                        fFreeHandle(prev);
+        }
+    }
+    if(omin>0)
+    {
+        for(o=1; o<= omin; o++)
+                {
+                        prev = current;
+            current = halveSize(current);
+                        fFreeHandle(prev);
+                }
+    }
+        return current;
+}
+
+/**
+    Returns the Gaussian scale space of image I. Image I is assumed to be
+    pre-smoothed at level SIGMAN. O,S,OMIN,SMIN,SMAX,SIGMA0 are the
+    parameters of the scale space.
+**/
+
+F2D** gaussianss(F2D* array, float sigman, int O, int S, int omin, int smin, int smax, float sigma0)
+{
+   /* We compute the following items in the function
+    1. Smooth input image per octave
+    2. Smooth each octave for different intervals
+    3. Subtract each "interval-1" smooth image from "interval" image per octave. So, per octave, we have "interval" * DOG images.
+    4. So, octave * intervals * image
+    5. Note: At each octave, the image is scaled down in both x and y directions
+    */
+
+    float k, dsigma0, dsigma;
+    int s, i, j, o, so, M, N, sbest;
+    int intervals = smax-smin+1;
+    float temp, target_sigma, prev_sigma;
+    F2D *TMP, **gss;
+    F2D* I = array;
+
+    // Scale multiplicative step
+    k = pow(2, (1.0/S));
+    dsigma0 = sigma0 * sqrt(1-(1.0/pow(k,2)));  // Scale step factor
+    
+    // If omin < 0, multiply the size of the image.
+        I = resizeArray(I, omin);
+    M = I->height;
+    N = I->width;
+    so = -smin+1;       // Index offset
+
+    gss = malloc(O*intervals*sizeof(F2D*));
+    if(gss == NULL)
+    {
+        printf("Could not allocate memory\n");
+        return NULL;
+    }
+
+/**
+                                                         First octave
+--------------------------------------------------------------------
+
+The first level of the first octave has scale index (o,s) =
+(omin,smin) and scale coordinate
+
+    sigma(omin,smin) = sigma0 2^omin k^smin 
+
+The input image I is at nominal scale sigman. Thus in order to get
+the first level of the pyramid we need to apply a smoothing of
+  
+    sqrt( (sigma0 2^omin k^smin)^2 - sigman^2 ).
+
+As we have pre-scaled the image omin octaves (up or down,
+depending on the sign of omin), we need to correct this value
+by dividing by 2^omin, getting
+
+   sqrt( (sigma0 k^smin)^2 - (sigman/2^omin)^2 )
+
+**/
+
+    temp = sqrt(pow((sigma0*pow(k,smin)),2) - pow((sigman/pow(2,omin)),2));
+
+    {
+        gss[0] = fSetArray(I->height, I->width, 0);
+        imsmooth(I, temp, gss[0] );
+    }
+
+    for(s=smin; s<smax; s++)
+    {
+        
+    /**
+        Here we go from (omin,s-1) to (omin,s). The extra smoothing
+            standard deviation is
+        
+            (sigma0 2^omin 2^(s/S) )^2 - (simga0 2^omin 2^(s/S-1/S) )^2
+        
+            After dividing by 2^omin (to take into account the fact
+        that the image has been pre-scaled omin octaves), the 
+        standard deviation of the smoothing kernel is
+  
+            dsigma = sigma0 k^s sqrt(1-1/k^2)
+    **/
+    
+        dsigma = pow(k,s+1) * dsigma0;
+        gss[s+so] = fSetArray(gss[s+so-1]->height, gss[s+so-1]->width, 0);
+        imsmooth( gss[(s+so-1)] , dsigma, gss[(s+so)] );
+    }     
+    
+    /** Other octaves **/
+    
+    for(o=1; o<O; o++)
+    {
+        /**
+            We need to initialize the first level of octave (o,smin) from
+                the closest possible level of the previous octave. A level (o,s)
+            in this octave corrsponds to the level (o-1,s+S) in the previous
+            octave. In particular, the level (o,smin) correspnds to
+            (o-1,smin+S). However (o-1,smin+S) might not be among the levels
+            (o-1,smin), ..., (o-1,smax) that we have previously computed.
+            The closest pick is
+  
+                                       /  smin+S    if smin+S <= smax
+                (o-1,sbest) , sbest = |
+                                   \  smax      if smin+S > smax
+        
+                The amount of extra smoothing we need to apply is then given by
+        
+                ( sigma0 2^o 2^(smin/S) )^2 - ( sigma0 2^o 2^(sbest/S - 1) )^2
+        
+            As usual, we divide by 2^o to cancel out the effect of the
+            downsampling and we get
+
+                ( sigma 0 k^smin )^2 - ( sigma0 2^o k^(sbest - S) )^2
+        **/
+
+        sbest = MIN(smin+S-1, smax-1);
+        TMP = halveSize( gss[(o-1)*intervals+sbest+so]);
+        target_sigma = sigma0 * pow(k,smin);
+        prev_sigma = sigma0 * pow(k, (sbest+1)-S);
+
+        temp = sqrt(pow(target_sigma,2) - pow(prev_sigma, 2));
+        if(target_sigma > prev_sigma)
+        {
+            gss[o*intervals] = fSetArray(TMP->height, TMP->width, 0);
+            imsmooth(TMP, temp, gss[o*intervals] );
+        }
+        else
+        {
+            int i;
+            gss[o*intervals] = fSetArray(TMP->height, TMP->width, 0);
+            for(i=0; i<(TMP->height*TMP->width); i++)
+                asubsref(gss[o*intervals],i) = asubsref(TMP,i);
+        }
+
+        M = TMP->height;
+        N = TMP->width;
+
+        fFreeHandle(TMP);
+
+        for(s=smin; s<smax; s++)
+        {
+                    // The other levels are determined as above for the first octave.           
+            dsigma = pow(k,s+1) * dsigma0;
+            gss[o*intervals+s+so] = fSetArray(gss[o*intervals+s-1+so]->height, gss[o*intervals+s-1+so]->width, 0);
+            imsmooth( gss[o*intervals+s-1+so] , dsigma, gss[o*intervals+s+so]);
+        }    
+    }
+
+    fFreeHandle(I);
+    return gss;
+}
diff --git a/SD-VBS/benchmarks/sift/src/c/halveSize.c b/SD-VBS/benchmarks/sift/src/c/halveSize.c
new file mode 100644
index 0000000..fe1e536
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/halveSize.c
@@ -0,0 +1,35 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "sift.h"
+
+F2D* halveSize(F2D* I)
+{
+    F2D *J;
+    int i, j, k;
+    int hM, hN;
+    int M, N;
+
+    M = I->height;
+    N = I->width;
+    
+    hM = (M+1)/2;
+    hN = (N+1)/2;
+
+    J = fSetArray(hM, hN, 0.0);
+
+    k = 0;
+    for(i=0; i<M; i+=2)
+    {
+        for(j=0; j<N; j+=2)
+        {
+            asubsref(J,k++) = subsref(I,i,j);
+        }
+    }
+
+    return J;
+}
+
diff --git a/SD-VBS/benchmarks/sift/src/c/imsmooth.c b/SD-VBS/benchmarks/sift/src/c/imsmooth.c
new file mode 100644
index 0000000..d901418
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/imsmooth.c
@@ -0,0 +1,104 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "sift.h"
+#include <math.h>
+#include <assert.h>
+const double win_factor = 1.5 ;
+const int nbins = 36 ;
+const float threshold = 0.01;
+
+/**
+    This function is similar to imageBlur in common/c folder.
+    Here, we can specify the sigma value for the gaussian filter
+    function.
+**/
+
+void imsmooth(F2D* array, float dsigma, F2D* out)
+{
+  int M,N ;
+  int i,j,k;
+  float s ;
+
+  /* ------------------------------------------------------------------
+  **                                                Check the arguments
+  ** --------------------------------------------------------------- */ 
+
+    M = array->height;
+    N = array->width;
+    s = dsigma;
+    
+  /* ------------------------------------------------------------------
+  **                                                         Do the job
+  ** --------------------------------------------------------------- */ 
+  if(s > threshold) 
+  {
+    int W = (int) ceil(4*s) ;
+    float temp[2*W+1];
+    F2D* buffer;
+    float acc = 0.0;
+   
+    buffer = fSetArray(M,N,0);
+    
+    for(j = 0 ; j < (2*W+1) ; ++j) 
+    {
+      temp[j] = (float)(expf(-0.5 * (j - W)*(j - W)/(s*s))) ;
+      acc += temp[j];
+    }
+
+    for(j = 0 ; j < (2*W+1) ; ++j) 
+    {
+      temp[j] /= acc ;
+    }
+    
+    /*
+    ** Convolve along the columns
+    **/
+
+    for(j = 0 ; j < M ; ++j) 
+    {
+      for(i = 0 ; i < N ; ++i) 
+      {
+        int startCol = MAX(i-W,0);
+        int endCol = MIN(i+W, N-1);
+        int filterStart = MAX(0, W-i);
+
+                assert(j < array->height);
+                assert(j < buffer->height);
+                assert(i < buffer->width);
+        for(k=startCol; k<=endCol; k++) {
+                        assert(k < array->width);
+                        assert(filterStart < 2*W+1);
+            subsref(buffer,j,i) += subsref(array, j, k) * temp[filterStart++];
+                }
+      }
+    }
+ 
+    /*
+    ** Convolve along the rows
+    **/
+    for(j = 0 ; j < M ; ++j) 
+    {
+      for(i = 0 ; i < N ; ++i) 
+      {
+        int startRow = MAX(j-W,0);
+        int endRow = MIN(j+W, M-1);
+        int filterStart = MAX(0, W-j);
+        for(k=startRow; k<=endRow; k++)
+            subsref(out,j,i) += subsref(buffer,k,i) * temp[filterStart++];
+      }
+    }  
+  
+    fFreeHandle(buffer);
+      
+  } 
+  else 
+  {
+      for(i=0;i<M*N;i++)
+          asubsref(out, i) = asubsref(array, i);
+  }
+
+
+  return;
+}
diff --git a/SD-VBS/benchmarks/sift/src/c/script_sift.c b/SD-VBS/benchmarks/sift/src/c/script_sift.c
new file mode 100644
index 0000000..0b2f106
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/script_sift.c
@@ -0,0 +1,83 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "sift.h"
+#include <malloc.h>
+#include "extra.h"
+#define SIFT_MEM 1<<29
+void normalizeImage(F2D* image)
+{
+        int i;
+        int rows;
+        int cols;
+ 
+    int tempMin = 10000, tempMax = -1;
+        rows = image->height;
+        cols = image->width;
+
+    for(i=0; i<(rows*cols); i++)
+        if(tempMin > asubsref(image,i))
+            tempMin = asubsref(image,i);
+
+    for(i=0; i<(rows*cols); i++)
+        asubsref(image,i) = asubsref(image,i) - tempMin;
+
+    for(i=0; i<(rows*cols); i++)
+        if(tempMax < asubsref(image,i))
+            tempMax = asubsref(image,i);
+
+    for(i=0; i<(rows*cols); i++)
+        asubsref(image,i) = ( asubsref(image,i) / (tempMax+0.0) );
+}
+
+int main(int argc, char* argv[])
+{
+    SET_UP
+    mallopt(M_TOP_PAD, SIFT_MEM);
+    mallopt(M_MMAP_MAX, 0);
+    I2D* im;
+    F2D *image;
+    int rows, cols, i, j;
+    F2D* frames;
+    unsigned int* startTime, *endTime, *elapsed;    
+    
+    char imSrc[100];
+    printf("Input image: ");
+    scanf("%s", imSrc);
+    im = readImage(imSrc);
+    image = fiDeepCopy(im);
+    rows = image->height;
+    cols = image->width;
+
+
+    printf("start\n");
+    for_each_job{
+        image = fiDeepCopy(im);
+        normalizeImage(image);
+        /** Extract sift features for the normalized image **/
+        frames = sift(image);
+    }
+    printf("end..\n");
+   
+#ifdef CHECK   
+    {
+        int ret=0;
+        float tol = 0.2;
+#ifdef GENERATE_OUTPUT
+        fWriteMatrix(frames, argv[1]);
+#endif
+        ret = fSelfCheck(frames, "expected_C.txt", tol);
+        if (ret == -1)
+            printf("Error in SIFT\n");
+    }
+#endif    
+
+    iFreeHandle(im);
+    fFreeHandle(frames);
+    WRITE_TO_FILE
+    return 0;
+}
+
diff --git a/SD-VBS/benchmarks/sift/src/c/sift.c b/SD-VBS/benchmarks/sift/src/c/sift.c
new file mode 100644
index 0000000..ea0d308
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/sift.c
@@ -0,0 +1,314 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <math.h>
+#include "sift.h"
+
+/** SIFT- Scale Invariant Feature Transform. This algorithm is based on
+    David Lowe's implementation of sift. So, we will use the parameter
+    values from Lowe's implementation.
+    See: http://www.cs.ubc.ca/~lowe/keypoints/
+
+    SIFT extracts from an image a collection of frames or keypoints. These
+    are oriented disks attacked to blob-like structures of the image. As
+    the image translates, rotates and scales, the frames track these blobs 
+    and the deformation.
+
+    'BoundaryPoint' [bool]
+    If set to 1, frames too close to the image boundaries are discarded.
+    
+    'Sigma0' [pixels]
+    Smoothing of the level 0 of octave 0 of the scale space.
+    (Note that Lowe's 1.6 value refers to the level -1 of octave 0.)
+
+    'SigmaN' [pixels]
+    Nominal smoothing of the input image. Typically set to 0.5.
+
+    'Threshold'
+    Threshold used to eliminate weak keypoints. Typical values for
+    intensity images in the range [0,1] are around 0.01. Smaller
+    values mean more keypoints.
+
+**/
+
+F2D* sift(F2D* I)
+{
+    int rows, cols, K;
+    int subLevels, omin, Octaves, r, NBP, NBO, smin, smax, intervals, o;
+    float sigma, sigman, sigma0, thresh, magnif;
+    int discardBoundaryPoints;
+    F2D *descriptors;
+    F2D **gss, *tfr;
+    F2D **dogss;
+    I2D* i_, *j_, *s_;
+    F2D *oframes, *frames;
+    int i, j, k, m, startRow, startCol, endRow, endCol, firstIn=1;
+    float minVal;
+    I2D* tx1, *ty1, *ts1;
+    I2D* x1, *y1, *s1, *txys;
+
+    rows = I->height;
+    cols = I->width;
+
+    /** 
+    Lowe's choices
+    Octaves - octave
+    subLevels - sub-level for image
+    sigma - sigma value for gaussian kernel, for smoothing the image
+    At each successive octave, the data is spatially downsampled by half
+    **/
+
+    subLevels = 3;
+    omin = -1;
+    minVal = log2f(MIN(rows,cols));
+    Octaves = (int)(floor(minVal))-omin-4;   /* Upto 16x16 images */
+    sigma0 = 1.6 * pow(2, (1.0/subLevels));
+    sigman = 0.5;
+    thresh = (0.04/subLevels)/2;
+    r = 10;
+
+#ifdef test
+    subLevels = 1;
+    Octaves = 1;
+    sigma0 = pow(0.6 * 2, 1);
+    sigman = 1.0;
+    thresh = (1/subLevels)/2;
+    r = 1;
+#endif
+
+    NBP = 4;
+    NBO = 8 ;
+    magnif = 3.0 ;
+    discardBoundaryPoints = 1 ;
+
+    smin = -1;
+    smax = subLevels+1;
+    intervals = smax - smin + 1;
+
+    /** 
+        We build gaussian pyramid for the input image. Given image I,
+        we sub-sample the image into octave 'Octaves' number of levels. At 
+        each level, we smooth the image with varying sigman values.
+        
+        Gaussiam pyramid can be assumed as a 2-D matrix, where each
+        element is an image. Number of rows corresponds to the number
+        of scales of the pyramid (octaves, "Octaves"). Row 0 (scale 0) is the 
+        size of the actual image, Row 1 (scale 1) is half the actual 
+        size and so on.
+
+        At each scale, the image is smoothened with different sigma values.
+        So, each row has "intervals" number of smoothened images, starting
+        with least blurred.
+        
+        gss holds the entire gaussian pyramid. 
+    **/
+
+    gss = gaussianss(I, sigman, Octaves, subLevels, omin, -1, subLevels+1, sigma0);
+
+    /** 
+        Once we build the gaussian pyramid, we compute DOG, the 
+        Difference of Gaussians. At every scale, we do:
+
+        dogss[fixedScale][0] = gss[fixedScale][1] - gss[fixedScale][0]
+
+        Difference of gaussian gives us edge information, at each scale.
+        In order to detect keypoints on the intervals per octave, we 
+        inspect DOG images at highest and lowest scales of the octave, for
+        extrema detection.
+    **/
+    
+    dogss = diffss(gss, Octaves, intervals);
+
+    /** The extraction of keypoints is carried one octave per time **/
+    for(o=0; o<Octaves; o++)
+    {
+        F2D *temp;
+        F2D *t;
+        F2D *negate;
+        F2D *idxf, *idxft;
+        I2D *idx;
+        int i1, j1;
+        I2D *s, *i, *j, *x, *y;
+        int sizeRows = dogss[o*intervals]->height;
+        int sizeCols = dogss[o*intervals]->width;
+        
+        {
+            int i,j,k=0;
+            temp = fMallocHandle(intervals-1, sizeRows*sizeCols);
+            negate = fMallocHandle(intervals-1, sizeRows*sizeCols);
+
+            /** 
+                Keypoints are detected as points of local extrema of the
+                DOG pyramid, at a given octave. In softlocalmax function, the
+                keypoints are extracted by looking at 9x9x9 neighborhood samples.
+                
+                We populate temp and negate arrays with the values of the DOG
+                pyramid for a given octave, o. Since we are interested in both
+                local maxima and minima, we compute negate matrix, which is the
+                negated values of the DOG pyramid.
+            
+            **/
+
+            for(i1=0; i1<(intervals-1); i1++)
+            {
+                for(j=0; j<sizeCols; j++)
+                {
+                    for(i=0; i<sizeRows; i++)
+                    {
+                        asubsref(temp,k) = subsref(dogss[o*intervals+i1],i,j);
+                        asubsref(negate,k++) = -subsref(dogss[o*intervals+i1],i,j);
+                    }
+                }
+            }
+        }
+        
+        /**
+            siftlocalmax returns indices k, that correspond to local maxima and 
+            minima. 
+                The 80% tricks discards early very weak points before refinement.
+        **/
+        idxf = siftlocalmax( temp, 0.8*thresh, intervals, sizeRows, sizeCols);
+        t = siftlocalmax( negate, 0.8*thresh, intervals, sizeRows, sizeCols);
+        
+        idxft = fHorzcat(idxf, t);
+
+        /**
+            Since indices is the 1-D index of the temp/negate arrays, we compute 
+            the x,y and intervals(s) co-ordinates corresponding to each index.
+        **/
+        
+        idx = ifDeepCopy(idxft);
+        
+        x = iSetArray(idx->height,idx->width,0);
+        y = iSetArray(idx->height,idx->width,0);
+        s_ = iSetArray(idx->height,idx->width,0);
+        
+        {
+            int i, j;
+            for(i=0; i<idx->height; i++)
+             {
+                 for(j=0; j<idx->width; j++)
+                 {
+                    int v, u, w, z;
+                    w = subsref(idx,i,j);
+                    v = ceil((w/(sizeRows*sizeCols)) + 0.5);
+                    u = floor(w/(sizeRows*sizeCols));
+                    z = w - (sizeRows*sizeCols*u);
+                    
+                    /** v is the interval number, s **/
+                    subsref(s_,i,j) = v;
+                    /** row number of the index **/
+                    subsref(y,i,j) = ceil((z / sizeRows)+0.5);
+                    /** col number of the index **/
+                    subsref(x,i,j) = z - (sizeCols * floor(z / sizeRows));
+                 }
+             }
+        }
+
+        {
+            
+            tx1 = isMinus(x, 1);
+            x1 = iReshape(tx1, 1, (tx1->height*tx1->width));
+
+            ty1 = isMinus(y, 1);
+            y1 = iReshape(ty1, 1, (ty1->height*ty1->width));
+
+            ts1 = isPlus(s_, (smin-1));
+            s1 = iReshape(ts1, 1, (ts1->height*ts1->width));
+        
+            txys = iVertcat(y1, x1);
+            i_ = iVertcat(txys, s1);
+        }
+
+        /**
+            Stack all x,y,s into oframes.
+            Row 0 of oframes = x
+            Row 1 of oframes = y
+            Row 2 of oframes = s
+        **/
+        oframes = fiDeepCopy(i_);
+         
+        {
+            int i,j;
+            F2D* temp;
+            temp = oframes;
+                
+            /** 
+                Remove points too close to the boundary
+            **/
+            
+            if(discardBoundaryPoints)
+                oframes = filterBoundaryPoints(sizeRows, sizeCols, temp);
+            fFreeHandle(temp);
+        }
+        
+        /**
+            Refine the location, threshold strength and remove points on edges
+        **/
+        if( asubsref(oframes,0) != 0)
+        {
+            F2D* temp_;
+            temp_ = fTranspose(oframes);
+            fFreeHandle(oframes);
+            oframes = siftrefinemx(temp_, temp, smin, thresh, r, sizeRows, sizeCols, intervals-1);
+            fFreeHandle(temp_);
+
+            if( firstIn == 0)
+            {
+                tfr = fDeepCopy(frames);
+                fFreeHandle(frames);
+                frames = fHorzcat(tfr, oframes);
+                fFreeHandle(tfr);
+            }
+            else
+                frames = fDeepCopy(oframes);
+            firstIn = 0;
+        }
+        else if(Octaves == 1)
+            frames = fDeepCopy(oframes);
+        
+        fFreeHandle(oframes);
+        iFreeHandle(y);
+        iFreeHandle(x);
+        iFreeHandle(s_);
+        iFreeHandle(y1);
+        iFreeHandle(x1);
+        iFreeHandle(s1);
+        iFreeHandle(ty1);
+        iFreeHandle(tx1);
+        iFreeHandle(ts1);
+        iFreeHandle(txys);
+        iFreeHandle(i_);
+        iFreeHandle(idx);
+        fFreeHandle(idxf);
+        fFreeHandle(idxft);
+        fFreeHandle(temp);
+        fFreeHandle(t);
+        fFreeHandle(negate);
+    }
+
+    { int s;
+    for(o=0; o<Octaves; o++)
+    {
+        for(s=0; s<(intervals-1); s++)
+        {
+            fFreeHandle(dogss[o*intervals+s]);
+        }
+    }
+    for(o=0; o<Octaves; o++)
+    {
+        for(s=0; s<(intervals); s++)
+        {
+            fFreeHandle(gss[o*intervals+s]);
+        }
+    }
+    }
+    free(gss);
+    free(dogss);
+   
+    return frames;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/sift/src/c/sift.h b/SD-VBS/benchmarks/sift/src/c/sift.h
new file mode 100644
index 0000000..e8a4ee0
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/sift.h
@@ -0,0 +1,27 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#ifndef _SIFT_
+#define _SIFT_
+
+#include "sdvbs_common.h"
+#include <assert.h>
+
+#define GREATER(a,b) ((a) > (b))
+#define MAX(a,b) (((a)>(b))?(a):(b))
+#define MIN(a,b) (((a)<(b))?(a):(b))
+
+F2D* sift(F2D* I);
+F2D* halveSize(F2D* I);
+F2D** gaussianss(F2D* I, float sigman, int O, int S, int omin, int smin, int smax, float sigma0);
+F2D** diffss(F2D** ss, int O, int intervals);
+F2D* doubleSize(F2D* I);
+void imsmooth(F2D* I_pt, float dsigma, F2D* out);
+F2D* siftlocalmax(F2D* in, float thresh, int intervals, int M, int N);
+F2D* filterBoundaryPoints(int M, int N, F2D* oframes); 
+F2D* siftrefinemx(F2D* oframes, F2D* dogss, int smin, float thresh, int rin, int M, int N, int intervals);
+
+#endif
+
+
diff --git a/SD-VBS/benchmarks/sift/src/c/siftlocalmax.c b/SD-VBS/benchmarks/sift/src/c/siftlocalmax.c
new file mode 100644
index 0000000..d75bcbd
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/siftlocalmax.c
@@ -0,0 +1,247 @@
+#include "sift.h"
+
+/**
+    SIFTLOCALMAX  Find local maximizers
+   Returns the indexes of the local maximizers of
+   the 3-dimensional array F.
+
+    Say, we have a Q-dimensional array F.
+   A local maximizer is an element whose value is greater than the
+   value of all its neighbors.  The neighbors of an element i1...iQ
+   are the subscripts j1...jQ such that iq-1 <= jq <= iq (excluding
+   i1...iQ itself).  For example, if Q=1 the neighbors of an element
+   are its predecessor and successor in the linear order; if Q=2, its
+   neighbors are the elements immediately to its north, south, west,
+   est, north-west, north-est, south-west and south-est
+   (8-neighborhood).
+
+   Points on the boundary of F are ignored (and never selected as
+   local maximizers).
+
+   SEL=SIFTLOCALMAX(F,THRESH) accepts an element as a mazimizer only
+   if it is at least THRES greater than all its neighbors.
+
+   SEL=SIFTLOCALMAX(F,THRESH,P) look for neighbors only in the first
+   P dimensions of the Q-dimensional array F. This is useful to
+   process F in ``slices''.
+
+   REMARK.  Matrices (2-array) with a singleton dimension are
+   interpreted as vectors (1-array). So for example SIFTLOCALMAX([0 1
+   0]) and SIFTLOCALMAX([0 1 0]') both return 2 as an aswer. However,
+   if [0 1 0] is to be interpreted as a 1x2 matrix, then the correct
+   answer is the empty set, as all elements are on the boundary.
+   Unfortunately MATLAB does not distinguish between vectors and
+   2-matrices with a singleton dimension.  To forece the
+   interpretation of all matrices as 2-arrays, use
+   SIFTLOCALMAX(F,TRESH,2) (but note that in this case the result is
+   always empty!).
+**/
+
+#define NDIMS 3
+
+F2D* siftlocalmax(F2D* in, float thresh, int intervals, int M, int N)
+{  
+  int ndims, ptoffset=0, maxIter = 0; 
+  int offsets[NDIMS];
+  int midx[NDIMS];
+  int dims[NDIMS];
+  I2D* neighbors ;
+  int nneighbors ;
+  F2D* out;
+    
+ /**  
+    We pass dogss[o], which has >1 intervals
+    If >1 intervals, then the dimensions of in[F] will be 1 x intervals
+    If =1 interval, then the dimensions of in[F] will be the size of the dogss[o] image
+    We will check for this condition.
+ **/
+    
+    ndims = NDIMS;      /* Since we have intervals number of images of size M x N */
+        dims[0] = M;
+        dims[1] = N;
+        dims[2] = intervals-1;
+
+  /* 
+     If there are only two dimensions and if one is singleton, then
+     assume that a vector has been provided as input (and treat this
+     as a COLUMN matrix with p=1). We do this because Matlab does not
+     distinguish between vectors and 1xN or Mx1 matrices and because
+     the cases 1xN and Mx1 are trivial (the result is alway empty).
+  */
+  
+  
+ 
+  /* ------------------------------------------------------------------
+   *                                                         Do the job
+   * --------------------------------------------------------------- */  
+    int maxima_size = M*N ;
+
+    I2D* maxima_start = iMallocHandle(1, maxima_size);
+    int* maxima_iterator = maxima_start->data ;
+    int* maxima_end = maxima_start->data + maxima_size ;
+
+    int i,h,o,j; 
+    F2D* pt;  
+    
+    pt = in;
+
+    /* Compute the offsets between dimensions. */
+    offsets[0] = 1 ;
+    for(i = 1 ; i < ndims ; ++i)
+    {
+      offsets[i] = offsets[i-1]*dims[i-1] ;
+    }
+
+    /* Multi-index. */
+    for(i = 0 ; i < ndims ; ++i)
+      midx[i] = 1 ;
+
+    /* Neighbors. */
+    nneighbors = 1 ;
+    o=0 ;
+    for(i = 0 ; i < ndims ; ++i) 
+    {
+      nneighbors *= 3 ;
+      midx[i] = -1 ;
+      o -= offsets[i] ;
+    }
+    nneighbors -= 1 ;
+    neighbors = iMallocHandle(1,nneighbors);
+
+    /* Precompute offsets from offset(-1,...,-1,0,...0) to
+     * offset(+1,...,+1,0,...,0). */
+    i = 0 ;
+
+    while(1) 
+    {
+      if(o != 0)
+      {
+        asubsref(neighbors, i) = o ;
+        i++;
+      }
+      h = 0 ;
+      while( o += offsets[h], (++midx[h]) > 1 ) 
+      {
+        o -= 3*offsets[h] ;
+        midx[h] = -1 ;
+        if(++h >= ndims)
+          goto stop ;
+      }
+    }
+
+  stop: ;
+
+    /* Starts at the corner (1,1,...,1,0,0,...0) */
+    for(h = 0 ; h < ndims ; ++h) 
+    {
+      midx[h] = 1 ;
+      ptoffset += offsets[h] ;
+    }
+
+
+    /* ---------------------------------------------------------------
+     *                                                            Loop
+     * ------------------------------------------------------------ */
+
+    /*
+      If any dimension in the first P is less than 3 elements wide
+      then just return the empty matrix (if we proceed without doing
+      anything we break the carry reporting algorithm below).
+    */
+
+    for(h=0 ; h < ndims ; ++h)
+      if(dims[h] < 3) 
+                goto end ;
+   
+    while(1) 
+    {
+      /* Propagate carry along multi index midx */
+      
+      h = 0 ;
+      while(midx[h] >= dims[h] - 1) 
+      {
+        midx[h] = 1 ;
+        if(++h >= ndims) 
+          goto next_layer ;
+        ++midx[h] ;
+      }
+      
+      /*  Scan neighbors */
+      {
+        float v = asubsref(pt, ptoffset);  //*pt ;
+        int is_greater = (v>=thresh) ? 1 : 0;
+        
+                assert(ptoffset < pt->width*pt->height);
+
+        i = 0  ;
+        while(is_greater && i < nneighbors)
+        {
+            if(v > asubsref(pt, ptoffset + asubsref(neighbors,i)))
+                is_greater *= 1;
+            else
+                is_greater *= 0;
+            i = i+1;
+        }
+        
+        /* Add the local maximum */
+        if(is_greater) 
+        {
+          /* Need more space? */
+          if( &(maxima_iterator[maxIter])  == maxima_end) 
+          {
+              int *temp, i, j;
+              maxima_size += M*N ;
+            
+            free(maxima_start); 
+            maxima_start = iMallocHandle(1, maxima_size);
+
+            maxima_end = maxima_start->data + maxima_size ;
+            maxima_iterator = maxima_end - M*N ;
+            maxIter = 0;
+          }
+          
+          maxima_iterator[maxIter] = ptoffset + 1;
+          maxIter++;
+        }
+        
+        /* Go to next element */
+        ptoffset += 1 ;
+        ++midx[0] ;
+        continue ;
+        
+      next_layer: ;
+        if( h >= ndims )
+          goto end ;
+        
+        while((++midx[h]) >= dims[h]) 
+        {
+          midx[h] = 0 ;
+          if(++h >= ndims)
+            goto end ;
+        }
+      }
+    }   
+     
+  end:;
+    /* Return. */
+    {
+        int i=0;
+        out = fMallocHandle(1, maxIter);
+      
+        for(i=0; i<maxIter; i++)
+            asubsref(out,i) = maxima_iterator[i] ;
+    }
+    
+    /* Release space. */
+    free(neighbors) ;
+    free(maxima_start);
+  
+  return out;
+}
+
+
+
+
+
+
+
diff --git a/SD-VBS/benchmarks/sift/src/c/siftrefinemx.c b/SD-VBS/benchmarks/sift/src/c/siftrefinemx.c
new file mode 100644
index 0000000..2b10e9d
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/c/siftrefinemx.c
@@ -0,0 +1,196 @@
+#include "sift.h"
+
+const int max_iter = 5 ;
+
+/**
+
+    SIFTREFINEMX  Subpixel localization, thresholding and on-edge test
+   Q = SIFTREFINEMX(P, OCTAVE, SMIN) refines, thresholds and performs
+   the on-edge test for the SIFT frames P extracted from the DOG
+   octave OCTAVE with parameter SMIN (see GAUSSIANSS()).
+
+   Q = SIFTREFINEMX(P, OCTAVE, SMIN, THRESH, R) specifies custom
+   values for the local maximum strength threshold THRESH and the
+   local maximum peakedeness threshold R.
+
+   OCTAVE is an octave of the Difference Of Gaussian scale space. P
+   is a 3xK matrix specifying the indexes (X,Y,S) of the points of
+   extremum of the octave OCTAVE. The spatial indexes X,Y are integer
+   with base zero. The scale index S is integer with base SMIN and
+   represents a scale sublevel in the specified octave.
+
+   The function returns a matrix Q containing the refined keypoints.
+   The matrix has the same format as P, except that the indexes are
+   now fractional. The function drops the points that do not satisfy
+   the strength and peakedness tests.
+
+**/
+
+F2D* siftrefinemx(F2D* oframes, F2D* dogss, int smin, float thresh, int r, int M, int N, int intervals)
+{
+  int S,K ;
+  F2D* out;
+        
+  /* -----------------------------------------------------------------
+  **                                               Check the arguments
+  ** -------------------------------------------------------------- */ 
+ 
+  S = intervals;
+  K = oframes->height;
+
+  /* If the input array is empty, then output an empty array as well. */
+  if( K == 0) {
+      out = fDeepCopy(oframes);
+    return out;
+  }
+
+  /* -----------------------------------------------------------------
+   *                                                        Do the job
+   * -------------------------------------------------------------- */
+  {    
+    F2D* buffer = fMallocHandle(K,3);
+    int p ;
+    const int yo = 1 ;
+    const int xo = M ;
+    const int so = M*N;
+    int buffCounter = 0;
+    int pptcount = 0;
+    
+    for(p = 0 ; p < K ; ++p) 
+    {
+        float tx, ty, ts;
+        int x,y,s;
+        int iter ;
+        float b[3] ;
+
+        tx = asubsref(oframes, pptcount++);
+        ty = asubsref(oframes, pptcount++);
+        ts = asubsref(oframes, pptcount++);
+
+        x = ceil(tx);
+        y = ceil(ty);
+        s = ceil(ts) - smin; 
+
+    
+      /* Local maxima extracted from the DOG
+       * have coorrinates 1<=x<=N-2, 1<=y<=M-2
+       * and 1<=s-mins<=S-2. This is also the range of the points
+       * that we can refine.
+       */
+      
+      if(x < 1 || x > N-2 ||
+         y < 1 || y > M-2 ||
+         s < 1 || s > S-2) {
+        continue ;
+      }
+
+#define at(dx,dy,ds) asubsref(dogss, (dx)*xo + (dy)*yo + (ds)*so)
+
+      {
+        float Dx=0,Dy=0,Ds=0,Dxx=0,Dyy=0,Dss=0,Dxy=0,Dxs=0,Dys=0 ;
+        int dx = 0 ;
+        int dy = 0 ;
+        
+        for(iter = 0 ; iter < max_iter ; ++iter) 
+        {
+
+          float A[3*3] ; 
+
+#define Aat(i,j) (A[(i)+(j)*3])    
+
+          x += dx ;
+          y += dy ;
+          
+          /* Compute the gradient. */
+          Dx = 0.5 * (at(x+1,y+0,s+0) - at(x-1,y+0,s+0)) ;
+          Dy = 0.5 * (at(x+0,y+1,s+0) - at(x+0,y-1,s+0));
+          Ds = 0.5 * (at(x+0,y+0,s+1) - at(x+0,y+0,s-1)) ;
+          
+          /* Compute the Hessian. */
+          Dxx = (at(x+1,y,s) + at(x-1,y,s) - 2.0 * at(x,y,s)) ;
+          Dyy = (at(x,y+1,s) + at(x,y-1,s) - 2.0 * at(x,y,s)) ;
+          Dss = (at(x,y,s+1) + at(x,y,s-1) - 2.0 * at(x,y,s)) ;
+          
+          Dxy = 0.25 * ( at(x+1,y+1,s) + at(x-1,y-1,s) - at(x-1,y+1,s) - at(x+1,y-1,s) ) ;
+          Dxs = 0.25 * ( at(x+1,y,s+1) + at(x-1,y,s-1) - at(x-1,y,s+1) - at(x+1,y,s-1) ) ;
+          Dys = 0.25 * ( at(x,y+1,s+1) + at(x,y-1,s-1) - at(x,y-1,s+1) - at(x,y+1,s-1) ) ;
+          
+          /* Solve linear system. */
+          Aat(0,0) = Dxx ;
+          Aat(1,1) = Dyy ;
+          Aat(2,2) = Dss ;
+          Aat(0,1) = Aat(1,0) = Dxy ;
+          Aat(0,2) = Aat(2,0) = Dxs ;
+          Aat(1,2) = Aat(2,1) = Dys ;
+          
+          b[0] = - Dx ;
+          b[1] = - Dy ;
+          b[2] = - Ds ;
+          
+          /* If the translation of the keypoint is big, move the keypoint
+           * and re-iterate the computation. Otherwise we are all set.
+           */
+          dx= ((b[0] >  0.6 && x < N-2) ?  1 : 0 )
+            + ((b[0] < -0.6 && x > 1  ) ? -1 : 0 ) ;
+          
+          dy= ((b[1] >  0.6 && y < M-2) ?  1 : 0 )
+            + ((b[1] < -0.6 && y > 1  ) ? -1 : 0 ) ;
+          
+          if( dx == 0 && dy == 0 ) 
+                        break ;
+          
+        }
+                                
+        {
+          float val = at(x,y,s) + 0.5 * (Dx * b[0] + Dy * b[1] + Ds * b[2]) ; 
+          float score = (Dxx+Dyy)*(Dxx+Dyy) / (Dxx*Dyy - Dxy*Dxy) ; 
+          float xn = x + b[0] ;
+          float yn = y + b[1] ;
+          float sn = s + b[2] ;
+        
+          if(fabs(val) > thresh &&
+             score < (r+1)*(r+1)/r && 
+             score >= 0 &&
+             fabs(b[0]) < 1.5 &&
+             fabs(b[1]) < 1.5 &&
+             fabs(b[2]) < 1.5 &&
+             xn >= 0 &&
+             xn <= N-1 &&
+             yn >= 0 &&
+             yn <= M-1 &&
+             sn >= 0 &&
+             sn <= S-1) 
+                  {
+            asubsref(buffer,buffCounter++) = xn ;
+            asubsref(buffer,buffCounter++) = yn ;
+            asubsref(buffer,buffCounter++) = sn+smin ;
+          }
+        }
+      }
+    }      
+
+    /* Copy the result into an array. */
+    {
+      int i, j, k=0;
+      int NL = buffCounter/3;
+      out = fMallocHandle(3, NL);
+
+        for(i=0; i<NL; i++)
+        {
+            for(j=0; j<3; j++)
+            {
+                subsref(out,j,i) = asubsref(buffer,k);
+                k++;
+            }
+        }
+    }
+    free(buffer) ;
+  }
+    
+    return out;
+}
+
+
+
+
+
diff --git a/SD-VBS/benchmarks/sift/src/matlab/diffss.m b/SD-VBS/benchmarks/sift/src/matlab/diffss.m
new file mode 100644
index 0000000..1e65390
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/diffss.m
@@ -0,0 +1,72 @@
+function dss = diffss(ss)
+% DIFFSS  Difference of scale space
+%   DSS=DIFFSS(SS) returns a scale space DSS obtained by subtracting
+%   consecutive levels of the scale space SS.
+%
+%   In SIFT, this function is used to compute the difference of
+%   Gaussian scale space from the Gaussian scale space of an image.
+%
+%   See also GAUSSIANSS(), PDF:SIFT.USER.SS.
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+dss.smin = ss.smin ;
+dss.smax = ss.smax-1 ;
+dss.omin = ss.omin ;
+dss.O = ss.O ;
+dss.S = ss.S ;
+dss.sigma0 = ss.sigma0 ;
+
+for o=1:dss.O
+  % Can be done at once, but it turns out to be faster
+  % this way
+  [M,N,S] = size(ss.octave{o}) ;
+  dss.octave{o} = zeros(M,N,S-1) ;
+  for s=1:S-1
+    dss.octave{o}(:,:,s) = ...
+        ss.octave{o}(:,:,s+1) - ss.octave{o}(:,:,s) ;
+  end
+end
+
+%    for i=1:32
+%        for j=1:32
+%            fprintf(1, '%f\n', dss.octave{1}(i,j,1));
+%        end
+%    end
diff --git a/SD-VBS/benchmarks/sift/src/matlab/gaussianss.m b/SD-VBS/benchmarks/sift/src/matlab/gaussianss.m
new file mode 100644
index 0000000..c92383c
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/gaussianss.m
@@ -0,0 +1,216 @@
+function SS = gaussianss(I,sigman,O,S,omin,smin,smax,sigma0)
+% GAUSSIANSS
+%   SS = GAUSSIANSS(I,SIGMAN,O,S,OMIN,SMIN,SMAX,SIGMA0) returns the
+%   Gaussian scale space of image I. Image I is assumed to be
+%   pre-smoothed at level SIGMAN. O,S,OMIN,SMIN,SMAX,SIGMA0 are the
+%   parameters of the scale space as explained in PDF:SIFT.USER.SS.
+%
+%   See also DIFFSS(), PDF:SIFT.USER.SS.
+
+% History
+%  4-15-2006  Fixed some comments
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+% --------------------------------------------------------------------
+%                                                  Check the arguments
+% --------------------------------------------------------------------
+% --------------------------------------------------------------------
+%                                                           Do the job
+% --------------------------------------------------------------------
+
+% Scale multiplicative step
+k = 2^(1/S) ;
+
+dsigma0 = sigma0 * sqrt(1 - 1/k^2) ; % Scale step factor
+sigman  = 0.5 ;                      % Nominal smoothing of the image
+
+% Scale space structure
+SS.O          = O ;
+SS.S          = S ;
+SS.sigma0     = sigma0 ;
+SS.omin       = omin ;
+SS.smin       = smin ;
+SS.smax       = smax ;
+
+% If mino < 0, multiply the size of the image.
+% (The rest of the code is consistent with this.)
+
+
+if omin < 0
+        for o=1:-omin
+                I = doubleSize(I) ;
+        end
+elseif omin > 0
+        for o=1:omin
+                I = halveSize(I) ;
+        end
+end
+
+[M,N] = size(I) ;
+
+% Index offset
+so = -smin+1 ;
+
+% --------------------------------------------------------------------
+%                                                         First octave
+% --------------------------------------------------------------------
+%
+% The first level of the first octave has scale index (o,s) =
+% (omin,smin) and scale coordinate
+%
+%    sigma(omin,smin) = sigma0 2^omin k^smin 
+%
+% The input image I is at nominal scale sigman. Thus in order to get
+% the first level of the pyramid we need to apply a smoothing of
+%  
+%   sqrt( (sigma0 2^omin k^smin)^2 - sigman^2 ).
+%
+% As we have pre-scaled the image omin octaves (up or down,
+% depending on the sign of omin), we need to correct this value
+% by dividing by 2^omin, getting
+%e
+%   sqrt( (sigma0 k^smin)^2 - (sigman/2^omin)^2 )
+%
+
+SS.octave{1} = zeros(M,N,smax-smin+1) ;
+SS.octave{1}(:,:,1)  = imsmooth(I, ...
+        sqrt((sigma0*k^smin)^2  - (sigman/2^omin)^2)) ;
+
+temp = sqrt((sigma0*k^smin)^2  - (sigman/2^omin)^2) ;
+
+for s=smin+1:smax
+        % Here we go from (omin,s-1) to (omin,s). The extra smoothing
+        % standard deviation is
+        %
+        %  (sigma0 2^omin 2^(s/S) )^2 - (simga0 2^omin 2^(s/S-1/S) )^2
+        %
+        % Aftred dividing by 2^omin (to take into account the fact
+  % that the image has been pre-scaled omin octaves), the 
+  % standard deviation of the smoothing kernel is
+  %
+        %   dsigma = sigma0 k^s sqrt(1-1/k^2)
+  %
+        dsigma = k^s * dsigma0 ;
+        SS.octave{1}(:,:,s +so) = ...
+                imsmooth(squeeze(...
+                SS.octave{1}(:,:,s-1 +so)...
+                ), dsigma )  ;
+end
+
+% --------------------------------------------------------------------
+%                                                        Other octaves
+% --------------------------------------------------------------------
+
+for o=2:O  
+        % We need to initialize the first level of octave (o,smin) from
+        % the closest possible level of the previous octave. A level (o,s)
+  % in this octave corrsponds to the level (o-1,s+S) in the previous
+  % octave. In particular, the level (o,smin) correspnds to
+  % (o-1,smin+S). However (o-1,smin+S) might not be among the levels
+  % (o-1,smin), ..., (o-1,smax) that we have previously computed.
+  % The closest pick is
+  %
+        %                       /  smin+S    if smin+S <= smax
+        % (o-1,sbest) , sbest = |
+        %                       \  smax      if smin+S > smax
+        %
+        % The amount of extra smoothing we need to apply is then given by
+        %
+        %  ( sigma0 2^o 2^(smin/S) )^2 - ( sigma0 2^o 2^(sbest/S - 1) )^2
+        %
+  % As usual, we divide by 2^o to cancel out the effect of the
+  % downsampling and we get
+  %
+        %  ( sigma 0 k^smin )^2 - ( sigma0 2^o k^(sbest - S) )^2
+  %
+        sbest = min(smin + S, smax) ;
+        TMP = halveSize(squeeze(SS.octave{o-1}(:,:,sbest+so))) ;
+
+        target_sigma = sigma0 * k^smin ;
+          prev_sigma = sigma0 * k^(sbest - S) ;
+          
+        if(target_sigma > prev_sigma)
+          temp = sqrt(target_sigma^2 - prev_sigma^2);
+          TMP = imsmooth(TMP, temp ) ;                               
+        end
+        [M,N] = size(TMP) ;
+        
+        SS.octave{o} = zeros(M,N,smax-smin+1) ;
+        SS.octave{o}(:,:,1) = TMP ;
+
+        for s=smin+1:smax
+                % The other levels are determined as above for the first octave.                
+                dsigma = k^s * dsigma0 ;
+                SS.octave{o}(:,:,s +so) = ...
+                        imsmooth(squeeze(...
+                        SS.octave{o}(:,:,s-1 +so)...
+                        ), dsigma)  ;    
+        end
+    
+        
+end
+
+% -------------------------------------------------------------------------
+%                                                       Auxiliary functions
+% -------------------------------------------------------------------------
+function J = doubleSize(I)
+[M,N]=size(I) ;
+J = zeros(2*M,2*N) ;
+J(1:2:end,1:2:end) = I ;
+J(2:2:end-1,2:2:end-1) = ...
+        0.25*I(1:end-1,1:end-1) + ...
+        0.25*I(2:end,1:end-1) + ...
+        0.25*I(1:end-1,2:end) + ...
+        0.25*I(2:end,2:end) ;
+J(2:2:end-1,1:2:end) = ...
+        0.5*I(1:end-1,:) + ...
+    0.5*I(2:end,:) ;
+J(1:2:end,2:2:end-1) = ...
+        0.5*I(:,1:end-1) + ...
+    0.5*I(:,2:end) ;
+
+function J = halveSize(I)
+J=I(1:2:end,1:2:end) ;
+%[M,N] = size(I) ;
+%m=floor((M+1)/2) ;
+%n=floor((N+1)/2) ;
+%J = I(:,1:2:2*n) + I(:,2:2:2*n+1) ;
+%J = 0.25*(J(1:2:2*m,:)+J(2:2:2*m+1,:)) ;
diff --git a/SD-VBS/benchmarks/sift/src/matlab/imreadbw.m b/SD-VBS/benchmarks/sift/src/matlab/imreadbw.m
new file mode 100644
index 0000000..55cb708
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/imreadbw.m
@@ -0,0 +1,52 @@
+function I = imreadbw(file) 
+% IMREADBW  Reads an image as gray-scale
+%   I=IMREADBW(FILE) reads the image FILE and converts the result to a
+%   gray scale image (with DOUBLE storage class anr range normalized
+%   in [0,1]).
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+I=im2double(imread(file)) ;
+
+if(size(I,3) > 1)
+  I = rgb2gray( I ) ;
+end
+
+
diff --git a/SD-VBS/benchmarks/sift/src/matlab/imsmooth.c b/SD-VBS/benchmarks/sift/src/matlab/imsmooth.c
new file mode 100644
index 0000000..5d6a660
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/imsmooth.c
@@ -0,0 +1,115 @@
+/** file:        imsmooth.c
+ ** author:      Andrea Vedaldi
+ ** description: Smooth an image.
+ **/
+
+#include"mex.h"
+#include<stdlib.h>
+#include<string.h>
+#include<math.h>
+#include<assert.h>
+
+#define greater(a,b) ((a) > (b))
+#define min(a,b) (((a)<(b))?(a):(b))
+#define max(a,b) (((a)>(b))?(a):(b))
+
+const double win_factor = 1.5 ;
+const int nbins = 36 ;
+
+void
+mexFunction(int nout, mxArray *out[], 
+            int nin, const mxArray *in[])
+{
+  int M,N ;
+  double* I_pt ;
+  double* J_pt ;
+  double s ;
+  enum {I=0,S} ;
+  enum {J=0} ;
+
+  /* ------------------------------------------------------------------
+  **                                                Check the arguments
+  ** --------------------------------------------------------------- */ 
+  if (nin != 2) {
+    mexErrMsgTxt("Exactly two input arguments required.");
+  } else if (nout > 1) {
+    mexErrMsgTxt("Too many output arguments.");
+  }
+  
+  if (!mxIsDouble(in[I]) || 
+      !mxIsDouble(in[S]) ) {
+    mexErrMsgTxt("All arguments must be real.") ;
+  }
+  
+  if(mxGetNumberOfDimensions(in[I]) > 2||
+     mxGetNumberOfDimensions(in[S]) > 2) {
+    mexErrMsgTxt("I must be a two dimensional array and S a scalar.") ;
+  }
+  
+  if(max(mxGetM(in[S]),mxGetN(in[S])) > 1) {
+    mexErrMsgTxt("S must be a scalar.\n") ;
+  }
+
+  M = mxGetM(in[I]) ;
+  N = mxGetN(in[I]) ;
+
+  out[J] = mxCreateDoubleMatrix(M, N, mxREAL) ;
+  
+  I_pt   = mxGetPr(in[I]) ;
+  J_pt   = mxGetPr(out[J]) ;
+  s      = *mxGetPr(in[S]) ;
+
+  /* ------------------------------------------------------------------
+  **                                                         Do the job
+  ** --------------------------------------------------------------- */ 
+  if(s > 0.01) {
+    
+    int W = (int) ceil(4*s) ;
+    int i ; 
+    int j ;
+    double* g0 = (double*) mxMalloc( (2*W+1)*sizeof(double) ) ;
+    double* buffer = (double*) mxMalloc( M*N*sizeof(double) ) ;
+    double acc=0.0 ;
+    
+    for(j = 0 ; j < 2*W+1 ; ++j) {
+      g0[j] = exp(-0.5 * (j - W)*(j - W)/(s*s)) ;
+      acc += g0[j] ;
+    }
+    for(j = 0 ; j < 2*W+1 ; ++j) {
+      g0[j] /= acc ;
+    }
+    
+    /*
+    ** Convolve along the columns
+    **/
+    for(j = 0 ; j < N ; ++j) {
+      for(i = 0 ; i < M ; ++i) {
+        double* start = I_pt + max(i-W,0) + j*M ;        
+        double* stop = I_pt + min(i+W,M-1) + j*M + 1 ;
+        double* g = g0 + max(0, W-i) ;
+        acc = 0.0 ;
+        while(stop != start) acc += (*g++) * (*start++) ;
+        *buffer++ = acc ;
+      }
+    }
+    buffer -= M*N ;
+    
+    /*
+    ** Convolve along the rows
+    **/
+    for(j = 0 ; j < N ; ++j) {
+      for(i = 0 ; i < M ; ++i) {
+        double* start = buffer + i + max(j-W,0)*M ;
+        double* stop  = buffer + i + min(j+W,N-1)*M + M ;
+        double* g = g0 + max(0, W-j) ;
+        acc = 0.0 ;
+        while(stop != start) { acc += (*g++) * (*start) ; start+=M ;}
+        *J_pt++ = acc ;
+      }
+    }    
+    mxFree(buffer) ;
+    mxFree(g0) ;
+  } else {
+    memcpy(J_pt, I_pt, sizeof(double)*M*N) ;   
+  }
+}
diff --git a/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexa64
new file mode 100755
index 0000000..0997262
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexa64
diff --git a/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexglx b/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexglx
new file mode 100755
index 0000000..a4a7a20
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/imsmooth.mexglx
diff --git a/SD-VBS/benchmarks/sift/src/matlab/imsmooth_.c b/SD-VBS/benchmarks/sift/src/matlab/imsmooth_.c
new file mode 100644
index 0000000..e0adeff
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/imsmooth_.c
@@ -0,0 +1,103 @@
+#include<stdlib.h>
+#include<string.h>
+#include<math.h>
+#include "imsmooth.h"
+
+#define greater(a,b) ((a) > (b))
+#define min(a,b) (((a)<(b))?(a):(b))
+#define max(a,b) (((a)>(b))?(a):(b))
+
+const double win_factor = 1.5 ;
+const int nbins = 36 ;
+
+float* imsmooth(float* I_pt_, float dsigma)
+{
+  int M,N ;
+  float *I_pt ;
+  float* J_pt_, *J_pt ;
+  float* out_, *out;
+  float s ;
+  enum {I=0,S} ;
+  enum {J=0} ;
+
+  /* ------------------------------------------------------------------
+  **                                                Check the arguments
+  ** --------------------------------------------------------------- */ 
+
+  M = (int)in_[0];
+  N = (int)in_[1];
+
+  out_ = fMallocHandle(M, N);
+    J_pt_ = &(out_[0]);
+    J_pt = &(J_pt_[4]);
+    s = dsigma;
+    
+
+  /* ------------------------------------------------------------------
+  **                                                         Do the job
+  ** --------------------------------------------------------------- */ 
+  if(s > 0.01) 
+  {
+    
+    int W = (int) ceil(4*s) ;
+    int i ; 
+    int j ;
+    float* g0_, *g0, *buffer_, *buffer, acc;
+    g0_ = fMallocHandle(1, 2*W+1);
+    g0 = &(g0_[4]);
+    buffer_ = fMallocHandle(M, N);
+    acc=0.0 ;
+    
+    for(j = 0 ; j < 2*W+1 ; ++j) 
+    {
+      g0[j] = exp(-0.5 * (j - W)*(j - W)/(s*s)) ;
+      acc += g0[j] ;
+    }
+
+    for(j = 0 ; j < 2*W+1 ; ++j) 
+    {
+      g0[j] /= acc ;
+    }
+    
+    /*
+    ** Convolve along the columns
+    **/
+
+    for(j = 0 ; j < N ; ++j) 
+    {
+      for(i = 0 ; i < M ; ++i) 
+      {
+        float* start = I_pt + max(i-W,0) + j*M ;        
+        float* stop = I_pt + min(i+W,M-1) + j*M + 1 ;
+        float* g = g0 + max(0, W-i) ;
+        acc = 0.0 ;
+        while(stop != start) acc += (*g++) * (*start++) ;
+        *buffer++ = acc ;
+      }
+    }
+    buffer -= M*N ;
+    
+    /*
+    ** Convolve along the rows
+    **/
+    for(j = 0 ; j < N ; ++j) 
+    {
+      for(i = 0 ; i < M ; ++i) 
+      {
+        float* start = buffer + i + max(j-W,0)*M ;
+        float* stop  = buffer + i + min(j+W,N-1)*M + M ;
+        float* g = g0 + max(0, W-j) ;
+        acc = 0.0 ;
+        while(stop != start) { acc += (*g++) * (*start) ; start+=M ;}
+        *J_pt++ = acc ;
+      }
+    }    
+    free(buffer) ;
+    free(g0) ;
+  } 
+  else 
+  {
+    memcpy(J_pt, I_pt, sizeof(double)*M*N) ;   
+  }
+  return J_pt_;
+}
diff --git a/SD-VBS/benchmarks/sift/src/matlab/mexutils.c b/SD-VBS/benchmarks/sift/src/matlab/mexutils.c
new file mode 100644
index 0000000..45843cf
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/mexutils.c
@@ -0,0 +1,98 @@
+/* file:        mexutils.c 
+** author:      Andrea Vedaldi
+** description: Utility functions to write MEX files.
+**/
+
+#include"mex.h"
+#include<math.h>
+
+#undef M_PI
+#define M_PI 3.14159265358979
+
+/** @biref Is real scalar?
+ **
+ ** @return @c true if the array @a A is a real scalar.
+ **/
+int
+uIsRealScalar(const mxArray* A)
+{
+  return 
+    mxIsDouble(A) && 
+    !mxIsComplex(A) &&
+    mxGetNumberOfDimensions(A) == 2 &&
+    mxGetM(A) == 1 &&
+    mxGetN(A) == 1 ;
+}
+
+/** @brief Is real matrix?
+ **
+ ** The function checks wether the argument @a A is a real matrix.  In
+ ** addition, if @a M >= 0, it checks wether the number of rows is
+ ** equal to @a M and, if @a N >= 0, if the number of columns is equal
+ ** to @a N.
+ **
+ ** @param M number of rows.
+ ** @param N number of columns.
+ ** @return @c true if the array is a real matrix with the specified format.
+ **/
+int
+uIsRealMatrix(const mxArray* A, int M, int N)
+{
+  return  
+    mxIsDouble(A) &&
+    !mxIsComplex(A) &&
+    mxGetNumberOfDimensions(A) == 2 &&
+    ((M>=0)?(mxGetM(A) == M):1) &&
+    ((N>=0)?(mxGetN(A) == N):1) ;   
+}
+
+/** @brief Is real vector?
+ **
+ ** The function checks wether the argument  @a V is a real vector. By
+ ** definiton, a  matrix is a vector  if one of its  dimension is one.
+ ** In addition, if  @a D >= 0, it checks wether  the dimension of the
+ ** vecotr is equal to @a D.
+ **
+ ** @param D lenght of the vector.
+ ** @return @c true if the array is a real vector of the specified dimension.
+ **/
+int
+uIsRealVector(const mxArray* V, int D) 
+{
+  int M = mxGetM(V) ;
+  int N = mxGetN(V) ;
+  int is_vector = (N == 1) || (M == 1) ;
+  
+  return   
+    mxIsDouble(V) &&
+    !mxIsComplex(V) &&
+    mxGetNumberOfDimensions(V) == 2 &&
+    is_vector &&
+    ( D < 0 || N == D || M == D) ;
+}
+
+
+/** @brief Is a string?
+ **
+ ** The function checks wether the array @a S is a string. If
+ ** @a L is non-negative, it also check wether the strign has
+ ** length @a L.
+ **
+ ** @return @a c true if S is a string of the specified length.
+ **/
+int
+uIsString(const mxArray* S, int L)
+{
+  int M = mxGetM(S) ;
+  int N = mxGetN(S) ;
+
+  return 
+    mxIsChar(S) &&
+    M == 1 &&
+    (L < 0 || N == L) ;
+}
+
+/**
+ **
+ **/
+
diff --git a/SD-VBS/benchmarks/sift/src/matlab/plotmatches.m b/SD-VBS/benchmarks/sift/src/matlab/plotmatches.m
new file mode 100644
index 0000000..b6324e9
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/plotmatches.m
@@ -0,0 +1,124 @@
+function h=plotmatches(I1,I2,P1,P2,matches,varargin)
+% PLOTMATCHES  Plot keypoint matches
+%   PLOTMATCHES(I1,I2,P1,P2,MATCHES) plots the two images I1 and I2
+%   and lines connecting the frames (keypoints) P1 and P2 as specified
+%   by MATCHES.
+%
+%   P1 and P2 specify two sets of frames, one per column. The first
+%   two elements of each column specify the X,Y coordinates of the
+%   corresponding frame. Any other element is ignored.
+%
+%   MATCHES specifies a set of matches, one per column. The two
+%   elementes of each column are two indexes in the sets P1 and P2
+%   respectively.
+%
+%   The images I1 and I2 might be either both grayscale or both color
+%   and must have DOUBLE storage class. If they are color the range
+%   must be normalized in [0,1].
+%
+%   The function accepts the following option-value pairs:
+%
+%   'Stacking' ['h']
+%      Stacking of images: horizontal [h], vertical [v], diagonal
+%      [h], overlap ['o']
+%
+%   See also PLOTSIFTDESCRIPTOR(), PLOTSIFTFRAME(), PLOTSS().
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+% --------------------------------------------------------------------
+%                                                  Check the arguments
+% --------------------------------------------------------------------
+
+stack='h' ;
+
+for k=1:2:length(varargin)
+  switch varargin{k}
+    case 'Stacking'
+      stack=varargin{k+1} ;
+  end
+end
+ 
+% --------------------------------------------------------------------
+%                                                           Do the job
+% --------------------------------------------------------------------
+
+[M1,N1,K1]=size(I1) ;
+[M2,N2,K2]=size(I2) ;
+
+switch stack
+  case 'h'
+    N3=N1+N2 ;
+    M3=max(M1,M2) ;
+    oj=N1 ;
+    oi=0 ;
+  case 'v'
+    M3=M1+M2 ;
+    N3=max(N1,N2) ;
+    oj=0 ;
+    oi=M1 ;    
+  case 'd'
+    M3=M1+M2 ;
+    N3=N1+N2 ;
+    oj=N1 ;
+    oi=M1 ;
+  case 'o'
+    M3=max(M1,M2) ;
+    N3=max(N1,N2) ;
+    oj=0;
+    oi=0;
+end
+
+I=zeros(M3,N3,K1) ;
+I(1:M1,1:N1,:) = I1 ;
+I(oi+(1:M2),oj+(1:N2),:) = I2 ;
+         
+axes('Position', [0 0 1 1]) ;
+imagesc(I) ; colormap gray ; hold on ; axis image ; axis off ;
+drawnow ;
+
+K = size(matches, 2) ;
+nans = NaN * ones(1,K) ;
+
+x = [ P1(1,matches(1,:)) ; P2(1,matches(2,:))+oj ; nans ] ;
+y = [ P1(2,matches(1,:)) ; P2(2,matches(2,:))+oi ; nans ] ;
+
+h = line(x(:)', y(:)') ;
+set(h,'Marker','.','Color','g') ;
diff --git a/SD-VBS/benchmarks/sift/src/matlab/plotsiftdescriptor.m b/SD-VBS/benchmarks/sift/src/matlab/plotsiftdescriptor.m
new file mode 100644
index 0000000..2f4af50
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/plotsiftdescriptor.m
@@ -0,0 +1,169 @@
+function h=plotsiftdescriptor(d,f)
+% PLOTSIFTDESCRIPTOR   Plot SIFT descriptor
+%   PLOTSIFTDESCRIPTOR(D) plots the SIFT descriptors D, stored as
+%   columns of the matrix D. D has the same format used by SIFT().
+%
+%   PLOTSIFTDESCRIPTOR(D,F) plots the SIFT descriptors warped to the
+%   SIFT frames F, specified as columns of the matrix F. F has
+%   the same format used by SIFT().
+%
+%   H=PLOTSIFTDESCRIPTOR(...) returns the handle H to the line drawing
+%   representing the descriptors.
+%
+%   REMARK. Currently the function supports only descriptors with 4x4
+%   spatial bins and 8 orientation bins (Lowe's default.)
+%
+%   See also PLOTSIFTFRAME(), PLOTMATCHES(), PLOTSS().
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+lowe_compatible = 1 ;
+
+% --------------------------------------------------------------------
+%                                                  Check the arguments
+% --------------------------------------------------------------------
+
+if(size(d,1) ~= 128)
+  error('D should be a 128xK matrix (only standard descriptors accepted)') ;
+end
+
+if nargin > 1
+  if(size(f,1) ~= 4)
+    error('F should be a 4xK matrix');
+  end
+  
+  if(size(f,2) ~= size(f,2))
+    error('D and F must have the same number of columns') ;
+  end
+end
+
+% Descriptors are often non-double numeric arrays
+d = double(d) ;
+K = size(d,2) ;
+if nargin < 2
+  f = repmat([0;0;1;0],1,K) ;
+end
+
+maginf = 3.0 ;
+NBP=4 ;
+NBO=8 ;
+
+% --------------------------------------------------------------------
+%                                                           Do the job
+% --------------------------------------------------------------------
+
+xall=[] ;
+yall=[] ;
+
+for k=1:K
+  SBP = maginf * f(3,k) ;
+  th=f(4,k) ;
+  c=cos(th) ;
+  s=sin(th) ;
+
+  [x,y] = render_descr(d(:,k)) ;
+  xall = [xall SBP*(c*x-s*y)+f(1,k)] ;
+  yall = [yall SBP*(s*x+c*y)+f(2,k)] ;
+end
+
+h=line(xall,yall) ;
+
+% --------------------------------------------------------------------
+%                                                     Helper functions
+% --------------------------------------------------------------------
+
+% Renders a single descriptor
+function [x,y] = render_descr( d )
+
+lowe_compatible=1; 
+NBP=4 ;
+NBO=8 ;
+
+[x,y] = meshgrid(-NBP/2:NBP/2,-NBP/2:NBP/2) ;
+
+% Rescale d so that the biggest peak fits inside the bin diagram
+d = 0.4 * d / max(d(:)) ;
+
+% We have NBP*NBP bins to plot. Here are the centers:
+xc = x(1:end-1,1:end-1) + 0.5 ;
+yc = y(1:end-1,1:end-1) + 0.5 ;
+
+% We swap the order of the bin diagrams because they are stored row
+% major into the descriptor (Lowe's convention that we follow.)
+xc = xc' ;
+yc = yc' ;
+
+% Each bin contains a star with eight tips
+xc = repmat(xc(:)',NBO,1) ;
+yc = repmat(yc(:)',NBO,1) ;
+
+% Do the stars 
+th=linspace(0,2*pi,NBO+1) ;
+th=th(1:end-1) ;
+if lowe_compatible
+  xd = repmat(cos(-th), 1, NBP*NBP ) ;
+  yd = repmat(sin(-th), 1, NBP*NBP ) ;
+else
+  xd = repmat(cos(th), 1, NBP*NBP ) ;
+  yd = repmat(sin(th), 1, NBP*NBP ) ;
+end
+xd = xd .* d(:)' ;
+yd = yd .* d(:)' ;
+
+% Re-arrange in sequential order the lines to draw
+nans = NaN * ones(1,NBP^2*NBO) ;
+x1 = xc(:)' ;
+y1 = yc(:)' ;
+x2 = x1 + xd ;
+y2 = y1 + yd ;
+xstars = [x1;x2;nans] ;
+ystars = [y1;y2;nans] ;
+
+% Horizontal lines of the grid
+nans = NaN * ones(1,NBP+1);
+xh = [x(:,1)' ; x(:,end)' ; nans] ;
+yh = [y(:,1)' ; y(:,end)' ; nans] ;
+
+% Verical lines of the grid
+xv = [x(1,:) ; x(end,:) ; nans] ;
+yv = [y(1,:) ; y(end,:) ; nans] ;
+
+x=[xstars(:)' xh(:)' xv(:)'] ;
+y=[ystars(:)' yh(:)' yv(:)'] ;
diff --git a/SD-VBS/benchmarks/sift/src/matlab/plotsiftframe.m b/SD-VBS/benchmarks/sift/src/matlab/plotsiftframe.m
new file mode 100644
index 0000000..984dfc9
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/plotsiftframe.m
@@ -0,0 +1,119 @@
+function h=plotsiftframe(frames,labels)
+% PLOTSIFTFRAME  Plot SIFT frame
+%   H=PLOTSIFTFRAME(FRAMES) plots the SIFT frames FRAMES and returns
+%   and handle H to the resulting line set. FRAMES has the same format
+%   used by SIFT().
+%
+%   PLOTSIFTFRAME(FRAMES, LABELS) displays nearby the frame centers
+%   the indexes specified by the vector LABELS. This operation is slow
+%   for large sets of frames.
+%
+%   A SIFT frame is denoted by a circle, representing its support, and
+%   one of its radii, representing its orientation. The support is a
+%   disk with radius equal to six times the scale SIGMA of the
+%   frame. If the standard parameters are used for the detector, this
+%   corresponds to four times the standard deviation of the Gaussian
+%   window that has been uses to estimate the orientation, which is in
+%   fact equal to 1.5 times the scale SIGMA.
+%
+%   This function is considerably more efficient if called once on a
+%   whole set of frames as opposed to multiple times, one for each
+%   frame.
+%
+%   See also PLOTMATCHES(), PLOTSIFTDESCRIPTOR(), PLOTSS().
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+% --------------------------------------------------------------------
+%                                                  Check the arguments
+% --------------------------------------------------------------------
+
+if size(frames,1) ~= 4
+        error('FRAMES should be a 4xK matrix') ;
+end
+
+K = size(frames,2) ;
+
+if nargin > 1
+        putlabels = 1 ;
+end
+
+% --------------------------------------------------------------------
+%                                                          Do the work
+% --------------------------------------------------------------------
+
+hold on ;
+K=size(frames,2) ;
+thr=linspace(0,2*pi,40) ;
+
+allx = nan*ones(1, 40*K+(K-1)) ;
+ally = nan*ones(1, 40*K+(K-1)) ;
+
+allxf = nan*ones(1, 3*K) ;
+allyf = nan*ones(1, 3*K) ;
+
+putlabel=0 ;
+
+for k=1:K
+        xc=frames(1,k) ;
+        yc=frames(2,k) ;
+        r=1.5*4*frames(3,k) ;
+        th=frames(4,k) ;
+        
+        x = r*cos(thr) + xc ;
+        y = r*sin(thr) + yc ;
+                
+        allx((k-1)*(41) + (1:40)) = x ;
+        ally((k-1)*(41) + (1:40)) = y ;
+
+        allxf((k-1)*3 + (1:2)) = [xc xc+r*cos(th)] ;
+        allyf((k-1)*3 + (1:2)) = [yc yc+r*sin(th)] ;
+        
+        if putlabel
+                x=xc+r ;
+                y=yc ;
+                h=text(x+2,y,sprintf('%d',labels(k))) ;
+                set(h,'Color',[1 0 0]) ;
+                plot(x,y,'r.') ;
+        end
+
+end
+
+h=line([allx nan allxf], [ally nan allyf], 'Color','g','LineWidth',3) ;
diff --git a/SD-VBS/benchmarks/sift/src/matlab/plotss.m b/SD-VBS/benchmarks/sift/src/matlab/plotss.m
new file mode 100644
index 0000000..17868b6
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/plotss.m
@@ -0,0 +1,68 @@
+function plotss(ss,field)
+% PLOTSS  Plot scale space
+%   PLOTSS(SS) plots all octaves of the scale space SS.
+%
+%   See also GAUSSIANSS(), DIFFSS().
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+if nargin > 2
+    error('Too many arguments.') ;
+end
+
+omin = ss.omin ;
+smin = ss.smin ;
+nlevels = ss.smax-ss.smin+1 ;
+
+for oi=1:ss.O
+        for si=1:nlevels
+                tightsubplot(nlevels, ss.O, nlevels*(oi-1)+si) ;
+                s = si-1 + smin ;
+                o = oi-1 + omin ;
+                sigma = ss.sigma0 * 2^(s/ss.S + o) ;
+                F=squeeze(ss.octave{oi}(:,:,si)) ;
+                [M,N]=size(F) ;
+                imagesc(squeeze(ss.octave{oi}(:,:,si))) ;       axis image ; axis off ;
+                h=text(M/10,N/20,sprintf('(o,s)=(%d,%d), sigma=%f',o,s,sigma)) ;
+                set(h,'BackgroundColor','w','Color','k') ;
+        end
+end
+
+
diff --git a/SD-VBS/benchmarks/sift/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/sift/src/matlab/script_run_profile.m
new file mode 100644
index 0000000..c157507
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/script_run_profile.m
@@ -0,0 +1,23 @@
+function script_run_profile(dataDir, resultDir, type, common, tooldir)
+
+path(path,common); 
+sift_compile;
+
+I1=readImage([dataDir, '/1.bmp']) ; 
+
+rows = size(I1,1);
+cols = size(I1,2);
+fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
+
+I1=I1-min(I1(:)) ;
+I1=I1/max(I1(:)) ;
+
+%% Timing
+start = photonStartTiming;
+frames1 = sift( I1) ;
+stop = photonEndTiming;
+elapsed = photonReportTiming(start, stop);
+photonPrintTiming(elapsed);
+
+fWriteMatrix(frames1, dataDir);
+
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift.m b/SD-VBS/benchmarks/sift/src/matlab/sift.m
new file mode 100644
index 0000000..ee79371
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/sift.m
@@ -0,0 +1,110 @@
+% Input:
+%   I          the input image, with pixel values normalize to lie betwen [0,1].
+%
+% Output:
+%   features    a structure which contains the following fields:
+%       pos     an n*2 matrix containing the (x,y) coordinates of the keypoints
+%               stored in rows.
+%       scale   an n*3 matrix with rows describing the scale of each keypoint
+%               (i.e., first column specifies the octave, second column specifies the interval, and
+%               third column specifies sigma).
+%       orient  a n*1 vector containing the orientations of the keypoints [-pi,pi).
+%       desc    an n*128 matrix with rows containing the feature descriptors 
+%               corresponding to the keypoints.
+
+function [frames]=sift(I)
+
+[M,N,C] = size(I) ;
+
+% Lowe's choices
+S=3 ;
+omin=-1 ;
+O=floor(log2(min(M,N)))-omin-4 ; % Up to 16x16 images
+sigma0=1.6*2^(1/S) ;
+sigman=0.5 ;
+thresh = 0.04 / S / 2 ;
+r = 10 ;
+
+NBP = 4 ;
+NBO = 8 ;
+magnif = 3.0 ;
+
+% Parese input
+compute_descriptor = 0 ;
+discard_boundary_points = 1 ;
+verb = 0 ;
+
+smin = -1;
+smax = S+1;
+intervals = smax - smin + 1;
+
+
+% --------------------------------------------------------------------
+%                                                           Parameters
+% --------------------------------------------------------------------
+
+oframes = [] ;
+frames = [] ;
+descriptors = [] ;
+
+% --------------------------------------------------------------------
+%                                         SIFT Detector and Descriptor
+% --------------------------------------------------------------------
+
+% Compute scale spaces
+%if verb > 0, fprintf('SIFT: computing scale space...') ; end
+
+gss = gaussianss(I,sigman,O,S,omin,-1,S+1,sigma0) ;
+dogss = diffss(gss) ;
+frames = [];
+
+%% To maintain consistency with C code. Once C code is ready, this will be uncommented.
+for o=1:O                               %for o=1:O 
+        
+        % Local maxima of the DOG octave
+        % The 80% tricks discards early very weak points before refinement.
+         
+    idx = siftlocalmax(  dogss.octave{o}, 0.8*thresh  ) ;
+        idx = [idx , siftlocalmax( - dogss.octave{o}, 0.8*thresh)] ;  
+   
+        K=length(idx) ; 
+        [i,j,s] = ind2sub( size( dogss.octave{o} ), idx ) ;
+    
+    y=i-1 ;
+        x=j-1 ;
+        s=s-1+dogss.smin ;
+    oframes = [x(:)';y(:)';s(:)'] ;
+
+%    fWriteMatrix(oframes, '../data/sim');
+        
+        % Remove points too close to the boundary
+        if discard_boundary_points
+                oframes = filter_boundary_points(size(dogss.octave{o}), oframes ) ;
+        end
+                
+        % Refine the location, threshold strength and remove points on edges
+        oframes = siftrefinemx(...
+                oframes, ...
+                dogss.octave{o}, ...
+                dogss.smin, ...
+                thresh, ...
+                r) ;
+    
+   frames = [frames, oframes];     
+ 
+end
+end
+
+%% --------------------------------------------------------------------
+%%                                                              Helpers
+%% --------------------------------------------------------------------
+function oframes=filter_boundary_points(sz, oframes)
+
+sel=find(...
+        oframes(1,:) > 3 & ...
+        oframes(1,:) < sz(2)-3 & ...
+        oframes(2,:) > 3 & ...
+        oframes(2,:) < sz(1)-3 ) ;
+
+oframes=oframes(:,sel) ;
+end
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_compile.m b/SD-VBS/benchmarks/sift/src/matlab/sift_compile.m
new file mode 100644
index 0000000..78c0034
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/sift_compile.m
@@ -0,0 +1,60 @@
+function sift_compile(type)
+% SIFT_COMPILE  Compile MEX files
+%   Compiling under Windows requires at least Visual C 6 or LCC. You
+%   might try other compilers, but most likely you will need to edit
+%   this file.
+
+siftroot = fileparts(which('siftcompile')) ;
+opts = { '-O', '-I.' } ;
+%opts = { opts{:}, '-v' } ;
+
+if nargin < 1
+    type = 'visualc' ;
+end
+
+switch computer
+  case 'PCWIN'
+    warning('NOTE: compiling has been tested only with Visual C 6-7 and LCC') ;
+    switch type
+      case 'visualc'
+        lib{1}=[matlabroot '\extern\lib\win32\microsoft\libmwlapack.lib'] ;
+        lib{2}=[matlabroot '\extern\lib\win32\microsoft\msvc60\libmwlapack.lib'];
+        lib{3}=[matlabroot '\extern\lib\win32\microsoft\msvc71\libmwlapack.lib'];
+      case 'lcc'
+        lib{1}=[matlabroot '\extern\lib\win32\lcc\libmwlapack.lib'] ;
+    end
+    found=0;
+    for k=1:length(lib)
+      fprintf('Trying LAPACK lib ''%s''\n',lib{k}) ;
+      found=exist(lib{k}) ;
+      if found ~= 0
+        break ;
+      end
+    end
+    if found == 0
+      error('Could not find LAPACK library. Please edit this M-file to fix the issue.');
+    end
+    opts = {opts{:}, '-DWINDOWS'} ;
+    opts = {opts{:}, lib{k}} ;
+    
+  case 'MAC'
+    opts = {opts{:}, '-DMACOSX'} ;
+    opts = {opts{:}, 'CFLAGS=\$CFLAGS -faltivec'} ;
+  
+  case 'GLNX86'
+    opts = {opts{:}, '-DLINUX' } ;
+        
+  otherwise
+    error(['Unsupported architecture ', computer, '. Please edit this M-mfile to fix the issue.']) ;    
+end
+
+mex('imsmooth.c',opts{:}) ;
+mex('siftlocalmax.c',opts{:}) ;
+mex('siftrefinemx.c',opts{:}) ;
+mex('siftormx.c',opts{:}) ;
+mex('siftdescriptor.c',opts{:}) ;
+mex('siftmatch.c',opts{:}) ;
+
+    
+
+
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_demo2.m b/SD-VBS/benchmarks/sift/src/matlab/sift_demo2.m
new file mode 100644
index 0000000..a6f0c66
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/sift_demo2.m
@@ -0,0 +1,110 @@
+cd % SIFT_DEMO2  Demonstrate SIFT code (2)
+%   This is similar to SIFT_DEMO().
+%
+%   See also SIFT_DEMO().
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+I1=imreadbw('data/landscape-a.jpg') ; % I1=I1(1:2:end,:) ;
+I2=imreadbw('data/landscape-b.jpg') ; % I2=I2(1:2:end,:) ;
+I1c=double(imread('data/landscape-a.jpg'))/255.0 ;
+I2c=double(imread('data/landscape-b.jpg'))/255.0 ;
+
+I1=imsmooth(I1,.1) ;
+I2=imsmooth(I2,.1) ;
+
+I1=I1-min(I1(:)) ;
+I1=I1/max(I1(:)) ;
+I2=I2-min(I2(:)) ;
+I2=I2/max(I2(:)) ;
+
+S=3 ;
+
+fprintf('Computing frames and descriptors.\n') ;
+[frames1,descr1,gss1,dogss1] = sift( I1, 'Verbosity', 1, 'Threshold', ...
+                                     0.005, 'NumLevels', S ) ;
+[frames2,descr2,gss2,dogss2] = sift( I2, 'Verbosity', 1, 'Threshold', ...
+                                     0.005, 'NumLevels', S ) ;
+
+figure(11) ; clf ; plotss(dogss1) ; colormap gray ;
+figure(12) ; clf ; plotss(dogss2) ; colormap gray ;
+drawnow ;
+
+figure(2) ; clf ;
+tightsubplot(1,2,1) ; imagesc(I1) ; colormap gray ; axis image ;
+hold on ;
+h=plotsiftframe( frames1 ) ; set(h,'LineWidth',2,'Color','g') ;
+h=plotsiftframe( frames1 ) ; set(h,'LineWidth',1,'Color','k') ;
+
+tightsubplot(1,2,2) ; imagesc(I2) ; colormap gray ; axis image ;
+hold on ;
+h=plotsiftframe( frames2 ) ; set(h,'LineWidth',2,'Color','g') ;
+h=plotsiftframe( frames2 ) ; set(h,'LineWidth',1,'Color','k') ;
+
+fprintf('Computing matches.\n') ;
+% By passing to integers we greatly enhance the matching speed (we use
+% the scale factor 512 as Lowe's, but it could be greater without
+% overflow)
+descr1=uint8(512*descr1) ;
+descr2=uint8(512*descr2) ;
+tic ; 
+matches=siftmatch( descr1, descr2, 3 ) ;
+fprintf('Matched in %.3f s\n', toc) ;
+
+figure(3) ; clf ;
+plotmatches(I1c,I2c,frames1(1:2,:),frames2(1:2,:),matches,...
+  'Stacking','v') ;
+drawnow ;
+
+% Movie
+figure(4) ; set(gcf,'Position',[10 10 1024 512]) ;
+figure(4) ; clf ;
+tightsubplot(1,1);
+imagesc(I1) ; colormap gray ; axis image ; hold on ;
+h=plotsiftframe( frames1 ) ; set(h,'LineWidth',1,'Color','g') ;
+h=plot(frames1(1,:),frames1(2,:),'r.') ;
+MOV(1)=getframe ;
+
+figure(4) ; clf ;
+tightsubplot(1,1);
+imagesc(I2) ; colormap gray ; axis image ; hold on ;
+h=plotsiftframe( frames2 ) ; set(h,'LineWidth',1,'Color','g') ;
+h=plot(frames2(1,:),frames2(2,:),'r.') ;
+MOV(2)=getframe ;
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.css b/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.css
new file mode 100644
index 0000000..b9bd8e3
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.css
@@ -0,0 +1,159 @@
+/** file:        default.css
+ ** author:      Andrea Vedaldi
+ ** description: Default CSS sylesheet for SIFT_GENDOC.PL
+ **/
+
+/* AUTORIGHTS */
+
+h1
+{
+  color: #3a3a3a ;
+}
+
+pre
+{
+  font-family: monaco, courier, monospace ;
+  font-size: 14px ;
+  color: #3a3a3a ;
+}
+
+body
+{
+  margin: 10px ;
+  padding: 1em ;
+  right: 0px ;
+  font-family: arial, sans-serif ;
+
+  color: black ;
+  background-color: #fffffa ; 
+}
+
+/* ------------------------------------------------------------------
+ *                                                             Module
+ * --------------------------------------------------------------- */
+
+div.module
+{
+  margin-bottom: 1em ;
+  //background-color: #ffffff ;
+}
+
+div.module h1
+{
+  margin: 0px ;
+  margin-bottom: 0.5em ;
+  padding: 0px ;
+  font-size: 1.5em ;
+  border-bottom: 2px #3a3a3a solid ;
+}
+
+div.module pre
+{
+  padding-left: 1em ;
+}
+
+div.module div.footer
+{
+  clear: both ;
+}
+
+div.module div.footer :link
+{
+  color: white ;
+  text-decoration: none ;
+}
+
+/* ------------------------------------------------------------------
+ *                                                       Module index
+ * --------------------------------------------------------------- */
+
+div.module div.index
+{
+  font-family: sans-serif ;
+  font-size: 0.8em ;
+
+  width: 15em ;
+  float: right ;
+  border: 1px #ccc0c0 solid ;
+  background-color: #fcf0f0 ;
+}
+
+div.module div.index h1
+{
+  font-size: 1em ;  
+  font-weight: bold ;
+  text-align: center ;
+  border: none ;
+  padding: 0 ;
+  margin: 0 ;
+}
+
+div.module div.index ul
+{
+  list-style-type: square ;
+  list-style-position: inside ;
+  color: #3a3a3a ;
+  padding: 0 ;
+  margin: 0 ;
+  padding: 0.3em ;
+}
+
+div.module div.index ul li
+{
+  margin-bottom: 0.1em ;
+}
+
+
+/* ------------------------------------------------------------------
+ *                                                              Mfile
+ * --------------------------------------------------------------- */
+
+div.mfile
+{
+  background-color: white ;
+  margin-bottom: 1em ;
+  border: 1px #aaaaaa solid ;
+}
+
+div.mfile h1
+{
+  margin: 0 ;
+  padding: 0 ;
+  padding-left: 10px ;
+  font-size: 1.3em ;  
+  background-color: #f0f0ff ;
+}
+
+div.mfile h1 span.name
+{
+  font-family: monaco, courier, fixed ;
+}
+
+div.mfile h1 span.brief
+{
+  padding-left: 10px ; 
+  font-size: 0.9em ;
+  font-weight: normal ;  
+}
+
+div.mfile pre
+{
+  padding-left: 1em ;
+}
+
+div.mfile div.footer
+{
+  font-size: 0.8em ;
+  padding: 0.3em ;
+}
+
+div.mfile div.footer a
+{
+  text-decoration: none ;
+  color: #777777 ;
+}
+
+div.mfile div.footer a:hover
+{
+  text-decoration: underline ;
+}
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.m b/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.m
new file mode 100644
index 0000000..417f9c5
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.m
@@ -0,0 +1,50 @@
+function sift_gendoc
+% SIFT_GENDOC  Generate documentation
+%   This function extracts the documentation from the MEX files and
+%   creates an HTML manual.
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+rootdir   = fileparts(which('siftgendoc')) ;
+d=pwd;
+cd([rootdir]) ;
+res = perl([rootdir '/siftgendoc.pl'],[rootdir '/dom/index.html']) ;
+cd(d) ;
+fprintf(res) ;
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.pl b/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.pl
new file mode 100755
index 0000000..6bc0b5e
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/sift_gendoc.pl
@@ -0,0 +1,296 @@
+#!/usr/bin/perl -w 
+## file:        sift_gendoc.pl
+## author:      Andrea Vedaldi
+## description: Summarize MATLAB M-Files docs
+
+# AUTORIGHTS
+# Copyright (c) 2006 The Regents of the University of California.
+# All Rights Reserved.
+# 
+# Created by Andrea Vedaldi
+# UCLA Vision Lab - Department of Computer Science
+# 
+# Permission to use, copy, modify, and distribute this software and its
+# documentation for educational, research and non-profit purposes,
+# without fee, and without a written agreement is hereby granted,
+# provided that the above copyright notice, this paragraph and the
+# following three paragraphs appear in all copies.
+# 
+# This software program and documentation are copyrighted by The Regents
+# of the University of California. The software program and
+# documentation are supplied "as is", without any accompanying services
+# from The Regents. The Regents does not warrant that the operation of
+# the program will be uninterrupted or error-free. The end-user
+# understands that the program was developed for research purposes and
+# is advised not to rely exclusively on the program for any reason.
+# 
+# This software embodies a method for which the following patent has
+# been issued: "Method and apparatus for identifying scale invariant
+# features in an image and use of same for locating an object in an
+# image," David G. Lowe, US Patent 6,711,293 (March 23,
+# 2004). Provisional application filed March 8, 1999. Asignee: The
+# University of British Columbia.
+# 
+# IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+# FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+# INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+# ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+# ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+# CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+# A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+# BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+# MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+# Debugging level
+$verb = 0 ;
+
+# PDF document location
+$pdfdoc = 'sift.pdf' ;
+
+# This is the queue of directories to process.
+# It gets filled recursively.
+@dir_fifo = ('.') ;
+
+# This will hold an entry for each m-file found
+%mfiles = () ;
+
+# This will hold an entry for each module found 
+%modules = () ;
+
+# #ARGV is the index of the last element, which is 0
+if ($#ARGV == 0) {
+    open(FOUT,">$ARGV[0]") ;
+    print STDERR "Writing to file '$ARGV[0]'.\n" if $verb ;
+} else {
+    *FOUT= *STDOUT; 
+    print STDERR "Using standard output.\n" if $verb ; 
+}
+
+# Each module is a subdirectory. The subdirectory is used
+# as the module ID.
+
+while ($module_path = shift(@dir_fifo)) { 
+    print STDERR "=> '$module_path'\n" if $verb ;
+    
+    # get a first version of the module name
+    $module_path =~ m/.*\/([^\\]+)$/ ;
+    $module_name = $1 ;
+
+    # start a new module    
+    $module = {
+        'id'          => $module_path,
+        'path'        => $module_path,
+        'name'        => $module_name,
+        'mfiles'      => [],
+        'description' => ""
+    } ;
+    
+    # .................................................................
+    opendir(DIRHANDLE, $module->{'path'}) ;
+    FILE: foreach (sort readdir(DIRHANDLE)) {
+        $name = $_ ;
+        $path = $module->{'path'} . "/" . $_ ;
+
+        # push if a directory
+        $_ = $path ;
+        if (-d) {
+            next FILE if /(\.$|\.\.$)/ ;
+            push( @dir_fifo, "$_" ) ;
+            next FILE ;
+        }
+        
+        # parse if .m and not test_
+        next FILE unless (/.+\.m$/) ;
+        next FILE if (/test_.x*/) ;
+        $name =~ m/(.*).m/ ;
+        $name = $1 ;
+        print STDERR "  . m-file '$name'\n" if $verb ;
+        my ($brief,$description) = get_comment($path) ;
+
+        # topic description?
+        if (/overview/) {
+            print STDERR "    * module description\n" if $verb ;
+            $module->{'id'}          = $name ;
+            $module->{'name'}        = $brief ;
+            $module->{'description'} = $description ;
+            next FILE ;
+        }
+
+        # use names as IDs
+        $id = $name ;
+        $id =~ tr/A-Z/a-z/ ;
+
+        # create a new mfile object
+        $mfile = {
+            'id'          => $id,
+            'path'        => $path,
+            'name'        => $name,
+            'brief'       => $brief,
+            'module'      => $module,
+            'description' => $description
+        } ;
+        
+        # add a reference to this mfile
+        # object to the global mfile list
+        $mfiles{$id} = $mfile ;
+
+        # add a reference to this mfile
+        # object to the current module
+        push( @{$module->{'mfiles'}}, $mfile) ;
+    }
+    closedir(DIRHANDLE) ;
+    # ................................................................
+
+    # add a reference to the current module to the global
+    # module list
+    $modules{$module->{'id'}} = $module ;
+}
+
+# ....................................................................
+#                                                  write documentation
+# ....................................................................
+
+print FOUT <<EOF;
+<html>
+  <head>
+    <link href="default.css" rel="stylesheet" type="text/css"/>
+  </head>
+  <body>
+EOF
+
+# sort modules by path
+sub criterion { $modules{$a}->{'path'} cmp $modules{$b}->{'path'} ; }
+
+MODULE:
+foreach $id ( sort criterion keys %modules ) {
+    my $module = $modules{$id} ;   
+    my $rich_description = make_rich($module->{'description'}) ;
+
+    next MODULE if $#{$module->{'mfiles'}} < 0 and length($rich_description) == 0;
+
+    print FOUT <<EOF;
+    <div class='module' id='$module->{"id"}'>
+      <h1>$module->{'name'}</h1>
+      <div class='index'>
+        <h1>Module contents</h1>
+        <ul>
+EOF
+    foreach( @{$module->{'mfiles'}} ) {
+        print FOUT "        <li><a href='#$_->{'id'}'>" 
+                 . "$_->{'name'}</a></li>\n" ;
+    }
+    print FOUT <<EOF;
+        </ul>
+      </div>
+      <pre>
+      $rich_description
+      </pre>
+      <div class="footer">
+      </div>
+    </div>
+EOF
+}
+
+foreach $id (sort keys %mfiles) {
+    my $mfile = $mfiles{$id} ;
+    my $rich_description = make_rich($mfile->{'description'}) ;
+
+    print FOUT <<EOF;
+    <div class="mfile" id='$mfile->{"id"}'>
+      <h1>
+       <span class="name">$mfile->{"name"}</span>
+       <span class="brief">$mfile->{"brief"}</span>
+      </h1>
+      <pre>
+$rich_description
+      </pre>
+      <div class="footer">
+        <a href="#$mfile->{'module'}->{'id'}">
+        $mfile->{'module'}->{'name'}
+        </a>
+      </div>
+    </div>
+EOF
+}
+
+print FOUT "</body></html>" ;
+
+# Close file
+close FOUT ;
+
+
+# -------------------------------------------------------------------------
+sub get_comment {
+# -------------------------------------------------------------------------
+    local $_ ;
+    my $full_name = $_[0] ;
+    my @comment = () ;
+    
+    open IN,$full_name ;
+  SCAN: 
+    while( <IN> ) {
+        next if /^function/ ;
+        last SCAN unless ( /^%/ ) ;
+        push(@comment, substr("$_",1)) ;
+    }
+    close IN ;
+
+    my $brief = "" ;
+    if( $#comment >= 0 && $comment[0] =~ m/^\s*\w+\s+(.*)$/ ) {
+        $brief = $1 ;
+        splice (@comment, 0, 1) ;
+    }
+
+    # from the first line
+    return ($brief, join("",@comment)) ;
+}
+
+# -------------------------------------------------------------------------
+sub make_rich {
+# -------------------------------------------------------------------------
+    local $_ = $_[0] ;
+    s/([A-Z]+[A-Z0-9_]*)\(([^\)]*)\)/${\make_link($1,$2)}/g ;
+    s/PDF:([A-Z0-9_\-:.]+[A-Z0-9])/${\make_pdf_link($1)}/g ;
+    return $_ ;
+}
+
+# -------------------------------------------------------------------------
+sub make_link {
+# -------------------------------------------------------------------------
+    local $_ ;
+    my $name = $_[0] ;
+    my $arg  = $_[1] ;
+    my $id   = $name ;
+
+    # convert name to lower case and put into $_
+    $id =~ tr/A-Z/a-z/ ;
+    
+    # get mfile
+    my $mfile = $mfiles{$id} ;
+    my $module = $modules{$id} ;
+    
+    # return as appropriate    
+    if($mfile) {
+        return "<a href='#$id'>" . $name . "</a>" . "(" . $arg . ")" ;
+    } elsif($module) {
+      return "<a class='module' href='#$id'>" . $name . 
+          "</a>" . "(" . $arg . ")" ;
+    } else {
+        return $name . "(" . $arg .")" ;
+    }
+}
+
+
+# -------------------------------------------------------------------------
+sub make_pdf_link {
+# -------------------------------------------------------------------------
+    local $_ ;
+    my $name = $_[0] ;
+    my $id   = $name ;
+
+    # convert name to lower case and put into $_
+    $id =~ tr/A-Z/a-z/ ;
+    
+    return "<a href='${pdfdoc}#$id'>PDF:$1</a>" ;
+}
diff --git a/SD-VBS/benchmarks/sift/src/matlab/sift_overview.m b/SD-VBS/benchmarks/sift/src/matlab/sift_overview.m
new file mode 100644
index 0000000..71557e4
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/sift_overview.m
@@ -0,0 +1,33 @@
+% SIFT_OVERVIEW  Scale-Invariant Feature Transfrom
+%
+%  This is a MATLAB/C implementation of SIFT detector and descriptor
+%  [1]. You can:
+%
+%  * Use SIFT() to detect the SIFT frames (keypoints) of a given image
+%    and compute their descriptors. Then you can use SIFTMATCH() to
+%    match the descriptors.
+%
+%  * Use PLOTSS(), PLOTSIFTDESCRIPTOR(), PLOTSIFTFRAME(),
+%    PLOTMATCHES() to visualize the results.
+%
+%  As SIFT is implemented by several reusable M and MEX files, you can
+%  also run portions of the algorithm, or change them. Specifically,
+%  you can:
+%
+%  * Use SIFTDESCRIPTOR() to compute the SIFT descriptor from a list
+%    of frames and a scale space or plain image.
+%
+%  * Use GAUSSIANSS() and DIFFSS() to compute the Gaussian and DOG
+%    scale spaces.
+%
+%  * Use SIFTLOCALMAX(), SIFTREFINEMX(), SIFTORMX() to manually
+%    extract the SIFT frames from the DOG scale space. More in
+%    general, you can use SIFTLOCALMAX() to find maximizers of any
+%    multi-dimensional arrays.
+%
+%  REFERENCES
+%  [1] D. G. Lowe, "Distinctive image features from scale-invariant
+%      keypoints," IJCV, vol. 2, no. 60, pp. 91 110, 2004.
+%
+%  See also PDF:SIFT.INTRODUCTION.
+
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.c b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.c
new file mode 100644
index 0000000..63f4830
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.c
@@ -0,0 +1,524 @@
+/* file:        siftdescriptor
+** author:      Andrea Vedaldi
+** description: Compute SIFT descriptors
+**/
+
+/* AUTORIGHTS
+Copyright (c) 2006 The Regents of the University of California.
+All Rights Reserved.
+
+Created by Andrea Vedaldi
+UCLA Vision Lab - Department of Computer Science
+
+Permission to use, copy, modify, and distribute this software and its
+documentation for educational, research and non-profit purposes,
+without fee, and without a written agreement is hereby granted,
+provided that the above copyright notice, this paragraph and the
+following three paragraphs appear in all copies.
+
+This software program and documentation are copyrighted by The Regents
+of the University of California. The software program and
+documentation are supplied "as is", without any accompanying services
+from The Regents. The Regents does not warrant that the operation of
+the program will be uninterrupted or error-free. The end-user
+understands that the program was developed for research purposes and
+is advised not to rely exclusively on the program for any reason.
+
+This software embodies a method for which the following patent has
+been issued: "Method and apparatus for identifying scale invariant
+features in an image and use of same for locating an object in an
+image," David G. Lowe, US Patent 6,711,293 (March 23,
+2004). Provisional application filed March 8, 1999. Asignee: The
+University of British Columbia.
+
+IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+*/
+
+/*
+  REMARKS. The use of strcasecmp makes the function POSIX but not ANSI
+  compliant. When compling with Altivec, GCC Altivec extensions are
+  supported.
+*/
+
+#define LOWE_COMPATIBLE
+
+#include"mexutils.c"
+#include<stdlib.h>
+#include<math.h>
+
+#ifdef WINDOWS
+#include<string.h>
+#ifndef __cplusplus
+#define sqrtf(x)    ((float)sqrt((double)(x)))
+#define powf(x,y)   ((float)pow((double)(x),(double)(y)))
+#define fabsf(x)    ((float)fabs((double)(x)))
+#define sinf(x)     ((float)sin((double)(x)))
+#define cosf(x)     ((float)cos((double)(x)))
+#define expf(x)     ((float)exp((double)(x)))
+#define atan2f(x,y) ((float)atan2((double)(x),(double)(y)))
+#endif
+#else
+#include<strings.h>
+#endif
+
+/* Altivec and Accelerate support.
+ * Very crude at this time.
+ */
+#if defined( MACOSX ) && defined( __ALTIVEC__ )
+#include<Accelerate/Accelerate.h>
+typedef union 
+{
+  float x[4] ;
+  vFloat vec ;
+} float4 ;
+#endif
+
+#define greater(a,b) a > b
+#define min(a,b) (((a)<(b))?(a):(b))
+#define max(a,b) (((a)>(b))?(a):(b))
+
+
+enum {SCALESPACE, NOSCALESPACE} ;
+
+enum {PROP_MAGNIF=0,
+      PROP_NBP,
+      PROP_NBO,
+      PROP_UNKNOWN} ;
+
+char const * properties [4] = 
+  { "Magnif",
+    "NumSpatialBins",
+    "NumOrientBins",
+     0L
+  } ;
+
+/** Fast fmodf for 2*PI
+ **/
+/*inline*/
+float fast_mod(float th)
+{
+  while(th < 0) th += 2*M_PI ;
+  while(th > 2*M_PI) th -= 2*M_PI ;
+  return th ;
+}
+
+/** Fast floor. Equivalent to (int) floor(x)
+ **/
+/*inline*/
+int fast_floor(float x)
+{
+  return (int)( x - ((x>=0)?0:1) ) ; 
+}
+
+/** Normalizes in norm L_2 a descriptor.
+ **/
+void
+normalize_histogram(float* L_begin, float* L_end)
+{
+  float* L_iter ;
+  float norm=0.0 ;
+
+  for(L_iter = L_begin; L_iter != L_end ; ++L_iter)
+    norm += (*L_iter) * (*L_iter) ;
+
+  norm = sqrtf(norm) ;
+  /*  mexPrintf("%f\n",norm) ;*/
+
+  for(L_iter = L_begin; L_iter != L_end ; ++L_iter)
+    *L_iter /= norm ;
+}
+
+/** @brief MATLAB Driver.
+ **/
+void
+mexFunction(int nout, mxArray *out[], 
+            int nin, const mxArray *in[])
+{
+  int M,N,S=0,smin=0,K,num_levels=0 ;
+  const int* dimensions ;
+  const double* P_pt ;
+  const double* G_pt ;
+  float* descr_pt ;
+  float* buffer_pt ;
+  float sigma0 ;
+  float magnif = 3.0f ; /* Spatial bin extension factor. */
+  int NBP = 4 ;         /* Number of bins for one spatial direction (even). */
+  int NBO = 8 ;         /* Number of bins for the ortientation. */
+  int mode = NOSCALESPACE ;
+  int buffer_size=0;
+
+  enum {IN_G=0,IN_P,IN_SIGMA0,IN_S,IN_SMIN} ;
+  enum {OUT_L=0} ;
+
+  /* ------------------------------------------------------------------
+  **                                                Check the arguments
+  ** --------------------------------------------------------------- */ 
+ 
+  if (nin < 3) {
+    mexErrMsgTxt("At least three arguments are required") ;
+  } else if (nout > 1) {
+    mexErrMsgTxt("Too many output arguments.");
+  }
+                
+  if( !uIsRealScalar(in[IN_SIGMA0]) ) {
+    mexErrMsgTxt("SIGMA0 should be a real scalar") ;
+  }
+        
+  if(!mxIsDouble(in[IN_G]) ||
+     mxGetNumberOfDimensions(in[IN_G]) > 3) {
+    mexErrMsgTxt("G should be a real matrix or 3-D array") ;
+  }
+  
+  sigma0 = (float) *mxGetPr(in[IN_SIGMA0]) ;
+  
+  dimensions = mxGetDimensions(in[IN_G]) ;
+  M = dimensions[0] ;
+  N = dimensions[1] ;
+  G_pt = mxGetPr(in[IN_G]) ;
+  
+  P_pt = mxGetPr(in[IN_P]) ;    
+  K = mxGetN(in[IN_P]) ;
+  
+  if( !uIsRealMatrix(in[IN_P],-1,-1)) {
+    mexErrMsgTxt("P should be a real matrix") ;
+  }
+
+  if ( mxGetM(in[IN_P])  == 4) {
+    /* Standard (scale space) mode */ 
+    mode = SCALESPACE ;
+    num_levels = dimensions[2] ;
+    
+    if(nin < 5) {
+      mexErrMsgTxt("Five arguments are required in standard mode") ;
+    }
+    
+    if( !uIsRealScalar(in[IN_S]) ) {
+      mexErrMsgTxt("S should be a real scalar") ;
+    }
+    
+    if( !uIsRealScalar(in[IN_SMIN]) ) {
+      mexErrMsgTxt("SMIN should be a real scalar") ;
+    }
+    
+    if( !uIsRealMatrix(in[IN_P],4,-1)) {
+      mexErrMsgTxt("When the e mode P should be a 4xK matrix.") ;
+    }
+    
+    S = (int)(*mxGetPr(in[IN_S])) ;
+    smin = (int)(*mxGetPr(in[IN_SMIN])) ;
+    
+  } else if (  mxGetM(in[IN_P])  == 3 ) {
+    mode = NOSCALESPACE ;
+    num_levels = 1 ;
+    S      = 1 ;
+    smin   = 0 ;
+  } else {
+    mexErrMsgTxt("P should be either a 3xK or a 4xK matrix.") ;
+  }
+
+  /* Parse the property-value pairs */
+  {
+    char str [80] ;
+    int arg = (mode == SCALESPACE) ? IN_SMIN + 1 : IN_SIGMA0 + 1 ;
+
+    while(arg < nin) {
+      int k ;
+
+      if( !uIsString(in[arg],-1) ) {
+        mexErrMsgTxt("The first argument in a property-value pair"
+                     " should be a string") ;
+      }
+      mxGetString(in[arg], str, 80) ;
+
+#ifdef WINDOWS      
+      for(k = 0 ; properties[k] && strcmpi(str, properties[k]) ; ++k) ;
+#else
+      for(k = 0 ; properties[k] && strcasecmp(str, properties[k]) ; ++k) ;
+#endif
+
+      switch (k) {
+      case PROP_NBP:
+        if( !uIsRealScalar(in[arg+1]) ) {
+          mexErrMsgTxt("'NumSpatialBins' should be real scalar") ;
+        }
+        NBP = (int) *mxGetPr(in[arg+1]) ;
+        if( NBP <= 0 || (NBP & 0x1) ) {
+          mexErrMsgTxt("'NumSpatialBins' must be positive and even") ;
+        }
+        break ;
+
+      case PROP_NBO:
+        if( !uIsRealScalar(in[arg+1]) ) {
+          mexErrMsgTxt("'NumOrientBins' should be a real scalar") ;
+        }
+        NBO = (int) *mxGetPr(in[arg+1]) ;
+        if( NBO <= 0 ) {
+          mexErrMsgTxt("'NumOrientlBins' must be positive") ;
+        }
+        break ;
+
+      case PROP_MAGNIF:
+        if( !uIsRealScalar(in[arg+1]) ) {
+          mexErrMsgTxt("'Magnif' should be a real scalar") ;
+        }
+        magnif = (float) *mxGetPr(in[arg+1]) ;
+        if( magnif <= 0 ) {
+          mexErrMsgTxt("'Magnif' must be positive") ;
+        }
+        break ;
+
+      case PROP_UNKNOWN:
+        mexErrMsgTxt("Property unknown.") ;
+        break ;
+      }
+      arg += 2 ;
+    }
+  }
+  
+  /* -----------------------------------------------------------------
+   *                                   Pre-compute gradient and angles
+   * -------------------------------------------------------------- */
+  /* Alloc two buffers and make sure their size is multiple of 128 for
+   * better alignment (used also by the Altivec code below.)
+   */
+  buffer_size = (M*N*num_levels + 0x7f) & (~ 0x7f) ;
+  buffer_pt = (float*) mxMalloc( sizeof(float) * 2 * buffer_size ) ;
+  descr_pt  = (float*) mxCalloc( NBP*NBP*NBO*K,  sizeof(float)  ) ;
+
+  {
+    /* Offsets to move in the scale space. */
+    const int yo = 1 ;
+    const int xo = M ;
+    const int so = M*N ;
+    int x,y,s ;
+
+#define at(x,y) (*(pt + (x)*xo + (y)*yo))
+
+    /* Compute the gradient */
+    for(s = 0 ; s < num_levels ; ++s) {
+      const double* pt = G_pt + s*so ;
+      for(x = 1 ; x < N-1 ; ++x) {
+        for(y = 1 ; y < M-1 ; ++y) {
+          float Dx = 0.5 * ( at(x+1,y) - at(x-1,y) ) ;
+          float Dy = 0.5 * ( at(x,y+1) - at(x,y-1) ) ;
+          buffer_pt[(x*xo+y*yo+s*so) + 0          ] = Dx ;
+          buffer_pt[(x*xo+y*yo+s*so) + buffer_size] = Dy ;
+        }
+      }
+    }
+    
+    /* Compute angles and modules */
+    {
+      float* pt = buffer_pt ;
+      int j = 0 ;
+      while (j < N*M*num_levels) {
+
+#if defined( MACOSX ) && defined( __ALTIVEC__ )
+        if( ((unsigned int)pt & 0x7) == 0 && j+3 < N*M*num_levels ) {
+          /* If aligned to 128 bit and there are at least 4 pixels left */
+          float4 a, b, c, d ;
+          a.vec = vec_ld(0,(vector float*)(pt              )) ;
+          b.vec = vec_ld(0,(vector float*)(pt + buffer_size)) ;
+          c.vec = vatan2f(b.vec,a.vec) ;
+          a.x[0] = a.x[0]*a.x[0]+b.x[0]*b.x[0] ;
+          a.x[1] = a.x[1]*a.x[1]+b.x[1]*b.x[1] ;
+          a.x[2] = a.x[2]*a.x[2]+b.x[2]*b.x[2] ;
+          a.x[3] = a.x[3]*a.x[3]+b.x[3]*b.x[3] ;
+          d.vec = vsqrtf(a.vec) ;
+          vec_st(c.vec,0,(vector float*)(pt + buffer_size)) ;
+          vec_st(d.vec,0,(vector float*)(pt              )) ;
+          j += 4 ;
+          pt += 4 ;
+        } else {
+#endif
+          float Dx = *(pt              ) ;
+          float Dy = *(pt + buffer_size) ;
+          *(pt              ) = sqrtf(Dx*Dx + Dy*Dy) ;
+          *(pt + buffer_size) = atan2f(Dy, Dx) ;
+          j += 1 ;
+          pt += 1 ;
+#if defined( MACOSX ) && defined( __ALTIVEC__ )
+        }
+#endif
+
+      }
+    }
+  }
+
+  /* -----------------------------------------------------------------
+   *                                                        Do the job
+   * -------------------------------------------------------------- */ 
+  if(K > 0) {    
+    int p ;
+
+    /* Offsets to move in the buffer */
+    const int yo = 1 ;
+    const int xo = M ;
+    const int so = M*N ;
+
+    /* Offsets to move in the descriptor. */
+    /* Use Lowe's convention. */
+    const int binto = 1 ;
+    const int binyo = NBO * NBP ;
+    const int binxo = NBO ;
+    const int bino  = NBO * NBP * NBP ;
+
+    for(p = 0 ; p < K ; ++p, descr_pt += bino) {
+      /* The SIFT descriptor is a  three dimensional histogram of the position
+       * and orientation of the gradient.  There are NBP bins for each spatial
+       * dimesions and NBO  bins for the orientation dimesion,  for a total of
+       * NBP x NBP x NBO bins.
+       *
+       * The support  of each  spatial bin  has an extension  of SBP  = 3sigma
+       * pixels, where sigma is the scale  of the keypoint.  Thus all the bins
+       * together have a  support SBP x NBP pixels wide  . Since weighting and
+       * interpolation of  pixel is used, another  half bin is  needed at both
+       * ends of  the extension. Therefore, we  need a square window  of SBP x
+       * (NBP + 1) pixels. Finally, since the patch can be arbitrarly rotated,
+       * we need to consider  a window 2W += sqrt(2) x SBP  x (NBP + 1) pixels
+       * wide.
+       */      
+      const float x = (float) *P_pt++ ;
+      const float y = (float) *P_pt++ ;
+      const float s = (float) (mode == SCALESPACE) ? (*P_pt++) : 0.0 ;
+      const float theta0 = (float) *P_pt++ ;
+
+      const float st0 = sinf(theta0) ;
+      const float ct0 = cosf(theta0) ;
+      const int xi = (int) floor(x+0.5) ; /* Round-off */
+      const int yi = (int) floor(y+0.5) ;
+      const int si = (int) floor(s+0.5) - smin ;
+      const float sigma = sigma0 * powf(2, s / S) ;
+      const float SBP = magnif * sigma ;
+      const int W = (int) floor( sqrt(2.0) * SBP * (NBP + 1) / 2.0 + 0.5) ;      
+      int bin ;
+      int dxi ;
+      int dyi ;
+      const float* pt ;
+      float* dpt ;
+
+      /* Check that keypoints are within bounds . */
+
+      if(xi < 0   || 
+         xi > N-1 || 
+         yi < 0   || 
+         yi > M-1 ||
+         ((mode==SCALESPACE) && 
+          (si < 0   ||
+           si > dimensions[2]-1) ) )
+        continue ;
+
+      /* Center the scale space and the descriptor on the current keypoint. 
+       * Note that dpt is pointing to the bin of center (SBP/2,SBP/2,0).
+       */
+      pt  = buffer_pt + xi*xo + yi*yo + si*so ;
+      dpt = descr_pt + (NBP/2) * binyo + (NBP/2) * binxo ;
+     
+#define atd(dbinx,dbiny,dbint) (*(dpt + (dbint)*binto + (dbiny)*binyo + (dbinx)*binxo))
+      
+      /*
+       * Process each pixel in the window and in the (1,1)-(M-1,N-1)
+       * rectangle.
+       */
+      for(dxi = max(-W, 1-xi) ; dxi <= min(+W, N-2-xi) ; ++dxi) {
+        for(dyi = max(-W, 1-yi) ; dyi <= min(+W, M-2-yi) ; ++dyi) {
+
+          /* Compute the gradient. */
+          float mod   = *(pt + dxi*xo + dyi*yo + 0           ) ;
+          float angle = *(pt + dxi*xo + dyi*yo + buffer_size ) ;
+#ifdef LOWE_COMPATIBLE
+          float theta = fast_mod(-angle + theta0) ;
+#else
+          float theta = fast_mod(angle - theta0) ;
+#endif
+          /* Get the fractional displacement. */
+          float dx = ((float)(xi+dxi)) - x;
+          float dy = ((float)(yi+dyi)) - y;
+
+          /* Get the displacement normalized w.r.t. the keypoint orientation
+           * and extension. */
+          float nx = ( ct0 * dx + st0 * dy) / SBP ;
+          float ny = (-st0 * dx + ct0 * dy) / SBP ; 
+          float nt = NBO * theta / (2*M_PI) ;
+
+          /* Get the gaussian weight of the sample. The gaussian window
+           * has a standard deviation of NBP/2. Note that dx and dy are in
+           * the normalized frame, so that -NBP/2 <= dx <= NBP/2. */
+          const float wsigma = NBP/2 ;
+          float win =  expf(-(nx*nx + ny*ny)/(2.0 * wsigma * wsigma)) ;
+
+          /* The sample will be distributed in 8 adijacient bins. 
+           * Now we get the ``lower-left'' bin. */
+          int binx = fast_floor( nx - 0.5 ) ;
+          int biny = fast_floor( ny - 0.5 ) ;
+          int bint = fast_floor( nt ) ;
+          float rbinx = nx - (binx+0.5) ;
+          float rbiny = ny - (biny+0.5) ;
+          float rbint = nt - bint ;
+          int dbinx ;
+          int dbiny ;
+          int dbint ;
+
+          /* Distribute the current sample into the 8 adijacient bins. */
+          for(dbinx = 0 ; dbinx < 2 ; ++dbinx) {
+            for(dbiny = 0 ; dbiny < 2 ; ++dbiny) {
+              for(dbint = 0 ; dbint < 2 ; ++dbint) {
+                
+                if( binx+dbinx >= -(NBP/2) &&
+                    binx+dbinx <   (NBP/2) &&
+                    biny+dbiny >= -(NBP/2) &&
+                    biny+dbiny <   (NBP/2) ) {
+                  float weight = win 
+                    * mod 
+                    * fabsf(1 - dbinx - rbinx)
+                    * fabsf(1 - dbiny - rbiny)
+                    * fabsf(1 - dbint - rbint) ;
+
+                  atd(binx+dbinx, biny+dbiny, (bint+dbint) % NBO) += weight ;
+                }
+              }            
+            }
+          }
+        }  
+      }
+
+      {
+        /* Normalize the histogram to L2 unit length. */        
+        normalize_histogram(descr_pt, descr_pt + NBO*NBP*NBP) ;
+        
+        /* Truncate at 0.2. */
+        for(bin = 0; bin < NBO*NBP*NBP ; ++bin) {
+          if (descr_pt[bin] > 0.2) descr_pt[bin] = 0.2;
+        }
+        
+        /* Normalize again. */
+        normalize_histogram(descr_pt, descr_pt + NBO*NBP*NBP) ;
+      }
+    }
+  }
+
+  /* Restore pointer to the beginning of the descriptors. */
+  descr_pt -= NBO*NBP*NBP*K ;
+
+  {
+    int k ;
+    double* L_pt ;
+    out[OUT_L] = mxCreateDoubleMatrix(NBP*NBP*NBO, K, mxREAL) ;
+    L_pt = mxGetPr(out[OUT_L]) ;
+    for(k = 0 ; k < NBP*NBP*NBO*K ; ++k) {
+      L_pt[k] = descr_pt[k] ;
+    }
+  }
+
+  mxFree(descr_pt) ;  
+  mxFree(buffer_pt) ;
+}
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.m b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.m
new file mode 100644
index 0000000..7764897
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.m
@@ -0,0 +1,79 @@
+% SIFTDESCRIPTOR  Compute SIFT descriptors
+%   DESCR = SIFTDESCRIPTOR(G, P, SIGMA0, S, MINS) computes the SIFT
+%   descriptors DESCR of the SIFT frames P defined on the octave G of
+%   a Gaussian scale space. SIGMA0, S and MINS are the the parameter
+%   of the scale space as explained in PDF:SIFT.USER.SS. P has one
+%   column per frame, specifiying the center X1,X2, the scal index s
+%   and the orientation THETA of the frame.
+%
+%   As the function operates on a single octave, in order to process
+%   features spanning several octaves, one must group them and call
+%   SIFTDESCRIPTOR() once per each octave.
+%    
+%   DESCR = SIFTDESCRIPTOR(I, P, SIGMA0) operates on a plain image
+%   I. The image I is assumed to be pre-smoothed at scale SIGMA0 and P
+%   is a matrix with a column per frame, specifying the center X1,X2
+%   and the orientation THETA (but NOT the scale).
+%
+%   REMARK. The scale parameter s in P is the scale index, NOT the
+%   scale coordinate (see the PDF doc. for a discussion).
+%
+%   Other parameters can be specfied as option-value paris. These
+%   are
+%
+%   'Magnif' [3.0]
+%      Frame magnification factor. Each spatial bin of the SIFT
+%      histogram has an exentsion equal to magnif * sigma, where
+%      magnif is the frame magnification factor and sigma is the scale
+%      of the frame.
+%
+%   'NumSpatialBins' [4]
+%      This parameter specifies the number of spatial bins in each
+%      spatial direction x1 and x2. It must be a positive and even
+%      number.
+%
+%   'NumOrientBins' [8]
+%      This parameter specifies the number of orietnation bins. It
+%      must be a positive number.
+%
+%   See also SIFT(), GAUSSIANSS(), DIFFSS(), SIFTLOCALMAX(), 
+%            PDF:SIFT.USER.DESCRIPTOR.
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexa64
new file mode 100755
index 0000000..f094f56
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexa64
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexglx b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexglx
new file mode 100755
index 0000000..4eb94d8
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftdescriptor.mexglx
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.c b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.c
new file mode 100644
index 0000000..3646692
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.c
@@ -0,0 +1,291 @@
+/* file:        siftlocalmax.c
+** author:      Andrea Vedaldi
+** description: Find local maximizer of multi-dimensional array.
+**/
+
+/* AUTORIGHTS
+Copyright (c) 2006 The Regents of the University of California.
+All Rights Reserved.
+
+Created by Andrea Vedaldi
+UCLA Vision Lab - Department of Computer Science
+
+Permission to use, copy, modify, and distribute this software and its
+documentation for educational, research and non-profit purposes,
+without fee, and without a written agreement is hereby granted,
+provided that the above copyright notice, this paragraph and the
+following three paragraphs appear in all copies.
+
+This software program and documentation are copyrighted by The Regents
+of the University of California. The software program and
+documentation are supplied "as is", without any accompanying services
+from The Regents. The Regents does not warrant that the operation of
+the program will be uninterrupted or error-free. The end-user
+understands that the program was developed for research purposes and
+is advised not to rely exclusively on the program for any reason.
+
+This software embodies a method for which the following patent has
+been issued: "Method and apparatus for identifying scale invariant
+features in an image and use of same for locating an object in an
+image," David G. Lowe, US Patent 6,711,293 (March 23,
+2004). Provisional application filed March 8, 1999. Asignee: The
+University of British Columbia.
+
+IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+*/
+
+#include"mex.h"
+#include<mexutils.c>
+#include<stdlib.h>
+
+/** Matlab driver.
+ **/
+#define greater(a,b) ((a) > (b)+threshold)
+
+void
+mexFunction(int nout, mxArray *out[], 
+            int nin, const mxArray *in[])
+{
+  int M, N ;
+  const double* F_pt ;
+  int ndims ; 
+  int pdims = -1 ;
+  int* offsets ;
+  int* midx ;
+  int* neighbors ;
+  int nneighbors ;
+  int* dims ;
+  enum {F=0,THRESHOLD,P} ;
+  enum {MAXIMA=0} ;
+  double threshold = - mxGetInf() ; 
+
+
+  /* ------------------------------------------------------------------
+   *                                                Check the arguments
+   * --------------------------------------------------------------- */
+  if(nin > 1) {
+    if(!uIsRealScalar(in[THRESHOLD])) {
+      mexErrMsgTxt("THRESHOLD must be a real scalar.") ;
+    }
+    threshold = *mxGetPr(in[THRESHOLD]) ;
+  }
+    
+  ndims = mxGetNumberOfDimensions(in[F]) ;
+
+if(ndims !=3)
+    printf("Error Error: NDIMS not equal to 3. Not handled by C version\n");
+
+  {
+    /* We need to make a copy because in one special case (see below)
+       we need to adjust dims[].
+    */
+    int d ;
+    const int* const_dims = (int*) mxGetDimensions(in[F]) ;
+    dims = mxMalloc(sizeof(int)*ndims) ;
+    for(d=0 ; d < ndims ; ++d)
+    {
+/*        printf("Const Dimensions = %d\n", const_dims[d]);
+*/
+         dims[d] = const_dims[d] ;
+    }
+  }
+  M = dims[0] ;
+  N = dims[1] ;
+  F_pt = mxGetPr(in[F]) ;
+
+  /* 
+     If there are only two dimensions and if one is singleton, then
+     assume that a vector has been provided as input (and treat this
+     as a COLUMN matrix with p=1). We do this because Matlab does not
+     distinguish between vectors and 1xN or Mx1 matrices and because
+     the cases 1xN and Mx1 are trivial (the result is alway empty).
+  */
+  if((ndims == 2) && (pdims < 0) && (M == 1 || N == 1)) {
+
+    printf("ERROR ERROR: Entered a different loop here. Not handled by C version");
+
+    pdims = 1 ;
+    M = (M>N)?M:N ;
+    N = 1 ;
+    dims[0]=M ;
+    dims[1]=N ;
+  }
+
+  /* search the local maxima along the first p dimensions only */
+  if(pdims < 0)
+  {
+    pdims = ndims ;
+    }
+  
+  if(pdims > ndims) {
+    mxFree(dims) ;
+    mexErrMsgTxt("P must not be greater than the number of dimensions") ;
+  }
+
+  /* ------------------------------------------------------------------
+   *                                                         Do the job
+   * --------------------------------------------------------------- */  
+  {
+    int maxima_size = M*N ;
+    int* maxima_start = (int*) mxMalloc(sizeof(int) * maxima_size) ;
+    int* maxima_iterator = maxima_start ;
+    int* maxima_end = maxima_start + maxima_size ;
+    int i,j,h,o ;
+    const double* pt = F_pt ;
+    
+    /* Compute the offsets between dimensions. */
+    offsets = (int*) mxMalloc(sizeof(int) * ndims) ;
+    offsets[0] = 1 ;
+
+    for(h = 1 ; h < ndims ; ++h)
+    {
+      offsets[h] = offsets[h-1]*dims[h-1] ;
+/*      printf("%d:%d\t%d\n", h, offsets[h], dims[h-1]);
+*/ 
+    }
+
+    /* Multi-index. */
+    midx = (int*) mxMalloc(sizeof(int) * ndims) ;
+    for(h = 0 ; h < ndims ; ++h)
+      midx[h] = 1 ;
+
+    /* Neighbors. */
+    nneighbors = 1 ;
+    o=0 ;
+    for(h = 0 ; h < pdims ; ++h) {
+      nneighbors *= 3 ;
+      midx[h] = -1 ;
+      o -= offsets[h] ;
+    }
+    nneighbors -= 1 ;
+    neighbors = (int*) mxMalloc(sizeof(int) * nneighbors) ;
+
+    /* Precompute offsets from offset(-1,...,-1,0,...0) to
+     * offset(+1,...,+1,0,...,0). */
+    i = 0 ;
+
+    while(true) {
+      if(o != 0)
+        neighbors[i++] = o ;
+      h = 0 ;
+      while( o += offsets[h], (++midx[h]) > 1 ) {
+        o -= 3*offsets[h] ;
+        midx[h] = -1 ;
+        if(++h >= pdims)
+          goto stop ;
+      }
+    }
+  stop: ;
+        
+    /* Starts at the corner (1,1,...,1,0,0,...0) */
+    for(h = 0 ; h < pdims ; ++h) {
+      midx[h] = 1 ;
+      pt += offsets[h] ;
+/*      printf("%d:%x\t%d\n", h, pt, offsets[h]);
+*/
+    }
+  
+    for(h = pdims ; h < ndims ; ++h) {
+      midx[h] = 0 ;
+    }
+
+    /* ---------------------------------------------------------------
+     *                                                            Loop
+     * ------------------------------------------------------------ */
+
+    /*
+      If any dimension in the first P is less than 3 elements wide
+      then just return the empty matrix (if we proceed without doing
+      anything we break the carry reporting algorithm below).
+    */
+    for(h=0 ; h < pdims ; ++h)
+      if(dims[h] < 3) goto end ;
+    
+     while(true) {
+ 
+       /* Propagate carry along multi index midx */
+       h = 0 ;
+       while((midx[h]) >= dims[h] - 1) {
+/*         pt += 2*offsets[h] ;  skip first and last el. */
+         midx[h] = 1 ;
+         if(++h >= pdims) 
+           goto next_layer ;
+         ++midx[h] ;
+       }
+      
+      /*  Scan neighbors */
+      {
+        double v = *pt ;
+        bool is_greater = (v >= threshold) ;
+      /* printf("%f\n", v);
+        */
+        i = 0  ;
+        while(is_greater && i < nneighbors)
+        {
+          is_greater &= v > *(pt + neighbors[i++]) ;
+        }
+        
+        /* Add the local maximum */
+        if(is_greater) {
+          /* Need more space? */
+          if(maxima_iterator == maxima_end) {
+            maxima_size += M*N ;
+            maxima_start = (int*) mxRealloc(maxima_start, 
+                                            maxima_size*sizeof(int)) ;
+            maxima_end = maxima_start + maxima_size ;
+            maxima_iterator = maxima_end - M*N ;
+          }
+          
+          *maxima_iterator++ = pt - F_pt + 1 ;
+        }
+        
+        /* Go to next element */
+        pt += 1 ;
+        ++midx[0] ;
+        continue ;
+        
+      next_layer: ;
+        if( h >= ndims )
+          goto end ;
+        
+        while((++midx[h]) >= dims[h]) {
+          midx[h] = 0 ;
+          if(++h >= ndims)
+            goto end ;
+        }
+      }
+    }    
+  end:;
+    /* Return. */
+    {
+      double* M_pt ;
+/*      printf("%x\t%x\t%d\n", maxima_iterator, maxima_start, maxima_iterator-maxima_start);
+*/  
+      out[MAXIMA] = mxCreateDoubleMatrix
+        (1, maxima_iterator-maxima_start, mxREAL) ;
+      maxima_end = maxima_iterator ;
+      maxima_iterator = maxima_start ;
+      M_pt = mxGetPr(out[MAXIMA]) ;
+      while(maxima_iterator != maxima_end) 
+      {
+        *M_pt++ = *maxima_iterator++ ;
+      }
+    }
+    
+    /* Release space. */
+    mxFree(offsets) ;
+    mxFree(neighbors) ;
+    mxFree(midx) ;
+    mxFree(maxima_start) ;     
+  }
+  mxFree(dims) ;
+}
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.m b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.m
new file mode 100644
index 0000000..cee30ce
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.m
@@ -0,0 +1,33 @@
+% SIFTLOCALMAX  Find local maximizers
+%   SEL=SIFTLOCALMAX(F) returns the indexes of the local maximizers of
+%   the Q-dimensional array F.
+%
+%   A local maximizer is an element whose value is greater than the
+%   value of all its neighbors.  The neighbors of an element i1...iQ
+%   are the subscripts j1...jQ such that iq-1 <= jq <= iq (excluding
+%   i1...iQ itself).  For example, if Q=1 the neighbors of an element
+%   are its predecessor and successor in the linear order; if Q=2, its
+%   neighbors are the elements immediately to its north, south, west,
+%   est, north-west, north-est, south-west and south-est
+%   (8-neighborhood).
+%
+%   Points on the boundary of F are ignored (and never selected as
+%   local maximizers).
+%
+%   SEL=SIFTLOCALMAX(F,THRESH) accepts an element as a mazimizer only
+%   if it is at least THRES greater than all its neighbors.
+%
+%   SEL=SIFTLOCALMAX(F,THRESH,P) look for neighbors only in the first
+%   P dimensions of the Q-dimensional array F. This is useful to
+%   process F in ``slices''.
+%
+%   REMARK.  Matrices (2-array) with a singleton dimension are
+%   interpreted as vectors (1-array). So for example SIFTLOCALMAX([0 1
+%   0]) and SIFTLOCALMAX([0 1 0]') both return 2 as an aswer. However,
+%   if [0 1 0] is to be interpreted as a 1x2 matrix, then the correct
+%   answer is the empty set, as all elements are on the boundary.
+%   Unfortunately MATLAB does not distinguish between vectors and
+%   2-matrices with a singleton dimension.  To forece the
+%   interpretation of all matrices as 2-arrays, use
+%   SIFTLOCALMAX(F,TRESH,2) (but note that in this case the result is
+%   always empty!).
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexa64
new file mode 100755
index 0000000..2b8e264
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexa64
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexglx b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexglx
new file mode 100755
index 0000000..613a74e
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftlocalmax.mexglx
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.c b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.c
new file mode 100644
index 0000000..1150176
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.c
@@ -0,0 +1,250 @@
+/* file:        siftmatch.c
+** author:      Andrea Vedaldi
+** description: SIFT descriptor matching.
+**/
+
+/* AUTORIGHTS
+Copyright (c) 2006 The Regents of the University of California.
+All Rights Reserved.
+
+Created by Andrea Vedaldi
+UCLA Vision Lab - Department of Computer Science
+
+Permission to use, copy, modify, and distribute this software and its
+documentation for educational, research and non-profit purposes,
+without fee, and without a written agreement is hereby granted,
+provided that the above copyright notice, this paragraph and the
+following three paragraphs appear in all copies.
+
+This software program and documentation are copyrighted by The Regents
+of the University of California. The software program and
+documentation are supplied "as is", without any accompanying services
+from The Regents. The Regents does not warrant that the operation of
+the program will be uninterrupted or error-free. The end-user
+understands that the program was developed for research purposes and
+is advised not to rely exclusively on the program for any reason.
+
+This software embodies a method for which the following patent has
+been issued: "Method and apparatus for identifying scale invariant
+features in an image and use of same for locating an object in an
+image," David G. Lowe, US Patent 6,711,293 (March 23,
+2004). Provisional application filed March 8, 1999. Asignee: The
+University of British Columbia.
+
+IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+*/
+
+#include"mexutils.c"
+
+#include<stdlib.h>
+#include<string.h>
+#include<math.h>
+
+#define greater(a,b) ((a) > (b))
+#define min(a,b) (((a)<(b))?(a):(b))
+#define max(a,b) (((a)>(b))?(a):(b))
+
+#define TYPEOF_mxDOUBLE_CLASS double
+#define TYPEOF_mxSINGLE_CLASS float
+#define TYPEOF_mxINT8_CLASS   char
+#define TYPEOF_mxUINT8_CLASS  unsigned char
+
+#define PROMOTE_mxDOUBLE_CLASS double
+#define PROMOTE_mxSINGLE_CLASS float
+#define PROMOTE_mxINT8_CLASS   int
+#define PROMOTE_mxUINT8_CLASS  int
+
+#define MAXVAL_mxDOUBLE_CLASS mxGetInf()
+#define MAXVAL_mxSINGLE_CLASS ((float)mxGetInf())
+#define MAXVAL_mxINT8_CLASS   0x7fffffff
+#define MAXVAL_mxUINT8_CLASS  0x7fffffff
+
+typedef struct 
+{ 
+  int k1 ; 
+  int k2 ;
+  double score ;
+} Pair ;
+
+/* 
+ * This macro defines the matching function for abstract type; that
+ * is, it is a sort of C++ template.  This is also a good illustration
+ * of why C++ is preferable for templates :-)
+ */
+#define _COMPARE_TEMPLATE(MXC)                                          \
+  Pair* compare_##MXC (Pair* pairs_iterator,                            \
+                       const TYPEOF_##MXC * L1_pt,                      \
+                       const TYPEOF_##MXC * L2_pt,                      \
+                       int K1, int K2, int ND, float thresh)            \
+  {                                                                     \
+    int k1, k2 ;                                                        \
+    const PROMOTE_##MXC maxval = MAXVAL_##MXC ;                         \
+    for(k1 = 0 ; k1 < K1 ; ++k1, L1_pt += ND ) {                        \
+                                                                        \
+      PROMOTE_##MXC best = maxval ;                                     \
+      PROMOTE_##MXC second_best = maxval ;                              \
+      int bestk = -1 ;                                                  \
+                                                                        \
+      /* For each point P2[k2] in the second image... */                \
+      for(k2 =  0 ; k2 < K2 ; ++k2, L2_pt += ND) {                      \
+                                                                        \
+        int bin ;                                                       \
+        PROMOTE_##MXC acc = 0 ;                                         \
+        for(bin = 0 ; bin < ND ; ++bin) {                               \
+          PROMOTE_##MXC delta =                                         \
+            ((PROMOTE_##MXC) L1_pt[bin]) -                              \
+            ((PROMOTE_##MXC) L2_pt[bin]) ;                              \
+          acc += delta*delta ;                                          \
+        }                                                               \
+                                                                        \
+        /* Filter the best and second best matching point. */           \
+        if(acc < best) {                                                \
+          second_best = best ;                                          \
+          best = acc ;                                                  \
+          bestk = k2 ;                                                  \
+        } else if(acc < second_best) {                                  \
+          second_best = acc ;                                           \
+        }                                                               \
+      }                                                                 \
+                                                                        \
+      L2_pt -= ND*K2 ;                                                  \
+                                                                        \
+      /* Lowe's method: accept the match only if unique. */             \
+      if(thresh * (float) best <= (float) second_best &&                \
+         bestk != -1) {                                                 \
+        pairs_iterator->k1 = k1 ;                                       \
+        pairs_iterator->k2 = bestk ;                                    \
+        pairs_iterator->score = best ;                                  \
+        pairs_iterator++ ;                                              \
+      }                                                                 \
+    }                                                                   \
+                                                                        \
+    return pairs_iterator ;                                             \
+  }                                                                     \
+
+_COMPARE_TEMPLATE( mxDOUBLE_CLASS )
+_COMPARE_TEMPLATE( mxSINGLE_CLASS )
+_COMPARE_TEMPLATE( mxINT8_CLASS   )
+_COMPARE_TEMPLATE( mxUINT8_CLASS  )
+
+void
+mexFunction(int nout, mxArray *out[], 
+            int nin, const mxArray *in[])
+{
+  int K1, K2, ND ;
+  void* L1_pt ;
+  void* L2_pt ;
+  double thresh = 1.5 ;
+  mxClassID data_class ;
+  enum {L1=0,L2,THRESH} ;
+  enum {MATCHES=0,D} ;
+
+  /* ------------------------------------------------------------------
+  **                                                Check the arguments
+  ** --------------------------------------------------------------- */ 
+  if (nin < 2) {
+    mexErrMsgTxt("At least two input arguments required");
+  } else if (nout > 2) {
+    mexErrMsgTxt("Too many output arguments");
+  }
+    
+  if(!mxIsNumeric(in[L1]) ||
+     !mxIsNumeric(in[L2]) ||
+     mxGetNumberOfDimensions(in[L1]) > 2 ||
+     mxGetNumberOfDimensions(in[L2]) > 2) {
+    mexErrMsgTxt("L1 and L2 must be two dimensional numeric arrays") ;
+  }
+  
+  K1 = mxGetN(in[L1]) ;
+  K2 = mxGetN(in[L2]) ;
+  ND = mxGetM(in[L1]) ;
+  
+  if(mxGetM(in[L2]) != ND) {
+    mexErrMsgTxt("L1 and L2 must have the same number of rows") ;
+  }
+
+  data_class = mxGetClassID(in[L1]) ;
+  if(mxGetClassID(in[L2]) != data_class) {
+    mexErrMsgTxt("L1 and L2 must be of the same class") ;
+  }
+
+  L1_pt = mxGetData(in[L1]) ;
+  L2_pt = mxGetData(in[L2]) ;
+
+  if(nin == 3) {
+    if(!uIsRealScalar(in[THRESH])) {
+      mexErrMsgTxt("THRESH should be a real scalar") ;
+    }
+    thresh = *mxGetPr(in[THRESH]) ;
+  } else if(nin > 3) {
+    mexErrMsgTxt("At most three arguments are allowed") ;
+  }
+ 
+  /* ------------------------------------------------------------------
+  **                                                         Do the job
+  ** --------------------------------------------------------------- */ 
+  {
+    Pair* pairs_begin = (Pair*) mxMalloc(sizeof(Pair) * (K1+K2)) ;
+    Pair* pairs_iterator = pairs_begin ;
+
+
+#define _DISPATCH_COMPARE( MXC )                                        \
+    case MXC :                                                          \
+      pairs_iterator = compare_##MXC(pairs_iterator,                    \
+                                     (const TYPEOF_##MXC*) L1_pt,       \
+                                     (const TYPEOF_##MXC*) L2_pt,       \
+                                     K1,K2,ND,thresh) ;                 \
+    break ;                                                             \
+    
+    switch (data_class) {
+    _DISPATCH_COMPARE( mxDOUBLE_CLASS ) ;
+    _DISPATCH_COMPARE( mxSINGLE_CLASS ) ; 
+    _DISPATCH_COMPARE( mxINT8_CLASS   ) ;
+    _DISPATCH_COMPARE( mxUINT8_CLASS  ) ;
+    default :
+      mexErrMsgTxt("Unsupported numeric class") ;
+      break ;
+    }
+
+    /* ---------------------------------------------------------------
+     *                                                        Finalize
+     * ------------------------------------------------------------ */
+    {
+      Pair* pairs_end = pairs_iterator ;
+      double* M_pt ;
+      double* D_pt = NULL ;
+
+      out[MATCHES] = mxCreateDoubleMatrix
+        (2, pairs_end-pairs_begin, mxREAL) ;
+
+      M_pt = mxGetPr(out[MATCHES]) ;
+
+      if(nout > 1) {
+        out[D] = mxCreateDoubleMatrix(1,
+                                      pairs_end-pairs_begin,
+                                      mxREAL) ;
+        D_pt = mxGetPr(out[D]) ;
+      }
+
+      for(pairs_iterator = pairs_begin ; 
+          pairs_iterator < pairs_end  ; 
+          ++pairs_iterator) {
+        *M_pt++ = pairs_iterator->k1 + 1 ;
+        *M_pt++ = pairs_iterator->k2 + 1 ;
+        if(nout > 1) {
+          *D_pt++ = pairs_iterator->score ;
+        }
+      }
+    }
+    mxFree(pairs_begin) ;
+  }
+}
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.m b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.m
new file mode 100644
index 0000000..d4398c1
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.m
@@ -0,0 +1,60 @@
+% SIFTMATCH  Match SIFT features
+%   MATCHES=SIFTMATCH(DESCR1, DESCR2) matches the two sets of SIFT
+%   descriptors DESCR1 and DESCR2.
+%
+%   The function uses the same algorithm suggested by D. Lowe [1] to
+%   reject matches that are too ambiguous.
+%
+%   SIFTMATCH(DESCR1, DESCR2, THRESH) uses [1] with the specified
+%   threshold THRESH. A descriptor D1 is matched to a descriptor D2
+%   only if the distance d(D1,D2) multiplied by THRESH is not greather
+%   than the distance of D1 to all other descriptors. The default
+%   value of THRESH is 1.5.
+%   
+%   The storage class of the descriptors can be either DOUBLE, FLOAT,
+%   INT8 or UINT8. Usually interger classes are faster.
+%   
+%   [1] D. G. Lowe, 
+%       `Distinctive image features from scale-invariant keypoints,'
+%       IJCV, vol. 2, no. 60, pp. 91–110, 2004.
+%
+%   See also SIFT(), SIFTDESCRIPTOR().
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexa64
new file mode 100755
index 0000000..e58eaf5
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexa64
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexglx b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexglx
new file mode 100755
index 0000000..d5e32f7
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftmatch.mexglx
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftormx.c b/SD-VBS/benchmarks/sift/src/matlab/siftormx.c
new file mode 100644
index 0000000..40380a2
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftormx.c
@@ -0,0 +1,251 @@
+/* file:        siftormx.c
+** author:      Andrea Vedaldi
+** description: Computes peaks of orientation histogram.
+**/
+
+/* AUTORIGHTS
+Copyright (c) 2006 The Regents of the University of California.
+All Rights Reserved.
+
+Created by Andrea Vedaldi
+UCLA Vision Lab - Department of Computer Science
+
+Permission to use, copy, modify, and distribute this software and its
+documentation for educational, research and non-profit purposes,
+without fee, and without a written agreement is hereby granted,
+provided that the above copyright notice, this paragraph and the
+following three paragraphs appear in all copies.
+
+This software program and documentation are copyrighted by The Regents
+of the University of California. The software program and
+documentation are supplied "as is", without any accompanying services
+from The Regents. The Regents does not warrant that the operation of
+the program will be uninterrupted or error-free. The end-user
+understands that the program was developed for research purposes and
+is advised not to rely exclusively on the program for any reason.
+
+This software embodies a method for which the following patent has
+been issued: "Method and apparatus for identifying scale invariant
+features in an image and use of same for locating an object in an
+image," David G. Lowe, US Patent 6,711,293 (March 23,
+2004). Provisional application filed March 8, 1999. Asignee: The
+University of British Columbia.
+
+IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+*/
+
+#include"mex.h"
+#include<stdlib.h>
+#include<string.h>
+#include<math.h>
+
+#include<mexutils.c>
+
+#define greater(a,b) a > b
+#define min(a,b) (((a)<(b))?(a):(b))
+#define max(a,b) (((a)>(b))?(a):(b))
+
+const double win_factor = 1.5 ;
+#define NBINS 36
+
+void
+mexFunction(int nout, mxArray *out[], 
+            int nin, const mxArray *in[])
+{
+  int M,N,S,smin,K ;
+  const int* dimensions ;
+  const double* P_pt ;
+  const double* G_pt ;
+  double* TH_pt ; 
+  double sigma0 ;
+  double H_pt [ NBINS ] ;
+
+  enum {IN_P=0,IN_G,IN_S,IN_SMIN,IN_SIGMA0} ;
+  enum {OUT_Q=0} ;
+
+  /* -----------------------------------------------------------------
+  **                                               Check the arguments
+  ** -------------------------------------------------------------- */ 
+  if (nin != 5) {
+    mexErrMsgTxt("Exactly five input arguments required.");
+  } else if (nout > 1) {
+    mexErrMsgTxt("Too many output arguments.");
+  }
+  
+  if( !uIsRealScalar(in[IN_S]) ) {
+    mexErrMsgTxt("S should be a real scalar") ;
+  }
+                
+  if( !uIsRealScalar(in[IN_SMIN]) ) {
+    mexErrMsgTxt("SMIN should be a real scalar") ;
+  }
+        
+  if( !uIsRealScalar(in[IN_SIGMA0]) ) {
+    mexErrMsgTxt("SIGMA0 should be a real scalar") ;
+  }
+        
+  if( !uIsRealMatrix(in[IN_P],3,-1)) {
+    mexErrMsgTxt("P should be a 3xK real matrix") ;
+  }
+        
+  if(mxGetNumberOfDimensions(in[IN_G]) != 3) {
+    mexErrMsgTxt("SSO must be a three dimensional array") ;
+  }
+
+  dimensions = mxGetDimensions(in[IN_G]) ;
+  M = dimensions[0] ;
+  N = dimensions[1] ;
+  S = (int)(*mxGetPr(in[IN_S])) ;
+  smin = (int)(*mxGetPr(in[IN_SMIN])) ;
+  sigma0 = *mxGetPr(in[IN_SIGMA0]) ;
+        
+  K = mxGetN(in[IN_P]) ;
+  P_pt = mxGetPr(in[IN_P]) ;
+  G_pt = mxGetPr(in[IN_G]) ;
+        
+
+  /* If the input array is empty, then output an empty array as well. */
+  if(K == 0) {    
+    out[OUT_Q] = mxCreateDoubleMatrix(4,0,mxREAL) ;
+    return ;
+  }
+
+  /* ------------------------------------------------------------------
+   *                                                         Do the job
+   * --------------------------------------------------------------- */ 
+  {
+    int p ;
+    const int yo = 1 ;
+    const int xo = M ;
+    const int so = M*N ;
+
+    int buffer_size = K*4 ;
+    double* buffer_start = (double*) mxMalloc( buffer_size *sizeof(double)) ;
+    double* buffer_iterator = buffer_start ;
+    double* buffer_end = buffer_start + buffer_size ;
+
+    for(p = 0 ; p < K ; ++p, TH_pt += 2) {
+      const double x = *P_pt++ ;
+      const double y = *P_pt++ ;
+      const double s = *P_pt++ ;
+      int xi = ((int) (x+0.5)) ; /* Round them off. */
+      int yi = ((int) (y+0.5)) ;
+      int si = ((int) (s+0.5)) - smin ;
+      int xs ;
+      int ys ;
+      double sigmaw = win_factor * sigma0 * pow(2, ((double)s) / S) ;
+      int W = (int) ceil(3.0 * sigmaw) ;
+      int bin ;
+      const double* pt ;
+
+      /* Make sure that the rounded off keypoint index is within bound.
+       */
+      if(xi < 0   || 
+         xi > N-1 || 
+         yi < 0   || 
+         yi > M-1 || 
+         si < 0   || 
+         si > dimensions[2]-1 ) {
+        mexPrintf("Dropping %d: W %d x %d y %d si [%d,%d,%d,%d]\n",p,W,xi,yi,si,M,N,dimensions[2]) ;
+        continue ;
+      }
+      
+      /* Clear histogram buffer. */
+      {
+        int i ;
+        for(i = 0 ; i < NBINS ; ++i) 
+          H_pt[i] = 0 ;
+      }
+
+      pt = G_pt + xi*xo + yi*yo + si*so ;      
+
+#define at(dx,dy) (*(pt + (dx)*xo + (dy)*yo))
+
+      for(xs = max(-W, 1-xi) ; xs <= min(+W, N -2 -xi) ; ++xs) {
+        for(ys = max(-W, 1-yi) ; ys <= min(+W, M -2 -yi) ; ++ys) {
+          double Dx = 0.5 * ( at(xs+1,ys) - at(xs-1,ys) ) ;
+          double Dy = 0.5 * ( at(xs,ys+1) - at(xs,ys-1) ) ;
+          double dx = ((double)(xi+xs)) - x;
+          double dy = ((double)(yi+ys)) - y;
+                                        
+          if(dx*dx + dy*dy > W*W+0.5) continue ;
+
+          {
+            double win = exp( - (dx*dx + dy*dy)/(2*sigmaw*sigmaw) ) ;
+            double mod = sqrt(Dx*Dx + Dy*Dy) ;
+            double theta = fmod(atan2(Dy, Dx) + 2*M_PI, 2*M_PI) ; 
+            bin = (int) floor( NBINS * theta / (2*M_PI) ) ;
+            H_pt[bin] += mod*win ;        
+          }
+        }
+      }
+                        
+      /* Smooth histogram */                    
+      {
+        int iter, i ;
+        for (iter = 0; iter < 6; iter++) {
+          double prev;
+          prev = H_pt[NBINS-1];
+          for (i = 0; i < NBINS; i++) {
+            float newh = (prev + H_pt[i] + H_pt[(i+1) % NBINS]) / 3.0;
+            prev = H_pt[i] ;
+            H_pt[i] = newh ;
+          }
+        }
+      }
+                        
+      /* Find most strong peaks. */
+      {
+        int i ;
+        double maxh = H_pt[0] ;
+        for(i = 1 ; i < NBINS ; ++i)
+          maxh = max(maxh, H_pt[i]) ;
+                                
+        for(i = 0 ; i < NBINS ; ++i) {
+          double h0 = H_pt[i] ;
+          double hm = H_pt[(i-1+NBINS) % NBINS] ;
+          double hp = H_pt[(i+1+NBINS) % NBINS] ;
+          
+          if( h0 > 0.8*maxh && h0 > hm && h0 > hp ) {
+
+            double di = -0.5 * (hp-hm) / (hp+hm-2*h0) ; /*di=0;*/
+            double th = 2*M_PI*(i+di+0.5)/NBINS ;
+
+            if( buffer_iterator == buffer_end ) {
+              int offset = buffer_iterator - buffer_start ;
+              buffer_size += 4*max(1, K/16) ;
+              buffer_start = (double*) mxRealloc(buffer_start,
+                                                 buffer_size*sizeof(double)) ;
+              buffer_end = buffer_start + buffer_size ;
+              buffer_iterator = buffer_start + offset ;
+            }
+            
+            *buffer_iterator++ = x ;
+            *buffer_iterator++ = y ;
+            *buffer_iterator++ = s ;
+            *buffer_iterator++ = th ;
+          }
+        } /* Scan histogram */
+      } /* Find peaks */
+    }
+
+    /* Save back the result. */
+    {
+      double* result ;
+      int NL = (buffer_iterator - buffer_start)/4 ;
+      out[OUT_Q] = mxCreateDoubleMatrix(4, NL, mxREAL) ;
+      result  = mxGetPr(out[OUT_Q]);
+      memcpy(result, buffer_start, sizeof(double) * 4 * NL) ;
+    }
+    mxFree(buffer_start) ;
+  }
+}
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexa64
new file mode 100755
index 0000000..ae1f787
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexa64
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexglx b/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexglx
new file mode 100755
index 0000000..de90e4b
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftormx.mexglx
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftread.m b/SD-VBS/benchmarks/sift/src/matlab/siftread.m
new file mode 100644
index 0000000..76945c8
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftread.m
@@ -0,0 +1,101 @@
+function [frames,descriptors] = siftread(file) 
+% SIFTREAD Read Lowe's SIFT implementation data files
+%   [FRAMES, DESCRIPTORS] = READSIFT(FILE) reads the frames and the
+%   descriptors from the specified file. The function reads files
+%   produced by Lowe's SIFT implementation.
+%     
+%   FRAMES and DESCRIPTORS have the same format used by SIFT(). 
+%
+%   REMARK. Lowe's and our implementations use a silightly different
+%   convention to store the orientation of the frame. When the file
+%   is read, the orientation is changed to match our convention.
+%
+%   See also SIFT().
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+verbosity=0 ;
+
+g = fopen(file, 'r');
+if g == -1
+    error(['Could not open file ''', file, '''.']) ;
+end
+[header, count] = fscanf(g, '%d', [1 2]) ;
+if count ~= 2
+    error('Invalid keypoint file header.');
+end
+K = header(1) ; 
+DL = header(2) ;
+
+if(verbosity > 0)
+        fprintf('%d keypoints, %d descriptor length.\n', K, DL) ;
+end
+
+%creates two output matrices
+P = zeros(4,K) ;
+L = zeros(DL,K) ;
+
+%parse tmp.key
+for k = 1:K
+
+        % Record format: i,j,s,th
+        [record, count] = fscanf(g, '%f', [1 4]) ; 
+        if count ~= 4
+                error(...
+                        sprintf('Invalid keypoint file (parsing keypoint %d)',k) );
+        end
+        P(:,k) = record(:) ;
+        
+        % Record format: descriptor
+        [record, count] = fscanf(g, '%d', [1 DL]) ;
+        if count ~= DL
+                error(...
+                        sprintf('Invalid keypoint file (parsing keypoint %d)',k) );
+        end
+        L(:,k) = record(:) ;
+        
+end
+fclose(g) ;
+
+L=double(L) ;
+P(1:2,:)=flipud(P(1:2,:)) ; % i,j -> x,y
+
+frames=[ P(1:2,:) ; P(3,:) ; -P(4,:) ] ;
+descriptors = L ;
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.c b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.c
new file mode 100644
index 0000000..a1ef8c7
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.c
@@ -0,0 +1,342 @@
+/* file:        siftrefinemx.c
+
+Benchmark               - sift
+Data set                - sqcif
+
+                                                                                < M A T L A B >
+                                                                    Copyright 1984-2006 The MathWorks, Inc.
+                                                                          Version 7.3.0.298 (R2006b)
+                                                                                August 03, 2006
+
+ 
+  To get started, type one of these: helpwin, helpdesk, or demo.
+  For product information, visit www.mathworks.com.
+ 
+Warning: Function /h/g2/kvs/checkParallel/sdvbs-svn/common/matlab/randn.m has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.
+> In path at 113
+  In script_run_profile at 3
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Warning: You are using gcc version "4.1.1".  The earliest gcc version supported
+with mex is "3.4.0".  The latest version tested for use with mex is "3.4.5".
+To download a different version of gcc, visit http://gcc.gnu.org 
+Input size              - (96x96)
+** author:      Andrea Vedaldi
+** description: Subpixel localization, thresholding and off-edge test.
+**/
+
+/* AUTORIGHTS
+Copyright (c) 2006 The Regents of the University of California.
+All Rights Reserved.
+
+Created by Andrea Vedaldi
+UCLA Vision Lab - Department of Computer Science
+
+Permission to use, copy, modify, and distribute this software and its
+documentation for educational, research and non-profit purposes,
+without fee, and without a written agreement is hereby granted,
+provided that the above copyright notice, this paragraph and the
+following three paragraphs appear in all copies.
+
+This software program and documentation are copyrighted by The Regents
+of the University of California. The software program and
+documentation are supplied "as is", without any accompanying services
+from The Regents. The Regents does not warrant that the operation of
+the program will be uninterrupted or error-free. The end-user
+understands that the program was developed for research purposes and
+is advised not to rely exclusively on the program for any reason.
+
+This software embodies a method for which the following patent has
+been issued: "Method and apparatus for identifying scale invariant
+features in an image and use of same for locating an object in an
+image," David G. Lowe, US Patent 6,711,293 (March 23,
+2004). Provisional application filed March 8, 1999. Asignee: The
+University of British Columbia.
+
+IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+*/
+
+#include"mex.h"
+
+#include<mexutils.c>
+
+#include<stdlib.h>
+#include<string.h>
+
+/* Prototype of DGESV LAPACK function for the solution of a linear system. */
+#ifdef WINDOWS
+#define DGESV dgesv
+#undef min
+#undef max
+#else
+#define DGESV dgesv_
+#endif
+
+#ifdef WINDOWS
+#ifdef __cplusplus__
+extern "C" {
+    extern int DGESV(int *n, int *nrhs, double *a, int *lda,
+                     int *ipiv, double *b, int *ldb, int *info) ;
+}
+#else
+  extern int DGESV(int *n, int *nrhs, double *a, int *lda,
+                     int *ipiv, double *b, int *ldb, int *info) ;
+#define sqrtf(x) ((float)sqrt((double)x)
+#define powf(x)  ((float)pow((double)x)
+#define fabsf(x) ((float)fabs((double)x)
+#endif
+#else
+extern int DGESV(int *n, int *nrhs, double *a, int *lda,
+                 int *ipiv, double *b, int *ldb, int *info) ;
+#endif
+
+#define greater(a,b) ((a) > (b))
+#define min(a,b) (((a)<(b))?(a):(b))
+#define max(a,b) (((a)>(b))?(a):(b))
+
+const int max_iter = 5 ;
+
+void
+mexFunction(int nout, mxArray *out[], 
+            int nin, const mxArray *in[])
+{
+  int M,N,S,smin,K ;
+  const int* dimensions ;
+  const double* P_pt ;
+  const double* D_pt ; 
+  double threshold = 0.01 ; /*0.02 ;*/
+  double r = 10.0 ;
+  double* result ;
+  enum {IN_P=0,IN_D,IN_SMIN,IN_THRESHOLD,IN_R} ;
+  enum {OUT_Q=0} ;
+        
+  /* -----------------------------------------------------------------
+  **                                               Check the arguments
+  ** -------------------------------------------------------------- */ 
+  if (nin < 3) {
+    mexErrMsgTxt("At least three input arguments required.");
+  } else if (nout > 1) {
+    mexErrMsgTxt("Too many output arguments.");
+  }
+  
+  if( !uIsRealMatrix(in[IN_P],3,-1) ) {
+    mexErrMsgTxt("P must be a 3xK real matrix") ;
+  }
+
+  if( !mxIsDouble(in[IN_D]) || mxGetNumberOfDimensions(in[IN_D]) != 3) {
+    mexErrMsgTxt("G must be a three dimensional real array.") ;
+  }
+
+  if( !uIsRealScalar(in[IN_SMIN]) ) {
+    mexErrMsgTxt("SMIN must be a real scalar.") ;
+  }
+
+  if(nin >= 4) {
+    if(!uIsRealScalar(in[IN_THRESHOLD])) {
+      mexErrMsgTxt("THRESHOLD must be a real scalar.") ;
+    }
+    threshold = *mxGetPr(in[IN_THRESHOLD]) ;
+  }
+  
+  if(nin >= 5) {
+    if(!uIsRealScalar(in[IN_R])) {
+      mexErrMsgTxt("R must be a real scalar.") ;
+    }
+    r = *mxGetPr(in[IN_R]) ;    
+  }
+  
+  dimensions = mxGetDimensions(in[IN_D]) ;
+  M = dimensions[0] ;
+  N = dimensions[1] ;
+  S = dimensions[2] ; 
+  smin = (int)(*mxGetPr(in[IN_SMIN])) ;
+  
+  if(S < 3 || M < 3 || N < 3) {
+    mexErrMsgTxt("All dimensions of DOG must be not less than 3.") ;
+  }
+  
+  K = mxGetN(in[IN_P]) ;  
+  P_pt = mxGetPr(in[IN_P]) ;
+  D_pt = mxGetPr(in[IN_D]) ;
+
+  /* If the input array is empty, then output an empty array as well. */
+  if( K == 0) {
+    out[OUT_Q] = mxDuplicateArray(in[IN_P]) ;
+    return ;
+  }
+
+  /* -----------------------------------------------------------------
+   *                                                        Do the job
+   * -------------------------------------------------------------- */
+  {    
+    double* buffer = (double*) mxMalloc(K*3*sizeof(double)) ;
+    double* buffer_iterator = buffer ;
+    int p ;
+    const int yo = 1 ;
+    const int xo = M ;
+    const int so = M*N ;
+    
+/*    printf("Actual values = %d\n\n", K);
+*/  
+    for(p = 0 ; p < K ; ++p) {
+      int x = ((int)*P_pt++) ;
+      int y = ((int)*P_pt++) ;
+/*      printf("%d\t%d\n", ((int)*P_pt), smin);
+*/  
+      int s = ((int)*P_pt++) - smin ;
+      int iter ;
+      double b[3] ;
+        
+      /* Local maxima extracted from the DOG
+       * have coorrinates 1<=x<=N-2, 1<=y<=M-2
+       * and 1<=s-mins<=S-2. This is also the range of the points
+       * that we can refine.
+       */
+/*      printf("%d\t%d\t%d\t%d\t%d\t%d\n", x, N-2,y,M-2, s, S-2);
+*/  
+      if(x < 1 || x > N-2 ||
+         y < 1 || y > M-2 ||
+         s < 1 || s > S-2) {
+        continue ;
+      }
+
+#define at(dx,dy,ds) (*(pt + (dx)*xo + (dy)*yo + (ds)*so))
+
+      {
+        const double* pt = D_pt + y*yo + x*xo + s*so ;      
+  
+        double Dx=0,Dy=0,Ds=0,Dxx=0,Dyy=0,Dss=0,Dxy=0,Dxs=0,Dys=0 ;
+        int dx = 0 ;
+        int dy = 0 ;
+/*        printf("%d\t%d\t%d\t%d\t%d\t%d\t%d\t%f\t%f\n",S, y, yo, x, xo, s, so, *D_pt, *pt); 
+*/        
+        for(iter = 0 ; iter < max_iter ; ++iter) {
+
+          double A[3*3] ;          
+          int ipiv[3] ;
+          int n = 3 ;
+          int one = 1 ;
+          int info = 0 ;
+
+#define Aat(i,j) (A[(i)+(j)*3])    
+
+          x += dx ;
+          y += dy ;
+          pt = D_pt + y*yo + x*xo + s*so ;
+          
+          /* Compute the gradient. */
+          Dx = 0.5 * (at(+1,0,0) - at(-1,0,0)) ;
+          Dy = 0.5 * (at(0,+1,0) - at(0,-1,0));
+          Ds = 0.5 * (at(0,0,+1) - at(0,0,-1)) ;
+          
+          /* Compute the Hessian. */
+          Dxx = (at(+1,0,0) + at(-1,0,0) - 2.0 * at(0,0,0)) ;
+          Dyy = (at(0,+1,0) + at(0,-1,0) - 2.0 * at(0,0,0)) ;
+          Dss = (at(0,0,+1) + at(0,0,-1) - 2.0 * at(0,0,0)) ;
+          
+          Dxy = 0.25 * ( at(+1,+1,0) + at(-1,-1,0) - at(-1,+1,0) - at(+1,-1,0) ) ;
+          Dxs = 0.25 * ( at(+1,0,+1) + at(-1,0,-1) - at(-1,0,+1) - at(+1,0,-1) ) ;
+          Dys = 0.25 * ( at(0,+1,+1) + at(0,-1,-1) - at(0,-1,+1) - at(0,+1,-1) ) ;
+          
+          /* Solve linear system. */
+          Aat(0,0) = Dxx ;
+          Aat(1,1) = Dyy ;
+          Aat(2,2) = Dss ;
+          Aat(0,1) = Aat(1,0) = Dxy ;
+          Aat(0,2) = Aat(2,0) = Dxs ;
+          Aat(1,2) = Aat(2,1) = Dys ;
+          
+          b[0] = - Dx ;
+          b[1] = - Dy ;
+          b[2] = - Ds ;
+          
+   /*       DGESV (&n, &one, A, &n, ipiv, b, &n, &info) ;
+    */      
+          /* If the translation of the keypoint is big, move the keypoint
+           * and re-iterate the computation. Otherwise we are all set.
+           */
+          dx= ((b[0] >  0.6 && x < N-2) ?  1 : 0 )
+            + ((b[0] < -0.6 && x > 1  ) ? -1 : 0 ) ;
+          
+          dy= ((b[1] >  0.6 && y < M-2) ?  1 : 0 )
+            + ((b[1] < -0.6 && y > 1  ) ? -1 : 0 ) ;
+          
+          if( dx == 0 && dy == 0 ) break ;
+          
+        }
+                                
+        {
+          double val = at(0,0,0) + 0.5 * (Dx * b[0] + Dy * b[1] + Ds * b[2]) ; 
+          double score = (Dxx+Dyy)*(Dxx+Dyy) / (Dxx*Dyy - Dxy*Dxy) ; 
+          double xn = x + b[0] ;
+          double yn = y + b[1] ;
+          double sn = s + b[2] ;
+         
+/*        printf("%f\t%f\t%f\t%f\t%f\t%f\t%f\t%f\t%f\t%f\t%f\n", fabs(val),threshold,score,(r+1)*(r+1)/r,fabs(b[0]), fabs(b[1]), fabs(b[2]),xn,yn,sn,r);
+*/          
+          if(fabs(val) > threshold &&
+             score < (r+1)*(r+1)/r && 
+             score >= 0 &&
+             fabs(b[0]) < 1.5 &&
+             fabs(b[1]) < 1.5 &&
+             fabs(b[2]) < 1.5 &&
+             xn >= 0 &&
+             xn <= N-1 &&
+             yn >= 0 &&
+             yn <= M-1 &&
+             sn >= 0 &&
+             sn <= S-1) {
+            *buffer_iterator++ = xn ;
+            *buffer_iterator++ = yn ;
+            *buffer_iterator++ = sn+smin  ;
+          }
+        }
+      }
+    }      
+
+    /* Copy the result into an array. */
+    {
+        int i;
+      int NL = (buffer_iterator - buffer)/3 ;
+/*      printf("%NL VALUE = %d\t%d\t%d\n", NL, buffer_iterator, buffer);
+*/
+      out[OUT_Q] = mxCreateDoubleMatrix(3, NL, mxREAL) ;
+      result = mxGetPr(out[OUT_Q]);
+        for(i=0; i<(3*NL); i++)
+        {
+            result[i] = buffer[i];
+/*            printf("%f\t", buffer[i]);
+*/  
+        }
+/*        printf("\n");
+      memcpy(result, buffer, sizeof(double) * 3 * NL) ;
+*/
+    }
+    mxFree(buffer) ;
+  }
+  
+}
+
+
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.m b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.m
new file mode 100644
index 0000000..222d610
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.m
@@ -0,0 +1,61 @@
+% SIFTREFINEMX  Subpixel localization, thresholding and on-edge test
+%   Q = SIFTREFINEMX(P, OCTAVE, SMIN) refines, thresholds and performs
+%   the on-edge test for the SIFT frames P extracted from the DOG
+%   octave OCTAVE with parameter SMIN (see GAUSSIANSS()).
+%
+%   Q = SIFTREFINEMX(P, OCTAVE, SMIN, THRESH, R) specifies custom
+%   values for the local maximum strength threshold THRESH and the
+%   local maximum peakedeness threshold R.
+%
+%   OCTAVE is an octave of the Difference Of Gaussian scale space. P
+%   is a 3xK matrix specifying the indexes (X,Y,S) of the points of
+%   extremum of the octave OCTAVE. The spatial indexes X,Y are integer
+%   with base zero. The scale index S is integer with base SMIN and
+%   represents a scale sublevel in the specified octave.
+%
+%   The function returns a matrix Q containing the refined keypoints.
+%   The matrix has the same format as P, except that the indexes are
+%   now fractional. The function drops the points that do not satisfy
+%   the strength and peakedness tests.
+%
+%   See also SIFT().
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexa64 b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexa64
new file mode 100755
index 0000000..c91556b
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexa64
diff --git a/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexglx b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexglx
new file mode 100755
index 0000000..74b312c
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/siftrefinemx.mexglx
diff --git a/SD-VBS/benchmarks/sift/src/matlab/tightsubplot.m b/SD-VBS/benchmarks/sift/src/matlab/tightsubplot.m
new file mode 100644
index 0000000..b790ef0
--- /dev/null
+++ b/SD-VBS/benchmarks/sift/src/matlab/tightsubplot.m
@@ -0,0 +1,151 @@
+function H = tightsubplot(varargin)
+% TIGHTSUBPLOT  Tiles axes without wasting space
+%   H = TIGHTSUBPLOT(K,P) returns an handle to the P-th axis in a
+%   regular grid of K axes. The K axes are numbered from left to right
+%   and from top to bottom.  The function operates similarly to
+%   SUBPLOT(), but by default it does not put any margin between axes.
+%
+%   H = TIGHTSUBPLOT(M,N,P) retursn an handle to the P-th axes in a
+%   regular subdivision with M rows and N columns.
+%
+%   The function accepts the following option-value pairs:
+%
+%   'Spacing' [0]
+%     Set extra spacing between axes.  The space is added between the
+%     inner or outer boxes, depending on the setting below.
+%
+%   'Box' ['inner'] (** ONLY >R14 **)
+%     If set to 'outer', the function displaces the axes by their
+%     outer box, thus protecting title and labels. Unfortunately
+%     MATLAB typically picks unnecessarily large insets, so that a bit
+%     of space is wasted in this case.  If set to 'inner', the
+%     function uses the inner box. This causes the instets of nearby
+%     axes to overlap, but it is very space conservative.
+%
+%   REMARK. While SUBPLOT kills any pre-existing axes that overalps a
+%   new one, this function does not.
+%
+%   See also SUBPLOT().
+
+% AUTORIGHTS
+% Copyright (c) 2006 The Regents of the University of California.
+% All Rights Reserved.
+% 
+% Created by Andrea Vedaldi
+% UCLA Vision Lab - Department of Computer Science
+% 
+% Permission to use, copy, modify, and distribute this software and its
+% documentation for educational, research and non-profit purposes,
+% without fee, and without a written agreement is hereby granted,
+% provided that the above copyright notice, this paragraph and the
+% following three paragraphs appear in all copies.
+% 
+% This software program and documentation are copyrighted by The Regents
+% of the University of California. The software program and
+% documentation are supplied "as is", without any accompanying services
+% from The Regents. The Regents does not warrant that the operation of
+% the program will be uninterrupted or error-free. The end-user
+% understands that the program was developed for research purposes and
+% is advised not to rely exclusively on the program for any reason.
+% 
+% This software embodies a method for which the following patent has
+% been issued: "Method and apparatus for identifying scale invariant
+% features in an image and use of same for locating an object in an
+% image," David G. Lowe, US Patent 6,711,293 (March 23,
+% 2004). Provisional application filed March 8, 1999. Asignee: The
+% University of British Columbia.
+% 
+% IN NO EVENT SHALL THE UNIVERSITY OF CALIFORNIA BE LIABLE TO ANY PARTY
+% FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES,
+% INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE AND
+% ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF CALIFORNIA HAS BEEN
+% ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF
+% CALIFORNIA SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT
+% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+% A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS"
+% BASIS, AND THE UNIVERSITY OF CALIFORNIA HAS NO OBLIGATIONS TO PROVIDE
+% MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+sp=0.0 ;
+use_outer=0 ;
+
+% --------------------------------------------------------------------
+%                                                      Parse arguments
+% --------------------------------------------------------------------
+K=varargin{1} ;
+p=varargin{2} ;
+N = ceil(sqrt(K)) ;
+M = ceil(K/N) ;
+
+a=3 ;
+NA = length(varargin) ;
+if NA > 2
+  if isa(varargin{3},'char')
+    % Called with K and p
+  else
+    % Called with M,N and p
+    a = 4 ;
+    M = K ;
+    N = p ;
+    p = varargin{3} ;
+  end
+end
+
+for a=a:2:NA
+  switch varargin{a}
+    case 'Spacing'
+      sp=varargin{a+1} ;
+    case 'Box'      
+      switch varargin{a+1}
+        case 'inner'
+          use_outer = 0 ;
+        case 'outer'
+        if ~strcmp(version('-release'), '14')
+          %warning(['Box option supported only on MATALB 14']) ;
+          continue;
+        end
+        use_outer = 1 ;
+        otherwise
+          error(['Box is either ''inner'' or ''outer''']) ;
+      end
+    otherwise
+      error(['Uknown parameter ''', varargin{a}, '''.']) ;
+  end      
+end
+
+% --------------------------------------------------------------------
+%                                                  Check the arguments
+% --------------------------------------------------------------------
+
+[j,i]=ind2sub([N M],p) ;
+i=i-1 ;
+j=j-1 ;
+
+dt = sp/2 ;
+db = sp/2 ;
+dl = sp/2 ;
+dr = sp/2 ;
+
+pos = [  j*1/N+dl,...
+       1-i*1/M-1/M-db,...
+       1/N-dl-dr,...
+       1/M-dt-db] ;
+
+switch use_outer
+  case 0
+    H = findobj(gcf, 'Type', 'axes', 'Position', pos) ;
+    if(isempty(H))
+      H = axes('Position', pos) ;
+    else
+      axes(H) ;
+    end
+    
+  case 1
+    H = findobj(gcf, 'Type', 'axes', 'OuterPosition', pos) ;
+    if(isempty(H))
+      H = axes('ActivePositionProperty', 'outerposition',...
+               'OuterPosition', pos) ;
+    else
+      axes(H) ;
+    end
+end    
diff --git a/SD-VBS/benchmarks/stitch/Makefile b/SD-VBS/benchmarks/stitch/Makefile
new file mode 100644
index 0000000..60cc0ec
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/Makefile
@@ -0,0 +1,3 @@
+include ../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/stitch/data/Makefile b/SD-VBS/benchmarks/stitch/data/Makefile
new file mode 100644
index 0000000..121b0d2
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/Makefile
@@ -0,0 +1,2 @@
+include ../../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
diff --git a/SD-VBS/benchmarks/stitch/data/cif/1.bmp b/SD-VBS/benchmarks/stitch/data/cif/1.bmp
new file mode 100644
index 0000000..f84e26c
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/cif/1.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/cif/2.bmp b/SD-VBS/benchmarks/stitch/data/cif/2.bmp
new file mode 100644
index 0000000..787dd67
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/cif/2.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/cif/3.bmp b/SD-VBS/benchmarks/stitch/data/cif/3.bmp
new file mode 100644
index 0000000..e97cd23
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/cif/3.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/cif/Makefile b/SD-VBS/benchmarks/stitch/data/cif/Makefile
new file mode 100644
index 0000000..291f322
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/cif/Makefile
@@ -0,0 +1,8 @@
+INPUT=cif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=stitch
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
+
diff --git a/SD-VBS/benchmarks/stitch/data/cif/expected.m b/SD-VBS/benchmarks/stitch/data/cif/expected.m
new file mode 100644
index 0000000..dc9aad2
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/cif/expected.m
@@ -0,0 +1,104 @@
+-1.267254       0.448087        0.269846        -0.046516       0.008815        -0.302984       -0.547297       -0.397124       0.454872        3.378042        2.804183        2.121006        2.014771        1.811798        0.806877        0.642709        -0.211614       2.266383        1.511370        0.800596        0.385946        0.473907        0.160869        0.031233        -1.134224       0.933532        0.579118        0.000096        -0.246471       -0.177921       -0.056162       -0.072827       -1.490613       0.042324        0.043825        -0.150114       -0.271740       -0.353742       -0.215269       -0.265320       -1.615147       -0.183971       -0.134671       -0.246453       -0.467647       -0.470726       -0.369555       -0.227479       -1.667640       -0.352695       -0.308670       -0.431446       -0.729182       -0.902388       -0.715257       -0.264311       -1.841068       -0.398765       -0.252229       -0.959242       -0.718953       -0.800257       -0.587460       -0.137802       
+-1.087448       -1.146922       -1.317673       -0.949723       -0.264679       -0.680521       -1.284745       -1.343582       -0.193472       -0.224010       -0.443379       -0.146132       1.717100        0.637961        -0.109907       -0.239492       -0.563322       -0.591768       -1.159393       -0.890598       0.918022        0.220444        -0.382076       -0.449357       -0.339664       -0.408725       -0.742055       -1.233748       0.404447        1.067418        0.118021        -0.433767       0.613224        0.429261        -0.859715       -0.607095       0.113293        1.788760        2.194819        0.859603        -0.526522       -0.629381       -0.760216       -0.466531       0.043160        1.622856        2.282871        2.349126        -0.512319       -0.982606       -0.691455       -0.501222       -0.193997       1.322832        1.690775        2.170050        0.981230        -1.083554       -0.674515       -0.651167       -0.250662       0.486269        0.562692        1.422881        
+1.125106        0.157780        0.031064        -0.167333       0.058357        0.184717        0.118472        -1.711094       3.130139        1.964384        1.525984        1.017099        1.590918        1.957499        1.583888        -0.929536       1.609271        0.820711        0.392990        -0.119024       -0.020304       0.185471        0.113563        -1.236081       0.525310        0.115715        -0.153787       -0.257190       -0.036052       0.548610        0.364845        -0.855888       1.336483        0.355124        -0.153996       -0.066430       0.411634        0.647309        1.280493        -0.664836       -0.195753       -0.023536       -0.259090       -0.749710       -0.928005       -1.076163       -0.836965       -1.673589       -0.532697       -0.976909       -0.496306       -0.835640       -0.395471       -0.262239       -0.920597       -1.801607       0.341613        0.328638        -0.049661       -0.992224       -0.666015       -0.476336       -1.037958       -2.265167       
+0.334098        0.718860        1.041120        1.063526        0.978217        0.941954        0.649160        -2.025505       0.349512        0.250917        0.371397        1.007732        1.240647        0.876760        0.559884        -2.262853       0.428511        0.565964        0.665059        0.839518        0.867693        0.909356        0.860263        -2.021370       0.549475        0.254836        0.964393        0.953533        0.209559        0.419035        0.378539        -2.107130       0.716301        0.568012        0.285110        0.272843        0.526713        0.009228        -0.044852       -2.405884       0.090393        0.383941        0.507853        0.363745        0.318608        -0.023200       -0.351668       -2.549061       0.091389        -0.417362       -0.177876       -0.239159       -0.130580       0.039704        -0.271974       -2.463456       -0.342495       -0.305237       -0.498452       -0.427523       -0.456802       -0.626943       -0.569719       -2.704254       
+-1.705739       -1.685635       -1.218863       -0.574561       0.781527        0.883086        0.740894        -0.290289       -0.638825       -0.430510       0.254675        0.550182        1.604348        2.796916        2.878283        1.635575        -0.513173       -0.008739       0.343393        0.029231        0.324651        0.999972        1.257020        0.416405        -1.015380       -0.436270       -0.307826       -0.221728       0.272884        0.510250        0.101503        -0.335130       -0.882432       -0.347882       -0.312355       -0.321934       0.131654        1.164120        0.966224        -0.079917       -0.657227       -0.130379       -0.189491       -0.819045       -0.235767       0.132874        -0.667159       -0.483573       0.642963        -0.832525       -1.159086       -1.310377       -1.141931       1.271637        -1.026346       -1.499881       2.357137        1.280223        -0.760726       -0.830539       -1.325880       0.271971        -0.094320       -0.108152       
+-1.606386       -0.579863       -0.851971       0.871034        0.887097        -0.737442       -0.800894       1.180769        -0.924622       -0.495797       0.085365        2.616354        3.063924        -0.495805       -1.030185       0.433201        -0.782149       -0.591362       0.129508        -0.203553       1.709221        0.027835        -0.985025       0.052961        0.084859        1.418248        0.105660        1.833765        1.536360        -0.566795       -0.617625       0.064815        1.393955        1.867039        -1.562383       1.149811        1.014435        -1.096732       -0.650901       -0.092726       0.396262        -0.883391       0.091487        0.337467        -0.371518       -0.735661       -0.070816       0.072748        0.232594        -0.609076       0.261734        -0.106559       -0.906475       0.429863        0.686790        0.420799        -0.657616       -0.196819       0.194704        -0.737794       -1.542330       -1.610329       -0.896509       -0.653555       
+-0.010539       -1.474051       -1.688084       -1.807864       -0.767107       -1.042989       0.703907        0.720193        -0.244444       -0.726836       0.254204        -1.116647       -0.681876       -0.092656       2.473426        2.927202        0.507234        -0.154496       0.456106        -0.972198       -0.778766       -0.047901       -0.385580       1.553716        -0.645902       -0.303412       0.364314        -0.093169       1.258708        -0.072080       1.679987        1.378458        -0.664680       1.466264        0.486998        1.234078        1.713721        -1.763250       0.986549        0.849296        -0.068957       0.806911        0.453206        0.222551        -1.074844       -0.086449       0.162942        -0.555874       -0.102245       -0.277574       0.961204        0.056614        -0.796725       0.086159        -0.287241       -1.098248       -0.326304       -0.556317       0.877996        -0.845938       -0.378752       0.018200        -0.927228       -1.742919       
+-0.040352       -0.261902       -0.139878       0.149141        -0.699851       -0.174246       0.169175        0.723798        0.372626        0.348355        0.213191        2.845392        -0.882088       -0.143665       -0.101515       0.621502        0.313743        0.223921        1.273114        3.949839        -1.853493       -0.655349       -0.284604       0.888277        1.047223        0.558159        1.305731        2.558955        -1.039506       -1.004223       -0.455133       1.183205        1.252828        0.232932        -0.385239       -0.245253       -0.608557       -0.838720       -0.399788       0.746316        -0.747987       -0.011735       0.135660        -1.376170       -0.396197       -0.516833       -0.158018       0.710970        -2.298968       -1.179833       -0.697159       -0.763670       -0.263035       -0.614155       -0.226431       0.257192        -0.606669       -0.067546       -0.383522       -0.459449       -0.353852       -0.663801       -0.259626       0.176770        
+-0.804537       -0.891026       -0.633777       -0.010766       -1.172612       -0.392628       2.686816        2.335384        -0.709068       -0.960799       -0.682825       -0.336097       -0.908980       -0.211723       1.792421        1.849255        -0.774178       -0.996392       -0.706624       -0.393754       -0.831537       -0.721601       1.423068        2.146664        -0.814402       -1.007484       -0.921527       -0.179968       -0.811193       -0.836264       2.625443        2.517647        -0.415980       -0.887757       -0.610982       2.104052        -0.393979       0.314342        0.598294        -0.216146       -0.552166       -1.061414       -0.351713       0.326139        0.011145        0.013701        0.208541        -0.304741       0.544936        -0.253484       -0.403662       -0.539295       0.010613        0.130005        0.387713        0.033129        0.497218        0.089021        0.494759        0.448510        -0.020941       -0.125755       -0.294173       -0.446867       
+0.435031        0.504540        1.286894        0.845405        -0.236961       0.337424        -0.396879       -0.151134       -0.425745       -0.046250       1.832746        -0.090504       1.832500        1.880526        -0.029352       -0.632321       -0.869795       -0.302584       1.851994        -0.824615       1.631254        0.253016        0.099681        -1.004447       -1.127312       -0.336147       2.300958        0.190572        0.130685        -0.383311       -1.140005       -1.351236       -1.006603       -0.458487       1.705522        1.458562        -1.034782       -0.418808       -1.515751       -1.532834       -0.821341       -0.331360       1.077007        1.116946        -0.658202       -0.557990       -1.011452       -1.075149       -0.766921       -0.689666       0.817453        1.325943        0.052877        -0.498913       -0.902811       -0.770947       -0.752624       -0.770242       1.662394        1.586643        -0.286034       -0.381948       -0.315868       -0.309240       
+0.895959        -0.271193       -0.449731       -0.460721       -0.539533       -0.643986       -0.852944       -0.875205       2.196452        -0.151345       -0.637590       -0.688312       -0.796203       -0.844449       -0.761364       -0.614462       2.040102        0.928982        -0.625901       -0.731416       -0.893093       -0.637153       -0.692900       -0.474516       1.387754        0.963944        -0.075080       0.476305        -0.228594       0.007311        -0.395027       -0.259323       1.911748        0.065512        1.911511        1.957615        0.124216        -0.454608       -0.765911       0.111981        1.930225        -0.639202       1.718325        0.395277        0.248082        -0.811832       -0.659925       0.145599        2.361211        0.335333        0.277844        -0.215570       -0.941963       -1.144735       -0.793416       -0.464966       1.789619        1.552548        -0.840953       -0.249645       -1.302662       -1.319061       -0.654916       -0.874049       
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+-1.018409       -0.761813       -0.448380       -0.236457       -0.662085       -0.068668       0.860551        0.427478        -1.356872       -0.981136       -0.747511       -0.498811       -0.276953       -0.587132       -0.003072       -0.201595       -1.140385       -0.553719       -0.780368       -1.307712       -1.094028       -0.349899       -0.333739       -0.641537       -1.235764       -1.314785       -0.666304       -0.668636       -1.126321       -0.827488       -0.515805       -0.310529       0.624529        1.101553        1.332510        1.086395        1.442488        1.066435        0.593522        0.646761        1.494729        2.370780        2.048071        1.828163        1.950318        1.363165        1.675331        1.381414        -0.107427       0.468927        -0.382813       -0.610422       -0.279138       0.430538        1.485522        0.278221        -1.326026       -0.541488       -1.366676       -1.194652       -0.376367       0.292967        0.490349        0.160205        
+-2.898661       -2.937382       -2.871673       -2.300486       -1.992630       -1.848523       -2.580640       -2.702846       0.201111        0.360054        0.433676        0.471531        0.530550        0.257036        -0.369359       -0.522128       0.524822        0.493873        0.583405        0.489055        0.565029        0.471659        0.489366        0.524174        0.638933        0.528716        0.406930        0.527185        0.595129        0.489631        0.466923        0.496102        0.476860        0.498082        0.581363        0.447603        0.345615        0.605930        0.824704        0.745277        0.234716        0.211606        0.151386        0.282833        0.211216        0.571705        0.747931        0.690151        0.139773        0.194973        0.196696        0.203605        0.189087        0.217615        0.404851        0.653961        -0.029854       -0.095234       0.015909        0.107669        -0.017815       0.045756        0.409477        0.215985        
diff --git a/SD-VBS/benchmarks/stitch/data/cif/stitch b/SD-VBS/benchmarks/stitch/data/cif/stitch
new file mode 100755
index 0000000..df8c9bc
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/cif/stitch
diff --git a/SD-VBS/benchmarks/stitch/data/fullhd/1.bmp b/SD-VBS/benchmarks/stitch/data/fullhd/1.bmp
new file mode 100644
index 0000000..bd46057
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/fullhd/1.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/fullhd/2.bmp b/SD-VBS/benchmarks/stitch/data/fullhd/2.bmp
new file mode 100644
index 0000000..c5f7748
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/fullhd/2.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/fullhd/Makefile b/SD-VBS/benchmarks/stitch/data/fullhd/Makefile
new file mode 100644
index 0000000..dff255f
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/fullhd/Makefile
@@ -0,0 +1,8 @@
+INPUT=fullhd
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=stitch
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
+
diff --git a/SD-VBS/benchmarks/stitch/data/fullhd/stitch b/SD-VBS/benchmarks/stitch/data/fullhd/stitch
new file mode 100755
index 0000000..7105598
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/fullhd/stitch
diff --git a/SD-VBS/benchmarks/stitch/data/qcif/1.bmp b/SD-VBS/benchmarks/stitch/data/qcif/1.bmp
new file mode 100644
index 0000000..a9bdd5d
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/qcif/1.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/qcif/2.bmp b/SD-VBS/benchmarks/stitch/data/qcif/2.bmp
new file mode 100644
index 0000000..f8a1569
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/qcif/2.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/qcif/Makefile b/SD-VBS/benchmarks/stitch/data/qcif/Makefile
new file mode 100644
index 0000000..7d07214
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/qcif/Makefile
@@ -0,0 +1,7 @@
+INPUT=qcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=stitch
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/stitch/data/qcif/expected.m b/SD-VBS/benchmarks/stitch/data/qcif/expected.m
new file mode 100644
index 0000000..160931e
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/qcif/expected.m
@@ -0,0 +1,48 @@
+-1.354127       0.558907        0.029724        -0.180108       -0.517136       -0.362920       0.162714        -0.548816       0.192864        2.743817        1.437628        1.222697        0.387461        0.716613        0.748615        0.318589        -1.378618       0.713755        0.003323        -0.116410       0.069268        0.006910        0.051049        0.303413        -1.763481       -0.001520       -0.233449       -0.409591       -0.134833       -0.070118       0.134256        -0.013045       -1.984464       -0.205120       -0.732187       -0.897908       -0.350145       0.224984        -0.061761       0.857919        -1.872651       0.174361        -0.421059       0.365301        -0.168333       0.817813        0.251503        2.904430        -1.472165       0.946202        1.183967        1.433838        0.610162        2.599045        0.283999        0.340085        -1.868841       -0.412931       -0.789055       -1.049011       -1.166659       -1.037729       -0.770446       -0.450572       
+-0.241535       -0.824120       -1.234248       -1.069897       -0.255446       -1.268364       -1.449678       -1.386019       0.238189        -0.113908       -0.335900       -0.951718       1.065197        -0.035897       -0.172191       -0.142805       -0.332964       -0.126333       0.069067        -0.883083       1.559820        1.411138        -0.220282       -0.380990       -0.264835       -0.385442       -0.377388       -0.339908       1.230179        3.083909        0.851223        -0.747097       -0.425330       0.327684        -0.678965       -0.470953       0.629347        1.951452        1.661047        -0.122452       -0.168835       2.003324        -1.243731       -0.667572       -0.258366       0.803682        0.428635        2.840524        -0.142229       -0.096307       -0.985571       -0.720763       -0.652517       0.441908        1.189678        0.386220        -1.005586       -0.743680       -0.755876       -0.566964       -0.562676       0.368788        1.846846        -0.579437       
+-1.760179       -1.109349       0.688788        1.364293        0.064104        -0.347365       -0.099277       -0.061512       -0.145283       1.019199        1.137542        2.732471        1.459993        0.352364        0.336541        0.477941        -0.512381       0.167130        0.587152        1.254995        0.179812        -0.377153       0.256982        1.041496        -0.207084       -0.043320       -0.127417       0.496010        -0.281337       -0.707286       -1.117478       -1.085239       1.943963        -0.891422       -1.175818       0.733879        -0.684686       -1.201789       -0.897712       -1.415550       -0.431712       1.101814        -1.016301       1.613015        1.082414        0.342475        -0.606184       -2.074193       0.244697        2.019770        -1.186535       0.296276        -0.148982       -0.717920       -1.154789       -1.767143       0.288342        1.385684        -1.163885       0.386478        0.264538        0.052286        -0.159590       -0.696574       
+-0.517577       -2.519817       0.852604        1.282481        -1.105907       -1.345469       0.263167        -0.931763       -0.819903       -1.734291       -1.171061       -0.718670       0.573096        -1.211099       1.003707        0.556755        -0.469640       -0.321052       -0.751568       -0.148896       1.346337        -1.354496       -0.105449       -0.480512       -0.387757       0.001450        1.619421        -0.112132       0.812215        -1.335417       -0.029467       -0.132184       0.268010        0.376827        -0.972901       -0.325035       -0.680558       -0.513337       0.187931        0.164303        -0.428427       0.107254        -0.852449       -0.307095       -1.974132       -1.045485       0.249183        2.313638        0.876658        1.651585        1.306377        0.618823        0.465712        -0.203982       -0.726471       2.271423        0.400177        0.876783        0.814554        0.664622        0.923191        1.305049        0.307421        1.273242        
+1.006143        -0.429333       -2.553203       1.024083        1.480074        -1.053402       -1.307516       0.398839        -0.489483       -0.750024       -1.719959       -1.122514       -0.642641       0.727596        -1.164984       1.184366        -0.657138       -0.378483       -0.220869       -0.677538       -0.038255       1.547809        -1.317092       0.007832        -1.861390       -0.291626       0.121224        1.837482        0.000742        0.981241        -1.296854       0.088428        -1.122033       0.403977        0.519405        -0.912316       -0.225094       -0.602214       -0.424835       0.319034        0.093226        -0.334767       0.233455        -0.784547       -0.206064       -1.974369       -0.989310       0.384006        1.019506        1.049598        1.871600        1.505422        0.776101        0.613688        -0.096687       -0.650916       0.649519        0.544173        1.049731        0.983721        0.824682        1.098958        1.504013        0.445782        
+-1.794177       -1.842775       -1.191605       0.607473        1.283332        -0.017538       -0.429222       -0.181005       -0.445874       -0.227034       0.938056        1.056462        2.652225        1.379081        0.270873        0.255042        -1.026460       -0.594324       0.085542        0.505784        1.173977        0.098231        -0.459026       0.175441        0.244053        -0.288867       -0.125018       -0.209159       0.414594        -0.363159       -0.789331       -1.199738       1.352707        1.863304        -0.973564       -1.258109       0.652588        -0.766720       -1.284093       -0.979857       -1.050952       -0.513613       1.020715        -1.098508       1.532184        1.001305        0.260979        -0.688176       -0.552689       0.163150        1.939151        -1.268831       0.214756        -0.230735       -0.799971       -1.237068       2.263513        0.206818        1.304734        -1.246169       0.305005        0.183001        -0.029362       -0.241349       
+1.006143        -0.429333       -2.553203       1.024083        1.480074        -1.053402       -1.307516       0.398839        -0.489483       -0.750024       -1.719959       -1.122514       -0.642641       0.727596        -1.164984       1.184366        -0.657138       -0.378483       -0.220869       -0.677538       -0.038255       1.547809        -1.317092       0.007832        -1.861390       -0.291626       0.121224        1.837482        0.000742        0.981241        -1.296854       0.088428        -1.122033       0.403977        0.519405        -0.912316       -0.225094       -0.602214       -0.424835       0.319034        0.093226        -0.334767       0.233455        -0.784547       -0.206064       -1.974369       -0.989310       0.384006        1.019506        1.049598        1.871600        1.505422        0.776101        0.613688        -0.096687       -0.650916       0.649519        0.544173        1.049731        0.983721        0.824682        1.098958        1.504013        0.445782        
+0.482952        0.592264        0.684978        0.652134        0.638210        0.896312        1.238442        1.016456        0.591464        0.661546        0.454307        0.422780        0.437373        0.638902        0.932319        0.938814        0.528980        0.400344        0.240188        0.413561        0.527152        0.400875        0.404086        0.215865        0.684534        0.563350        0.268626        0.232322        0.045874        0.578827        0.817125        0.221024        0.386095        0.261511        0.343056        0.049708        0.202067        0.645023        0.296113        0.295797        0.059795        0.226952        0.155154        0.339829        0.243719        -0.018479       0.102420        -0.375327       -0.036420       -0.117643       0.356238        -0.052863       -0.416295       -0.232902       -0.338772       -0.463012       -2.303509       -2.232957       -2.357896       -2.423844       -2.513997       -2.612776       -2.613687       -2.675084       
+1.505434        1.363417        -0.194859       -0.348362       -0.469649       -0.771525       -0.841470       -0.031078       1.190572        2.961191        0.828606        -0.698055       -0.860474       -0.936902       -0.639592       0.379187        0.616678        1.879507        1.602122        -0.101415       -0.522488       -0.436513       -0.320211       0.287293        -0.231235       0.783197        0.424965        2.728719        0.511859        -0.772082       0.107849        -0.936791       -0.607715       0.437643        1.151887        0.384451        -0.875804       -1.019544       -0.762657       -1.074007       -0.521902       0.367801        1.779592        -0.537912       -1.288307       -0.813308       -0.966678       -2.059618       -0.469105       -0.332961       2.073018        -0.024539       -0.758977       -0.578462       -0.860001       -1.454497       0.432296        0.397643        0.622481        0.167616        0.090635        -0.102007       -0.395083       -0.459877       
+-1.469105       -2.806421       -2.061450       -1.022853       0.633276        -0.596830       -1.287729       -1.554235       -0.726324       -0.849151       -1.386387       -1.805534       0.599411        0.739235        0.321035        -1.017575       -0.689583       -0.482156       -0.175825       -0.976134       -0.201341       1.197383        1.097442        0.899660        -2.089769       -2.023997       -1.488602       -1.009411       -1.724064       0.816693        0.737729        0.792972        0.786575        0.777591        0.745697        0.789235        0.824291        0.290903        0.745181        0.643504        0.555546        0.646213        0.829069        0.555059        0.680084        0.669478        0.628059        0.728045        0.536159        0.683868        0.605092        0.565139        0.671484        0.675128        0.303383        0.666785        0.447671        0.527836        0.536352        0.297539        0.417557        0.656946        0.603450        0.520721        
+-0.214438       -0.274357       -0.231945       0.010549        0.239864        -0.877546       1.989359        1.814870        -0.410556       -0.348373       -0.151992       -0.293532       -0.284080       -0.240094       1.602504        3.777976        -0.617447       -0.064813       -0.340343       0.543368        -0.638001       -0.393885       0.897389        2.448964        -0.442747       0.504831        -0.039330       2.509840        -1.300790       -0.624629       -0.144400       1.101982        0.305301        2.216398        -0.008106       0.045787        -0.997822       -0.687052       -0.606961       0.677417        -1.402028       -1.278141       -1.021311       -0.713947       -0.728260       -0.506560       -0.501528       0.591606        -0.765185       -0.975961       -0.615421       -0.916485       -0.690450       -0.528311       -0.436659       -0.269385       0.127727        0.290679        -0.166852       -0.287929       -0.513722       -0.444158       0.670848        0.628271        
+-0.080051       -0.028679       -1.023476       -0.727242       -0.650897       0.573408        1.409919        0.511111        -1.045867       -0.752879       -0.766522       -0.555191       -0.550395       0.491611        2.145077        -0.569145       -0.658961       -0.945944       -0.730480       -0.575926       -0.488560       -0.329110       2.488733        0.032109        -0.231372       -0.346787       -0.562019       -0.495708       0.567147        0.526561        0.789888        0.257157        -1.070170       -0.714738       0.007629        -0.263894       0.012954        0.254693        0.358966        0.375810        0.491162        0.461495        0.591320        0.254574        0.169059        -0.230257       -0.500852       -0.235912       -1.260096       -1.413045       -1.252802       -0.670750       -0.353203       -1.811982       -1.897584       -1.685245       1.518117        1.177692        1.111825        1.519545        1.783488        1.838665        1.928735        1.827293        
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+-0.172119       1.905443        1.313323        1.035427        0.188967        1.497373        1.992555        1.485453        0.575146        1.166607        1.003153        1.090684        0.163120        0.500443        0.786544        0.685191        -0.114027       1.232757        1.089061        0.888240        0.497972        0.714235        0.074726        -0.022563       -0.442409       0.362727        2.268691        1.420674        0.305157        -0.091796       -0.586017       -0.051012       -1.043603       0.495092        -0.559702       -0.469001       0.785174        0.411217        -0.498259       -0.610288       -0.606020       -1.003358       -1.472684       -1.018762       -0.135767       -0.520216       -0.268579       -1.173809       -1.314372       -0.014166       -1.572607       -2.396598       -1.142682       -0.626859       -0.848417       -0.278536       -0.873139       -0.652723       -0.440324       -0.066681       -1.439589       -1.690233       -0.227901       -1.490331       
+0.664453        0.390151        0.436705        0.296725        1.496327        1.778134        1.089854        0.963865        -0.904105       -0.525122       0.988603        1.140940        1.435225        1.429142        0.907178        0.944475        -0.977444       -0.929297       -0.274873       0.065058        0.699488        0.714941        0.993015        0.914801        -0.719331       -0.790991       -0.978181       -0.862564       -0.167738       -0.373895       0.354308        0.336833        1.201053        1.977864        1.734763        1.516794        1.047634        0.505436        0.123467        -0.010635       -0.699640       -0.172396       0.351930        -0.152880       -0.526728       -0.561498       0.083642        -0.678380       -2.042667       -0.949510       -0.535792       -0.959470       -0.701550       -0.352637       -0.254944       0.005396        -2.064262       -1.782433       -1.543399       -1.628078       -1.663977       -0.998538       -0.116460       -0.688785       
+1.173658        0.926681        0.934991        0.820088        1.962657        1.868499        1.723010        1.542392        0.469324        0.406841        0.498270        0.400594        0.949271        1.646693        1.429052        1.827806        -0.063639       -0.593735       0.107206        0.366940        0.632084        0.278332        0.672125        1.582985        -0.399588       -0.690383       -0.749674       0.236173        -0.292054       -0.286163       -0.082215       0.225759        -0.701344       0.048187        -0.668599       -0.666357       -0.695897       -0.376128       1.448237        1.851161        -0.728080       -0.750495       0.728578        -0.157512       -1.022799       -0.984878       -0.623561       -0.092622       -1.489307       -1.556340       -1.013360       -0.684326       -0.674437       -0.352121       -1.294540       -0.674013       -1.369541       -1.269575       -1.268095       -0.199062       -0.541047       -0.533007       -1.565978       -1.647123       
diff --git a/SD-VBS/benchmarks/stitch/data/qcif/stitch b/SD-VBS/benchmarks/stitch/data/qcif/stitch
new file mode 100755
index 0000000..d4d728b
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/qcif/stitch
diff --git a/SD-VBS/benchmarks/stitch/data/sim/1.bmp b/SD-VBS/benchmarks/stitch/data/sim/1.bmp
new file mode 100644
index 0000000..d8e683b
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sim/1.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/sim/2.bmp b/SD-VBS/benchmarks/stitch/data/sim/2.bmp
new file mode 100644
index 0000000..a4cfab2
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sim/2.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/sim/Makefile b/SD-VBS/benchmarks/stitch/data/sim/Makefile
new file mode 100644
index 0000000..6e75101
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sim/Makefile
@@ -0,0 +1,6 @@
+INPUT=sim
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=stitch
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/stitch/data/sim/expected.m b/SD-VBS/benchmarks/stitch/data/sim/expected.m
new file mode 100644
index 0000000..34d6ef0
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sim/expected.m
@@ -0,0 +1 @@
+0.000000        -1.000000       
diff --git a/SD-VBS/benchmarks/stitch/data/sim/stitch b/SD-VBS/benchmarks/stitch/data/sim/stitch
new file mode 100755
index 0000000..6c44da2
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sim/stitch
diff --git a/SD-VBS/benchmarks/stitch/data/sim_fast/1.bmp b/SD-VBS/benchmarks/stitch/data/sim_fast/1.bmp
new file mode 100644
index 0000000..251de9b
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sim_fast/1.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/sim_fast/2.bmp b/SD-VBS/benchmarks/stitch/data/sim_fast/2.bmp
new file mode 100644
index 0000000..1c061bb
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sim_fast/2.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/sim_fast/Makefile b/SD-VBS/benchmarks/stitch/data/sim_fast/Makefile
new file mode 100644
index 0000000..455323f
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sim_fast/Makefile
@@ -0,0 +1,6 @@
+INPUT=sim_fast
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=stitch
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/stitch/data/sim_fast/expected.m b/SD-VBS/benchmarks/stitch/data/sim_fast/expected.m
new file mode 100644
index 0000000..68a7208
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sim_fast/expected.m
@@ -0,0 +1 @@
+-1.000000       -2.000000       
diff --git a/SD-VBS/benchmarks/stitch/data/sim_fast/stitch b/SD-VBS/benchmarks/stitch/data/sim_fast/stitch
new file mode 100755
index 0000000..d4d728b
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sim_fast/stitch
diff --git a/SD-VBS/benchmarks/stitch/data/sqcif/1.bmp b/SD-VBS/benchmarks/stitch/data/sqcif/1.bmp
new file mode 100644
index 0000000..2401536
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sqcif/1.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/sqcif/2.bmp b/SD-VBS/benchmarks/stitch/data/sqcif/2.bmp
new file mode 100644
index 0000000..1261eb0
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sqcif/2.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/sqcif/Makefile b/SD-VBS/benchmarks/stitch/data/sqcif/Makefile
new file mode 100644
index 0000000..13e2ede
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sqcif/Makefile
@@ -0,0 +1,6 @@
+INPUT=sqcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=stitch
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/stitch/data/sqcif/expected.m b/SD-VBS/benchmarks/stitch/data/sqcif/expected.m
new file mode 100644
index 0000000..b77b986
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sqcif/expected.m
@@ -0,0 +1,21 @@
+-1.435722       0.292182        -0.284738       -0.616315       -0.169165       -1.070999       -0.774638       -0.686528       -0.440407       1.440547        0.648965        0.426184        0.547302        0.306045        -0.085758       1.570055        -1.821537       0.123628        -0.210573       -0.072751       0.230621        0.865103        0.255400        3.979900        -2.076040       -0.494912       -0.325409       0.163968        0.195773        0.651448        0.044355        2.098517        -1.614893       0.602843        0.954703        1.529341        0.637199        0.491996        -0.179437       0.215159        -1.937521       -0.276789       -0.653518       -0.708397       -0.549787       -0.490966       -0.009364       -0.099051       -1.896568       0.010633        -0.255187       -0.481948       -0.402612       -0.372059       -0.109800       -0.090200       -1.397247       1.171778        0.851867        0.806459        -0.651024       0.213394        0.471355        0.945137        
+-0.686544       -1.335081       -1.385839       -0.263983       1.113257        -0.082560       -0.011088       -1.686275       0.330052        -0.257203       -0.012644       0.646575        1.457970        0.288617        0.251867        -1.228703       0.564542        0.637169        0.002715        0.017976        0.898230        -0.154275       -0.274249       -1.445808       -0.454781       -0.872994       1.682431        -0.744804       0.766818        -0.196157       -0.713463       -2.293905       -0.174181       -0.601761       0.954149        0.107580        0.795035        0.150255        -0.604154       -2.520226       0.194050        1.190761        0.826202        -0.300453       0.310133        0.197000        -0.075917       -2.089836       0.482247        0.201750        0.153854        -0.056972       1.041540        0.749914        0.219370        -1.540749       1.081351        1.184191        0.440433        -0.532676       0.433977        2.956660        1.550377        -1.281769       
+-0.875383       -0.449758       -1.308180       -1.026085       -0.942216       -1.651829       -1.639644       -1.205379       0.116932        0.232220        0.002577        -0.370366       1.205740        0.031639        -0.122174       -0.320666       -0.357986       -0.069217       0.534722        -0.045631       3.499579        1.089687        -0.662285       -0.938505       -0.132661       -0.102387       0.331353        -0.246516       1.708763        2.229948        0.520546        -0.177574       1.166986        0.317789        0.179576        -0.459536       -0.083935       1.553497        1.126896        -0.807321       -0.963032       -0.812058       -0.756068       -0.297650       -0.383019       2.431668        -0.740305       -1.059478       -0.747484       -0.671967       -0.642885       -0.393251       -0.374594       2.554029        -0.128853       -0.162898       0.478902        -0.908421       -0.085614       0.159928        0.610904        0.481771        0.329854        0.227302        
+1.646092        1.321660        1.232799        1.253617        1.213816        1.039082        1.020517        -1.790029       0.939165        0.805362        0.638955        0.929464        0.960736        0.737324        0.847640        -1.853568       0.535266        0.395849        0.192933        0.408039        0.401929        0.546825        0.963448        -1.912600       0.498039        0.551789        0.275924        0.211979        0.167611        0.234458        0.589142        -1.998090       0.279866        0.493579        0.382804        0.222901        -0.033611       0.219395        0.228106        -2.339404       0.114883        -0.218363       0.175123        0.077621        -0.095540       0.040437        0.218676        -2.303741       -0.037397       -0.499628       -0.234704       -0.108584       -0.016259       -0.129802       -0.269936       -2.649468       -0.355373       -0.171418       -0.389701       -0.448592       -0.596868       -0.868166       -0.840378       -2.851635       
+-0.694978       -1.732550       -1.287036       -2.160638       -2.229010       -0.717833       1.137354        -0.473451       0.372360        0.110059        0.082351        -0.708700       -0.379272       0.508718        1.601694        0.026537        -0.373014       0.284594        0.398217        0.496048        -0.358583       -0.338026       0.847706        -0.570053       0.544989        0.676397        -0.974844       -1.538191       1.904050        -1.365516       0.670689        -0.626469       -0.214752       -0.482274       -0.596868       -1.172831       0.923031        -0.217325       0.708698        -0.159841       -0.518959       -1.299560       -0.100848       1.241755        0.750682        -0.766960       0.055520        -0.096874       0.562694        -0.609161       0.287363        -0.090476       -0.154994       -0.438983       1.040748        0.647918        1.033440        1.213888        1.094376        1.232905        0.231038        -1.079771       0.222341        3.620479        
+-0.979990       -1.188307       -1.223878       -1.380451       -0.564622       -0.781203       -1.175221       -2.482405       -0.535055       -0.458679       -1.011044       -1.733741       -1.015839       0.857677        -0.186724       -2.290069       -0.805813       -0.483921       -0.444864       -0.251154       -0.732694       1.010521        1.279538        -1.079549       -0.660390       -0.729273       -0.623650       -0.412492       -0.018573       0.259465        0.973744        -1.076621       0.917487        0.880297        0.887748        1.018590        0.855428        0.910874        0.819616        -1.092655       0.952872        0.791040        0.799493        0.896255        0.798488        0.920267        0.705986        -1.136431       0.803851        0.827820        0.770491        0.834797        0.592088        0.724547        0.871818        -1.199866       1.071322        0.952881        0.992911        1.091129        1.031764        1.023332        0.986747        -1.355710       
+-1.690854       0.915814        1.167157        1.512991        1.126070        1.216655        1.365908        1.901696        -1.804121       0.521720        0.753341        0.615376        0.744814        0.628512        1.075755        1.093304        -1.957019       0.298432        0.464763        0.539655        0.651753        0.485891        0.719092        0.694932        -1.784838       0.556545        0.359041        0.320936        0.323324        0.472984        0.488904        0.534218        -2.106520       0.095108        0.255771        0.203476        0.011965        0.121390        0.368362        0.399494        -2.241670       -0.074936       0.006015        -0.151600       -0.047817       0.109241        0.135561        0.451886        -2.513001       -0.731346       -0.613836       -0.332205       -0.217062       -0.203714       -0.010417       0.335577        -2.636497       -1.205204       -1.182429       -0.797443       -0.349190       -0.692704       -0.321876       -0.377126       
+-0.579592       1.279067        0.496867        0.276727        0.396410        0.158013        -0.229146       1.407040        -1.944350       -0.022243       -0.352481       -0.216294       0.083483        0.710443        0.107968        3.788319        -2.195836       -0.633450       -0.465957       0.017620        0.049048        0.499321        -0.100575       1.929237        -1.740155       0.451292        0.798981        1.366808        0.485241        0.341759        -0.321715       0.068204        -2.058959       -0.417912       -0.790176       -0.844405       -0.687675       -0.629551       -0.153658       -0.242282       -2.018491       -0.133898       -0.396567       -0.620640       -0.542244       -0.512054       -0.252903       -0.233536       -1.525089       1.013483        0.697364        0.652495        -0.787712       0.066460        0.321362        0.789529        -1.429293       0.964019        1.190879        0.932152        0.534237        0.759145        0.532102        -0.086234       
+0.008373        -0.519772       1.267262        1.743601        0.181287        -0.456763       -0.357211       -1.608148       -0.130344       -0.714462       -0.371180       1.125356        0.735463        -1.032322       -1.234990       -1.321803       -0.985479       -0.566506       -0.644530       1.927964        -0.971073       -1.262782       -1.854144       -0.946032       -0.882035       -0.653881       -0.636830       2.039796        -0.412233       -0.443349       -1.331117       -0.651933       -0.372716       -0.148301       0.263870        0.145848        0.007003        -0.086725       0.049978        -0.040562       0.237120        0.037233        -0.507146       -0.808089       -0.493842       -0.040343       -0.156483       -0.412601       -0.744030       0.186997        0.395558        -0.280839       -0.382779       0.043176        0.250210        -0.212781       1.465272        1.500391        1.538390        1.887049        1.848351        1.829106        2.006171        1.955331        
+-2.377947       -0.794181       -1.014921       -1.203227       -1.137345       -1.111974       -0.894190       -0.877914       -1.963304       0.170050        -0.095608       -0.133315       -1.343630       -0.625805       -0.411591       -0.018155       -1.882799       0.128482        0.319129        0.101701        -0.232697       -0.043689       -0.234490       -0.754125       -1.589357       0.198126        -0.380413       -0.701431       -0.249079       -0.980241       -0.091534       0.107547        -1.208382       1.291991        1.263724        1.171813        1.170917        1.128638        1.162160        1.198431        -1.365638       1.048469        0.977085        0.931515        0.967489        1.255358        1.192580        1.213004        -1.614693       0.655497        0.705367        0.628663        0.724521        0.934559        0.876566        1.307551        -1.754237       0.536917        0.527052        0.492765        0.682339        0.563292        0.665629        0.786983        
+0.773800        0.417025        0.966623        0.665707        0.441729        2.162716        2.432357        2.330291        -0.278929       0.269851        0.532268        0.603795        0.724467        0.268304        0.672876        1.035046        -0.341692       -0.149055       -0.133773       0.660126        0.932812        -0.089760       -0.144014       0.449918        0.010867        0.615148        0.505906        0.080649        -0.219105       -0.124434       -0.225306       -0.101618       -0.238222       0.356246        1.174199        0.259069        0.473316        0.826325        2.093549        2.139252        -1.170318       -0.622495       -0.948806       -0.642665       -0.917736       0.140066        0.181572        -0.185256       -1.698431       -1.305030       -1.127900       -0.862769       -1.255059       -0.703501       -0.760644       -0.464138       -1.087950       -1.555081       -1.645205       -1.639557       -1.285587       -1.247933       -1.140759       -0.883148       
+0.639310        0.673261        0.592058        0.683143        0.339358        0.526979        0.735581        -2.198853       1.018169        0.850403        0.907104        1.046225        0.962137        0.950193        0.898373        -2.419598       0.935827        0.741872        0.926912        0.848006        0.943531        0.786414        0.820200        -2.157478       0.444322        0.366226        0.118049        0.083063        0.212009        0.525793        0.351146        -2.280283       0.272528        0.241118        -0.354085       -0.022192       0.211383        0.412287        0.197713        -2.395383       0.318846        0.293527        -0.456679       -0.406912       -0.265169       -0.054401       0.097997        -2.453421       0.534160        0.238003        0.156886        0.175890        0.139558        -0.019949       -0.036896       -2.602502       -0.111157       -0.233299       -0.385204       -0.120013       -0.091467       -0.295408       -0.194706       -2.660503       
+0.862765        1.015568        1.267335        2.171126        2.203721        2.120276        2.130394        2.699486        0.219644        0.023462        0.777892        0.807494        0.545871        1.426635        1.178142        0.992851        0.062665        -0.217117       0.176256        0.135501        0.346971        0.782642        0.547421        0.311710        -0.491343       -0.238890       -0.212035       -0.135598       0.048131        -0.135029       -0.113602       -0.151946       -1.016558       -0.831975       -0.415371       -0.362856       -0.204346       0.270752        0.134506        0.153873        -1.117401       -0.852468       -0.808070       -0.274480       -0.450062       0.035115        0.132344        -0.011308       -1.402890       -1.380374       -1.054312       -0.470674       -0.431434       -0.139011       -0.087246       -0.361746       -1.625770       -2.205225       -1.579695       -1.672893       -0.686116       -0.707293       -1.118460       -0.616950       
+0.816577        0.934480        0.324267        1.119824        0.593417        0.620913        0.935660        0.617642        0.211815        0.726147        0.540269        0.635087        0.713054        0.526575        0.735748        -0.053736       0.398320        0.482803        1.001079        1.505119        1.119853        1.250063        1.569548        1.376445        0.309777        0.440361        0.652094        1.316025        0.870617        1.295552        1.114347        1.333716        -1.466851       -1.254792       -1.194648       0.187308        0.007965        -0.561963       -0.642305       -0.346186       -1.590802       -1.522781       -1.478997       -0.207208       -0.279340       -1.646194       -0.884019       -0.347626       -2.150393       -1.766118       -1.405339       -0.100842       -0.158985       -1.881797       -1.767509       -1.442003       -0.516064       -0.503643       0.195023        0.393617        -0.286494       -0.472775       -0.429133       -0.512568       
+0.580588        0.536559        0.941667        0.825350        0.708433        0.731858        1.143191        0.630253        0.643511        0.757461        0.167708        0.936590        0.427833        0.454408        0.758602        0.451246        0.059027        0.556113        0.376467        0.468106        0.543459        0.363233        0.565393        -0.197621       0.239278        0.320928        0.821827        1.308966        0.936619        1.062462        1.371235        1.184607        0.153704        0.279910        0.484543        1.126212        0.695739        1.106426        0.931297        1.143311        -1.563354       -1.358406       -1.300279       0.035341        -0.137989       -0.688807       -0.766456       -0.480266       -1.683149       -1.617409       -1.575094       -0.345947       -0.415661       -1.736684       -1.000065       -0.481656       -2.223978       -1.852588       -1.503906       -0.243148       -0.299341       -1.964387       -1.853932       -1.539339       
+0.198167        0.257415        1.618795        1.442121        0.880680        0.801534        1.093244        1.803102        -0.065832       -0.022700       1.230153        1.159094        -0.187408       0.563419        1.091826        1.546324        -0.305546       0.049861        1.334934        1.277658        -0.419502       -0.306916       0.013744        0.490554        0.938132        1.626394        1.822032        1.152047        0.968540        1.011532        0.929339        0.568495        -0.213526       -0.437618       0.362157        0.085840        -0.257807       0.342123        0.406702        -0.054666       -0.976323       -1.261393       -0.471936       -0.759846       -1.178887       -0.734672       -0.747290       -0.448064       -1.775766       -1.822140       -0.548813       -0.437815       -1.007502       -1.139555       -1.231181       -1.093135       -1.475704       -1.452281       -0.999363       -0.558023       -0.786784       -1.117000       -1.646724       -1.124241       
+1.695119        1.705902        2.312388        2.484780        1.894401        1.732697        1.770581        1.698154        0.955900        0.691079        0.493613        1.198362        0.954876        0.652059        1.180709        1.237614        0.269592        0.018915        -0.232284       0.463372        0.209671        -0.159581       0.231854        0.220735        -0.708377       -0.685542       -0.726406       0.395630        0.493440        -0.008560       -0.124923       -0.205662       -0.275933       -0.421132       -0.400492       -0.001388       0.387514        0.185933        -0.105048       -0.571832       -0.527053       -0.423436       -0.576527       -0.301612       -0.908031       -0.191991       -0.369418       -0.684526       -0.712621       -0.657455       -0.949991       -0.578720       -1.419858       -0.937767       -0.708263       -0.540255       -1.318244       -1.756427       -1.221964       -1.157353       -0.822604       -1.219821       -1.326987       -1.596809       
+-2.445530       -1.680134       -2.917287       -1.413561       -1.076708       -2.169176       -2.333822       -1.645850       0.724071        0.722554        0.651016        0.707737        0.769110        1.332239        1.269736        1.238654        0.317477        0.378346        0.865432        0.759209        0.793767        1.156751        1.314155        1.394598        -0.194961       -0.032766       0.322627        0.224500        0.953744        0.997760        0.901544        1.252458        -0.424904       -0.104139       -0.305570       -0.132412       0.072923        0.355942        1.028791        1.086431        -0.225690       -0.405454       -0.539256       0.488844        0.649925        0.588952        0.968381        1.057474        -0.485169       -0.442440       -0.370351       -0.642859       -0.401171       -0.184815       -0.243762       -0.099080       -0.883055       -0.408788       -0.245888       -0.856762       -0.889173       -0.534364       -0.328330       -0.281921       
+0.087346        0.160305        0.082567        0.177889        0.376197        0.714419        1.031961        2.180123        0.620965        0.893013        1.869608        1.904829        1.814663        1.825595        2.440531        2.615325        -0.451059       0.364144        0.396130        0.113432        1.065146        0.796635        0.596418        1.310985        -0.711018       -0.285957       -0.329994       -0.101490       0.369276        0.115107        -0.139592       0.565756        -0.734545       -0.705527       -0.622933       -0.424403       -0.622317       -0.599164       -0.640597       0.497070        -1.375405       -0.925242       -0.868497       -0.697218       -0.183849       -0.331071       -0.310143       0.094521        -1.397549       -1.349575       -0.773001       -0.962728       -0.438467       -0.333407       -0.488630       -0.209885       -1.967980       -1.615653       -0.985000       -0.942600       -0.626620       -0.570685       -0.867298       -0.490855       
+0.776198        -0.046630       -0.090286       0.387630        0.665151        0.727662        0.767899        1.936670        -0.150710       -0.074531       -0.155699       -0.056171       0.150888        0.504036        0.835590        2.034419        0.406457        0.690511        1.710202        1.746977        1.652832        1.664247        2.306319        2.488827        -0.712873       0.138303        0.171701        -0.123473       0.870240        0.589880        0.380827        1.126927        -0.984305       -0.540486       -0.586467       -0.347879       0.143662        -0.121724       -0.387662       0.348812        -1.008870       -0.978571       -0.892332       -0.685041       -0.891689       -0.867515       -0.910776       0.277095        -1.678010       -1.207981       -1.148733       -0.969896       -0.433872       -0.587590       -0.565740       -0.143218       -1.701131       -1.651040       -1.049023       -1.247122       -0.699726       -0.590029       -0.752103       -0.461057       
+1.250168        1.221881        0.383703        0.439306        0.597670        0.833153        1.003422        -1.847184       1.490732        1.159846        1.069217        1.090449        1.049856        0.871646        0.852712        -2.013747       0.769742        0.633277        0.463559        0.759848        0.791741        0.563885        0.676396        -2.078550       0.357807        0.215616        0.008665        0.228050        0.221818        0.369597        0.794508        -2.138756       0.319840        0.374659        0.093306        0.028089        -0.017162       0.051015        0.412755        -2.225947       0.097326        0.315291        0.202313        0.039229        -0.222387       0.035652        0.044537        -2.574051       -0.070939       -0.410814       -0.009500       -0.108942       -0.285548       -0.146865       0.034919        -2.537679       -0.226248       -0.697675       -0.427480       -0.298852       -0.204689       -0.320491       -0.463413       -2.890283       
diff --git a/SD-VBS/benchmarks/stitch/data/sqcif/stitch b/SD-VBS/benchmarks/stitch/data/sqcif/stitch
new file mode 100755
index 0000000..d4d728b
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/sqcif/stitch
diff --git a/SD-VBS/benchmarks/stitch/data/test/1.bmp b/SD-VBS/benchmarks/stitch/data/test/1.bmp
new file mode 100644
index 0000000..900ebaa
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/test/1.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/test/2.bmp b/SD-VBS/benchmarks/stitch/data/test/2.bmp
new file mode 100644
index 0000000..b6fd176
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/test/2.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/test/Makefile b/SD-VBS/benchmarks/stitch/data/test/Makefile
new file mode 100644
index 0000000..ddbfe5c
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/test/Makefile
@@ -0,0 +1,6 @@
+INPUT=test
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=stitch
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/stitch/data/test/expected.m b/SD-VBS/benchmarks/stitch/data/test/expected.m
new file mode 100644
index 0000000..4870e84
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/test/expected.m
@@ -0,0 +1 @@
+-2.000000       -2.000000       
diff --git a/SD-VBS/benchmarks/stitch/data/test/stitch b/SD-VBS/benchmarks/stitch/data/test/stitch
new file mode 100755
index 0000000..d4d728b
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/test/stitch
diff --git a/SD-VBS/benchmarks/stitch/data/vga/1.bmp b/SD-VBS/benchmarks/stitch/data/vga/1.bmp
new file mode 100644
index 0000000..0e7cc75
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/vga/1.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/vga/2.bmp b/SD-VBS/benchmarks/stitch/data/vga/2.bmp
new file mode 100644
index 0000000..e85bdea
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/vga/2.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/vga/3.bmp b/SD-VBS/benchmarks/stitch/data/vga/3.bmp
new file mode 100644
index 0000000..ef5ccff
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/vga/3.bmp
diff --git a/SD-VBS/benchmarks/stitch/data/vga/Makefile b/SD-VBS/benchmarks/stitch/data/vga/Makefile
new file mode 100644
index 0000000..46359e0
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/vga/Makefile
@@ -0,0 +1,8 @@
+INPUT=vga
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=stitch
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
+
diff --git a/SD-VBS/benchmarks/stitch/data/vga/expected.m b/SD-VBS/benchmarks/stitch/data/vga/expected.m
new file mode 100644
index 0000000..dc9d68f
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/vga/expected.m
@@ -0,0 +1,410 @@
+-2.815381       -1.474772       -1.533418       -1.619486       -1.672673       -1.758406       -1.712836       -1.641870       -1.485937       0.772955        0.538966        0.502206        0.506943        0.458815        0.567163        0.484278        -1.670080       0.474010        0.390266        0.467047        0.472563        0.537337        0.701247        0.677645        -1.695447       0.381256        0.314992        0.431289        0.436185        0.671067        0.923957        0.621169        -1.852322       0.282497        0.534603        0.343076        0.617765        0.896995        0.797993        0.491512        -1.822673       0.506268        0.328572        0.569893        0.811269        0.702421        0.507373        0.421338        -1.845603       0.306612        0.473853        0.642549        0.603620        0.504003        0.472381        0.423817        -1.781270       0.507525        0.632079        0.495029        0.523791        0.575856        0.499999        0.578129        
+-1.409002       0.923920        0.916747        0.857305        0.801960        0.700222        0.574731        0.566434        -1.375046       0.885262        0.801132        0.805258        0.774854        0.644441        0.551712        0.552930        -1.426283       0.809233        0.725724        0.712624        0.633061        0.472026        0.472519        0.482974        -1.475056       0.686715        0.609963        0.568747        0.467157        0.431705        0.457540        0.502031        -1.558586       0.587859        0.533076        0.488706        0.477176        0.486546        0.396666        0.343847        -1.566729       0.546721        0.431083        0.384426        0.418992        0.324629        0.258725        0.234941        -1.633529       0.411706        0.336563        0.343221        0.241302        0.187035        0.102136        0.134463        -2.865279       -1.706942       -1.727600       -1.771293       -1.823743       -1.884011       -1.949568       -1.886079       
+-1.906510       -1.041985       -1.397626       -1.443327       -0.588719       1.015354        0.926494        0.707382        -2.034870       -1.473615       -1.382297       0.568703        1.376200        1.082129        0.734135        0.254445        -2.266427       -0.604015       1.356403        1.516109        1.263590        0.827772        0.258456        -0.326853       -0.743464       1.526851        1.580275        1.297586        0.872004        0.418196        -0.096306       -0.621346       -0.460192       1.574847        1.385967        0.842581        0.408458        -0.150615       -0.503860       -0.787898       -0.479110       1.396542        1.023277        0.550776        0.085045        -0.483402       -0.708558       -0.860238       -0.649044       0.973186        0.668525        0.327979        -0.143930       -0.632982       -0.796079       -0.963343       -0.932055       0.469951        0.258579        -0.131823       -0.488610       -0.625665       -0.792101       -1.030935       
+0.992444        1.052733        1.159454        0.863935        0.517352        0.438041        0.311604        0.000725        0.942778        0.518042        0.510794        0.866402        0.420717        0.187649        0.263652        0.114203        0.716812        0.344353        0.319965        0.362056        -0.005736       -0.141480       0.056630        -0.252095       1.107276        0.457245        0.167155        0.347211        -0.046324       -0.290922       -0.283001       -0.110994       1.017023        0.624283        0.897549        0.636087        -0.020757       -0.252213       -0.090688       -0.013188       0.602848        0.902898        0.793633        0.341758        0.184072        0.100797        -0.286291       -0.180744       0.734274        0.803115        0.413777        0.026017        0.406254        0.052905        -0.120952       -0.212279       -2.070596       -2.194900       -2.537598       -2.403320       -2.317866       -2.507715       -2.539667       -2.697191       
+-1.467576       -1.603689       -1.582569       -1.550473       -1.633320       -1.679546       -1.698803       -1.965691       -0.173101       -0.157706       0.046900        -0.200401       -0.355274       -0.364067       -0.147824       -0.013389       -0.189975       -0.129655       -0.181864       -0.269016       -0.394677       1.469737        1.217846        0.223808        -0.124972       -0.120037       -0.301076       -0.038488       1.886462        2.359133        1.135009        -0.068888       -0.165658       -0.350060       0.984722        1.498388        2.239054        1.504809        -0.057874       -0.724473       -0.267074       1.202184        1.463206        1.337042        1.223889        0.142552        -0.713713       -0.904420       0.764523        1.142223        1.082387        0.008892        -0.037421       -0.212439       -0.775894       -0.741455       0.513967        0.591545        -0.190483       -0.865219       -0.438195       -0.612805       -0.704852       0.135835        
+1.691223        1.025013        -0.974405       -0.953098       0.115567        1.156545        -0.264991       -0.671371       1.621143        1.237127        -0.985672       -1.176888       -0.002912       0.469985        -0.992390       -0.713906       1.352997        1.268336        -0.792194       -1.116583       -0.214779       -0.699918       -1.200159       -0.693934       1.148916        1.553413        -0.248870       -0.162051       0.012074        -1.566588       -1.226662       -0.590252       1.105757        1.834517        0.354714        1.112392        -0.140049       -1.574270       -0.968912       -0.661911       1.285157        1.855637        0.562375        1.270620        -0.539959       -1.140124       -0.822570       -1.255596       1.292259        1.352968        0.445418        0.275850        -0.717921       -1.136428       -0.431971       -0.859421       1.031138        0.736607        0.764436        0.150250        -0.622698       -0.610588       -0.414465       -0.937932       
+-0.572186       -0.534018       -0.392621       -0.238690       -0.205142       -0.679137       -0.527531       -0.491943       -0.414159       -0.423923       0.103562        1.627662        1.145971        0.407497        0.933617        0.667125        -0.133262       -0.225215       0.444607        1.138095        1.123684        0.727191        1.803226        1.917033        -0.007881       0.275630        -0.147965       0.071110        0.494515        0.843822        2.508710        2.314652        0.094100        0.732528        -0.606993       -0.617965       -0.491191       1.242884        2.082862        0.885373        -0.266401       -0.435036       -1.379414       -1.542405       -0.478482       0.951329        0.740519        -0.257789       -1.147834       -1.594492       -1.645956       -1.499459       0.256086        -0.155350       -0.288538       -0.829133       -1.497946       -0.978325       -1.343227       -1.170163       -0.598141       -1.085475       -0.506585       -0.123422       
+-0.982495       -0.921452       0.022964        -0.602464       -1.307531       0.261956        0.191123        1.552343        -0.232662       -0.631134       0.129710        -0.415876       -0.445076       0.109797        0.361391        1.730833        -0.286724       -0.653931       0.302875        0.705876        -0.548147       -1.137801       -1.029407       0.300869        -0.681228       -1.016336       1.220959        2.281170        -0.793992       -1.764200       -1.375780       0.370629        -0.839062       -0.668723       2.262216        2.866011        -0.235380       -0.992823       -0.526125       -0.233791       -0.399850       0.122809        2.867960        2.122262        -0.119511       0.410060        -0.137442       -0.337061       -0.223178       0.432676        1.731816        -0.229141       -0.147877       0.146047        -0.096807       -0.504294       -0.229208       0.049724        -0.500185       -0.978254       0.058010        -0.132698       0.514523        -0.768960       
+0.011350        1.826225        2.148647        1.992806        1.853035        0.517334        -0.540352       -0.775919       1.285612        1.752159        1.678247        0.352233        0.295026        0.078838        -0.617159       -0.574620       0.976118        1.071945        0.105959        -0.727497       -0.200023       -0.415707       -0.529406       0.509037        0.116524        -0.212410       -0.706777       -0.545877       -0.104954       -0.077607       0.723868        1.878722        -0.562900       -0.573791       -0.866614       0.010222        0.041840        0.694721        2.005940        0.396604        -0.907743       -0.486908       -0.784132       0.412431        0.624127        1.012659        0.034133        -1.426587       -0.800775       -0.346279       -0.675568       0.528105        -0.016905       -0.653309       -1.382711       -1.665355       -0.601373       -0.064904       -0.131086       -0.262827       -1.538251       -1.812867       -1.780083       -1.565193       
+-0.302017       -0.410357       -0.546065       -0.662287       -0.827890       -0.937219       -1.013823       -1.022516       -0.300978       -0.493323       -0.545862       -0.568911       -0.714216       -0.883106       -0.961132       -0.983521       -0.453870       -0.655464       -0.608550       -0.434752       -0.245549       -0.204313       -0.786922       -0.600576       -0.494216       -0.461226       -0.473228       0.175128        2.048469        1.456400        0.548709        1.195386        -0.423154       -0.115962       -0.228986       0.594322        1.446720        1.429006        0.941659        2.264263        -0.347350       0.038149        0.386625        -0.134034       0.135240        0.655666        1.085016        3.131404        -0.194902       0.163498        0.948218        -0.698246       -0.711733       -0.555909       1.575521        2.607976        -0.197956       -0.279609       -0.486886       -1.647665       -1.848004       -0.540288       1.217158        0.958041        
+-0.302184       -0.673024       -0.159330       0.230486        0.189947        -0.259756       -0.250514       0.289718        -0.300373       -0.805092       -0.605691       1.776660        1.883063        -0.673669       0.364452        0.296640        -0.438391       -1.001000       -0.528897       3.621659        2.614842        0.818841        0.253369        -0.018317       -0.733902       -0.673470       -0.022109       3.621344        1.499329        0.166981        0.021277        0.283615        -0.889188       -0.063614       0.362873        1.210686        -0.171829       0.064819        0.126096        0.448979        -0.949628       -0.623853       -0.088808       -0.275805       -0.951652       -0.090119       -0.172263       0.195107        -1.465319       -0.374531       -0.045740       -0.577089       -0.450251       -0.120209       0.138460        -0.481737       -1.243093       -0.488616       -0.482686       -0.408304       -0.003558       0.328142        -1.082521       -1.861252       
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+2.020659        1.261603        1.144025        1.305974        1.301643        0.448544        -0.473719       1.151596        1.295715        1.020114        1.017522        0.813527        0.155405        -0.650260       0.478807        0.424105        0.576052        1.051299        0.904039        0.145607        -0.105290       0.145116        0.049716        0.269049        0.939631        1.645882        0.357725        -0.957374       -0.517361       -0.083949       0.197777        0.129700        1.340171        1.220180        -0.945344       -1.799780       -0.822291       0.262404        0.714150        -0.455657       0.629287        0.079326        -1.175957       -0.939762       0.033102        0.812370        -0.907266       -1.785290       0.289980        -0.007986       -0.233047       -0.548661       -0.458912       -1.207144       -2.033019       -1.943073       -0.457789       0.483412        -0.210270       -1.101696       -1.860719       -1.697211       -1.698670       -1.037719       
+-0.328918       -0.812569       -1.215666       -1.176216       -1.334547       -0.334748       0.324182        -0.048529       -1.177949       -0.871482       -0.628511       -1.422512       -0.717311       0.576645        0.412041        -0.530490       -0.939127       -0.658085       -1.124966       -1.099805       -0.380528       0.509590        0.470788        0.264104        -1.330723       -1.385840       -0.789215       -0.474738       0.058708        1.046372        1.193213        0.543384        -1.059436       -0.550616       0.402338        0.708108        1.156502        1.417184        0.485759        0.012509        -0.051657       0.849491        1.483715        1.831854        1.486493        0.517848        -0.786051       -0.855709       1.945214        1.974654        1.743649        0.901875        0.486541        -0.771340       -1.250292       -0.738297       2.432688        1.439474        0.483479        -0.550098       -0.442113       -0.674534       -0.221963       -0.423825       
+-0.451878       -0.419981       -0.744059       -0.014480       -0.572593       -0.313039       0.186178        2.063606        -0.688624       -0.651479       -0.215315       0.888400        0.729472        0.090758        0.493757        0.687767        -0.929409       -0.896441       0.685175        2.388050        0.349184        -0.508448       -0.738109       -0.329904       -1.523405       0.326261        2.206500        1.539855        -0.523886       -0.800978       -0.553395       -1.080849       0.003905        1.629250        0.896306        -0.417084       -0.996416       -0.725533       -1.071605       -2.143374       0.493149        0.231010        -0.439776       -0.652705       -0.979723       -0.199985       -0.950462       -2.053451       -0.500201       -0.306532       0.044060        -0.466737       0.059361        0.831668        -0.748643       0.444643        -0.603519       0.784859        1.793384        1.338759        1.964116        0.897176        -0.453348       1.618752        
+-0.152913       -0.423078       -0.388265       -0.741973       0.054312        -0.554831       -0.271545       0.273317        -1.245763       -0.681471       -0.640929       -0.164885       1.039745        0.866285        0.169172        0.609018        -1.798974       -0.944270       -0.908288       0.817938        2.676510        0.451226        -0.484820       -0.735479       -0.184979       -1.592577       0.426208        2.478361        1.750764        -0.501670       -0.804097       -0.533877       -1.699170       0.074379        1.848331        1.048373        -0.385102       -1.017404       -0.721753       -1.099468       -0.631449       0.608355        0.322248        -0.409870       -0.642267       -0.999185       -0.148154       -0.967248       0.531403        -0.475819       -0.264442       0.118205        -0.439295       0.134905        0.977826        -0.746976       0.390045        -0.588584       0.926736        2.027473        1.531280        2.213815        1.049323        -0.424683       
+-2.729012       -0.179291       -0.165334       -0.128811       0.442577        0.425417        0.472528        0.393017        -2.701348       0.058900        -0.013083       0.383171        0.758067        0.647174        0.796261        0.632284        -2.458263       0.257361        0.141334        0.564098        0.484944        0.850441        0.987364        0.127121        -2.467548       0.077833        0.513468        0.577847        0.658791        1.070799        0.434982        0.081639        -2.496066       0.370793        0.688518        0.702432        0.875065        0.675968        0.248722        0.111863        -2.419455       0.688277        0.631490        0.523243        0.313853        0.125829        0.296585        0.164726        -2.301997       0.772065        0.332480        0.060172        0.049139        0.189043        0.249848        -0.038943       -2.466228       0.224018        0.100920        0.004946        0.248179        0.210638        0.208769        -0.339621       
+-2.340587       -2.376398       -2.532559       -1.975458       -1.169519       -0.066946       0.308929        0.308932        -2.541646       -2.220950       -1.485977       -1.110508       -0.176514       0.372912        0.380982        0.181454        -2.761434       -0.940505       0.000236        0.284996        0.076741        0.463609        0.592213        0.426632        -1.431142       0.138985        0.500282        0.222549        0.224696        0.796728        0.684656        0.603369        -0.127316       0.152527        0.469544        0.455557        0.755716        0.677678        0.628109        0.652299        0.037302        0.865977        0.775762        1.028662        0.662103        0.548898        0.793913        0.598192        0.524160        0.918567        0.912268        0.428900        0.654522        0.704114        0.618231        0.339586        0.228921        0.136834        -0.260310       0.655438        0.804785        0.358934        0.463214        0.098156        
+1.782902        1.732598        1.587628        0.543386        0.746381        -0.142354       -0.258956       0.175721        1.457503        1.038703        0.737104        -0.546876       -0.385912       -0.001495       0.280024        0.799328        1.649165        1.457903        0.504168        0.105779        0.386007        1.135714        1.563375        0.712671        -0.573181       0.790063        0.629400        -0.384320       -0.280444       0.612957        1.060929        0.722555        0.151917        0.123395        -0.455796       -0.546759       0.046176        0.647671        1.691078        0.760184        -0.218433       -0.793670       0.015805        -0.933456       -1.559251       0.622318        -0.767259       -2.181406       -0.751096       -0.934081       0.099087        -1.430393       -0.793840       -1.176069       -2.040540       -1.599991       -1.647680       -1.024036       -0.333980       -0.401392       -0.862539       -0.569287       -1.467082       -1.308022       
+0.377974        -0.093930       -0.224614       -0.519054       -0.183130       -0.241966       -0.404910       -0.285138       0.127516        -0.003726       -0.057849       -0.577758       -0.390194       -0.351416       -0.352443       0.003908        0.111349        0.375100        -0.134247       -0.488346       -0.353526       -0.571368       -0.203061       -0.376042       0.471521        0.312319        -0.199314       -0.461610       -0.931585       -0.744026       -0.239708       -0.739056       0.683269        0.328928        -0.450379       -0.825310       -0.973426       -0.905603       -0.382278       1.752156        0.479722        -0.197224       -0.672286       -1.087674       -1.267318       1.571270        2.122271        1.023121        -0.579689       -0.692840       -0.921984       -0.382102       2.783246        2.059806        1.182392        -0.301148       -0.967407       -0.813361       2.109658        2.642806        1.647300        1.055980        0.094689        -2.768254       
+0.769286        0.865735        1.861989        0.602012        0.057998        0.577978        0.212154        0.511417        1.542161        3.487763        1.488927        0.258504        0.599069        0.007948        0.540563        0.468026        2.231804        1.806407        -0.482840       -0.528986       -0.347481       -0.567835       -0.452119       -0.852649       0.277622        -0.994540       -1.037345       -0.156339       -0.608265       -0.914499       -0.507891       -2.323336       -0.590525       -0.798867       0.197491        0.187612        -1.643493       -1.028962       -0.320436       -0.409425       -0.716763       -0.138948       1.032881        -0.418785       -0.764948       -0.512592       0.344215        -0.131690       0.061446        0.494185        -0.774896       -0.870981       -0.982252       -0.814974       0.420430        0.243948        -0.275734       -1.650312       -0.817296       -0.785087       -0.232271       0.552214        1.999162        0.752415        
+0.876172        0.867254        0.793347        0.724534        0.598039        0.442010        0.431694        0.447787        0.828107        0.723505        0.728635        0.690832        0.528684        0.413389        0.414904        0.369421        0.733577        0.629746        0.613459        0.514534        0.314312        0.314926        0.327925        0.334413        0.581244        0.485815        0.434570        0.308258        0.264180        0.296301        0.351619        0.214908        0.458333        0.390219        0.335051        0.320716        0.332365        0.220614        0.154941        -0.084152       0.407183        0.263406        0.205395        0.248373        0.131047        0.049106        0.019533        0.160689        0.239314        0.145885        0.154164        0.027443        -0.040029       -0.145588       -0.105394       -0.120595       -2.394896       -2.420581       -2.474906       -2.540120       -2.615053       -2.696564       -2.617625       -2.606376       
+-2.703736       -2.788291       -2.482000       -1.535631       -0.691499       -0.719826       -0.709443       -0.763665       -0.740712       -0.480263       -0.025005       -0.271031       -0.260817       0.065676        0.280460        0.974430        -0.218284       -0.218811       -0.413788       -0.279644       0.384596        1.081961        1.317520        0.807220        -0.569224       -0.213714       -0.175273       0.919556        1.439369        1.432507        0.727762        0.234147        -0.118373       0.414024        1.238877        1.584055        0.969952        0.301974        -0.145553       0.087830        0.995261        1.897181        1.665267        0.819180        0.012598        -0.511402       -0.360244       -0.199311       1.615403        1.438613        0.641364        -0.239955       -0.520727       -0.563887       -0.522485       -0.925247       1.059162        0.399429        -0.625934       -0.727877       -0.541616       -0.624164       -0.896608       -1.021335       
+-3.219649       -0.987678       -0.071967       -0.333570       0.040500        0.484011        1.078131        0.789260        -1.831000       -0.465839       0.288877        0.914629        0.799028        1.183952        0.706792        0.420196        -0.433818       0.487383        0.767129        1.339410        1.177533        0.558620        0.288972        0.106320        0.647461        1.015821        1.283407        1.029016        0.730369        0.186294        0.188626        -0.453962       0.891325        1.405386        1.574004        0.778881        0.222362        0.150116        -0.357993       -0.992612       1.248396        1.266319        0.766422        0.171138        -0.175080       -0.487428       -1.184111       -1.034658       0.784104        0.263724        -0.311091       -0.409254       -0.522271       -1.381348       -1.514419       -1.331130       -0.169503       -0.571831       -0.641423       -0.608826       -1.342740       -1.654657       -1.657592       -1.888466       
+-5.475975       0.993673        1.615915        1.321396        0.926097        0.780378        0.464121        0.911390        1.738761        1.357361        0.604544        0.462090        0.758700        0.510100        0.159158        0.936561        0.852682        0.024550        -0.133690       0.311983        0.204066        0.110684        0.168812        0.126133        -0.225957       -0.331832       -0.351469       -0.312817       0.013883        0.361409        -0.627627       -0.784933       -0.066756       -0.452900       -0.689472       -0.333447       -0.306552       -0.219350       0.125632        0.447110        0.077795        -0.872991       -1.143160       -1.146665       -0.756816       0.375225        0.569453        0.711670        -0.383725       -1.561100       -1.452354       -0.685673       0.616805        0.949690        0.368821        0.141095        -0.466889       -1.547040       -0.059425       0.287185        0.108933        0.071038        -0.298955       0.122669        
+-0.291668       0.407677        0.407681        0.434394        0.588269        0.834763        0.493107        0.929937        0.526721        0.541736        0.170499        0.482274        0.633888        0.187418        -0.186297       0.193404        0.695470        0.934747        0.626672        0.787373        0.272861        0.611445        -0.191331       -1.514064       1.315262        1.106743        0.955503        0.743870        0.327846        0.385915        -0.591887       -1.895622       1.093761        1.001533        1.046541        0.055953        -0.240475       -0.819537       -2.199653       -2.205257       0.854155        1.310025        0.945871        -0.188857       -0.826246       -1.742686       -2.196623       -1.458360       1.142946        0.983155        0.464715        -0.258953       -0.339503       -1.158158       -0.880840       -1.263322       0.500715        0.694734        0.015518        -0.243281       -0.142914       -0.877240       -1.153643       -2.838680       
+-3.734622       -3.845305       -2.060605       -0.020017       0.746682        0.746168        0.573060        0.436094        -4.358677       -1.545880       0.533223        0.733189        0.638541        0.511507        0.464678        0.363045        -0.641241       0.772667        0.650099        0.408171        0.362392        0.457712        0.377821        0.265041        0.708744        0.487914        0.221783        0.170931        0.314153        0.279473        0.249463        0.268143        0.264937        0.141280        0.107255        0.100945        0.113366        0.218355        0.330037        0.012198        0.089926        0.192441        0.068349        -0.007677       0.106736        0.115379        0.143403        0.254267        0.413073        0.238894        -0.066653       -0.153475       -0.154602       -0.029319       0.334477        0.396895        0.428047        0.090579        -0.287785       -0.252839       -0.006456       0.412112        0.519089        0.332419        
+0.320388        0.130958        -0.192565       1.431908        1.884953        2.161205        0.194405        -1.317657       -0.196577       0.276083        0.398771        1.164087        1.456055        0.650745        -0.757355       -1.099620       0.721669        -0.124998       -0.265037       0.766593        -0.054179       -0.628482       -1.031667       -1.417166       -0.234424       -1.064668       0.073034        -0.531546       -1.302909       -0.926136       -1.302665       0.412988        -1.850793       -0.851317       -0.835320       -1.348878       0.005423        -1.136488       -0.459821       0.677597        -0.708431       0.253192        -0.212147       1.218979        1.183659        -0.686002       0.295130        0.055819        1.629598        1.326734        1.474978        1.061247        -0.200618       -0.039468       1.156890        -1.388115       2.342039        -0.037961       -0.537550       -1.260501       -1.199173       0.842471        0.517310        -0.884674       
+-0.864289       -0.620224       -0.295892       -0.485570       -0.748921       -1.298619       -2.355277       -3.200331       -0.014603       0.008973        0.052712        -0.048972       -0.698643       -1.238990       -1.926417       -2.185461       0.320849        0.212925        0.258685        0.064210        -0.571148       -1.056688       -1.102361       -0.980843       0.456880        0.333466        0.338182        0.029707        -0.366567       -0.381157       -0.266672       -0.494981       0.785880        0.534355        0.301363        0.350626        0.205428        0.085501        -0.184032       -0.594646       0.441215        -0.127335       0.650530        0.797878        0.523421        -0.038428       -0.340827       -0.735458       0.955595        1.272600        1.157926        1.068034        0.244087        -0.106094       0.087372        -0.260374       1.777501        2.137738        1.660668        1.152251        0.882504        1.331365        1.510184        1.599214        
diff --git a/SD-VBS/benchmarks/stitch/data/vga/stitch b/SD-VBS/benchmarks/stitch/data/vga/stitch
new file mode 100755
index 0000000..d4d728b
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/data/vga/stitch
diff --git a/SD-VBS/benchmarks/stitch/src/c/dist2.c b/SD-VBS/benchmarks/stitch/src/c/dist2.c
new file mode 100644
index 0000000..d76fcb2
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/c/dist2.c
@@ -0,0 +1,76 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "stitch.h"
+
+F2D* dist2(I2D* x, F2D* c)
+{
+    int ndata, dimx, ncentres, dimc, i, j, k;
+    F2D *n2, *t1, *t2;
+    float temp;
+    F2D *s1, *s2, *ctrans;
+    F2D *mult1, *mult2, *mult3;
+
+    ndata = x->height;
+    dimx = x->width;
+
+    ncentres = c->height;
+    dimc = c->width;
+
+    if(dimx != dimc)
+        return NULL;
+
+    s1 = fSetArray(ncentres, 1, 1);
+    s2 = fSetArray(ndata, 1, 1);
+    t1 = fMallocHandle(1, x->height);
+
+    for(j=0; j<t1->width; j++)
+    {
+        temp = 0;
+        for(i=0; i<t1->height; i++)
+        {
+            temp += subsref(x,j,i) * subsref(x,j,i);
+        }
+
+        asubsref(t1,j) = temp;
+    }
+
+    mult1 = fMtimes(s1, t1);
+    t2 = fMallocHandle(1, c->height);
+
+    for(j=0; j<t2->width; j++)
+    {
+        temp = 0;
+        for(i=0; i<t2->height; i++)
+        {
+            temp += subsref(c,j,i) * subsref(c,j,i);
+        }
+
+        asubsref(t2,j) = temp;
+    }
+
+    mult2 = fMtimes(s2, t2);
+    ctrans = fTranspose(c);
+    mult3 = ifMtimes(x, ctrans);
+
+    for(i=0; i<(mult3->height * mult3->width); i++)
+        asubsref(mult3,i) = asubsref(mult3,i) * 2;
+
+    free(t1);
+    free(t2);
+    free(s1);
+    free(s2);
+    free(ctrans);
+
+    n2 = fMallocHandle(ndata, ncentres);
+    for(i=0; i<(ndata*ncentres); i++)
+        asubsref(n2,i) = asubsref(mult1,i) + asubsref(mult2,i) - asubsref(mult3,i);
+
+    free(mult1);
+    free(mult2);
+    free(mult3);
+
+    return n2;
+
+}
diff --git a/SD-VBS/benchmarks/stitch/src/c/extractFeatures.c b/SD-VBS/benchmarks/stitch/src/c/extractFeatures.c
new file mode 100644
index 0000000..ea574e4
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/c/extractFeatures.c
@@ -0,0 +1,181 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "stitch.h"
+#include <math.h>
+
+#define min(a,b) (a<b)?a:b
+
+F2D* extractFeatures(I2D* I, F2D* x, F2D* y)
+{
+    int n, i, j, k;
+    F2D* I1;
+    F2D *Iconv;
+    F2D *Isub;
+    int nr, nc;
+    F2D *w, *wt, *vecF;
+    I2D *Xsub, *Ysub;
+    float temp, mean, std;
+    int m;
+    F2D *g1, *g;
+
+    g1 = fSetArray(5,5,0);
+
+    asubsref(g1,0) = 1;
+    asubsref(g1,1) = 4;
+    asubsref(g1,2) = 6;
+    asubsref(g1,3) = 4;
+    asubsref(g1,4) = 1;
+
+    asubsref(g1,5) = 4;
+    asubsref(g1,6) = 16;
+    asubsref(g1,7) = 24;
+    asubsref(g1,8) = 16;
+    asubsref(g1,9) = 4;
+
+    asubsref(g1,10) = 6;
+    asubsref(g1,11) = 24;
+    asubsref(g1,12) = 36;
+    asubsref(g1,13) = 24;
+    asubsref(g1,14) = 6;
+
+    asubsref(g1,15) = 4;
+    asubsref(g1,16) = 16;
+    asubsref(g1,17) = 24;
+    asubsref(g1,18) = 16;
+    asubsref(g1,19) = 4;
+
+    asubsref(g1,20) = 1;
+    asubsref(g1,21) = 4;
+    asubsref(g1,22) = 6;
+    asubsref(g1,23) = 4;
+    asubsref(g1,24) = 1;
+
+    g = fDivide(g1, 256);
+    n = x->height;
+
+    vecF = fMallocHandle(n, 64);
+    I1 = fiDeepCopy(I);
+
+    Iconv = ffConv2(I1, g);
+    fFreeHandle(I1);
+    I1 = ffConv2(Iconv, g);
+    fFreeHandle(Iconv);
+    Iconv = fDeepCopy(I1);
+
+    {
+        int i = (Iconv->height/5);
+        int j = (Iconv->width/5);
+        Isub = fMallocHandle(i, j);
+    }
+
+    for(i=0, m=0; m<Isub->height; i+=5, m++)
+    {
+        for(j=0, k=0; k<Isub->width; j+=5, k++)
+        {
+            subsref(Isub,m,k) = subsref(Iconv,i,j);
+        }
+    }
+
+    fFreeHandle(Iconv);
+    fFreeHandle(g1);
+    fFreeHandle(g);
+    fFreeHandle(I1);
+
+    nr = Isub->height;
+    nc = Isub->width;
+
+    Xsub = iMallocHandle(x->height, x->width);
+    Ysub = iMallocHandle(y->height, y->width);
+        
+//    printf("Sizes = %d\t%d\t%d\t%d\n", Isub->height, Isub->width, x->height, x->width);
+   
+    for(i=0; i<(x->height*x->width); i++)
+    {
+        asubsref(Xsub,i) = min( ( asubsref(x,i) /5), nc-4 );
+        asubsref(Ysub,i) = min( ( asubsref(y,i) /5), nr-4 );
+    }
+
+    {
+        int maxX, maxY;
+        maxX = Xsub->height>Xsub->width?Xsub->height:Xsub->width;
+        maxY = Ysub->height>Ysub->width?Ysub->height:Ysub->width;
+        if(maxX < 6 || maxY < 10)
+        {
+            fFreeHandle(vecF);
+            vecF = fSetArray(n,2,0);
+            for(i=0; i<(x->height); i++)
+            {
+                subsref(vecF, i, 0) = asubsref(Xsub,i)*1.0;
+                subsref(vecF, i, 1) = asubsref(Ysub,i)*1.0;
+            }
+
+            fFreeHandle(Isub); 
+            iFreeHandle(Xsub); 
+            iFreeHandle(Ysub); 
+            return vecF;
+        }
+    }
+
+    {
+        int newSize = 4;
+        if(I->height > 32 && I->width >32)
+            newSize = 64;
+        fFreeHandle(vecF);
+        vecF = fMallocHandle(n, newSize);
+    }
+
+//    printf("Size of Isub = %d\t%d\n", Isub->height, Isub->width);      
+    for(i=0; i<n; i++)
+    {
+    
+        if( asubsref(Ysub,i) < 3)
+            asubsref(Ysub,i) = 3;
+        if( asubsref(Xsub,i) < 3)
+            asubsref(Xsub,i) = 3;
+        
+        if( asubsref(Ysub,i) >= (Isub->height-4))
+            asubsref(Ysub,i) = Isub->height-5;
+        if( asubsref(Xsub,i) >= (Isub->width-4))
+            asubsref(Xsub,i) = Isub->width-5;
+
+        m = 0;
+        temp = 0;
+//        printf("SUBS %d\t%d\n", asubsref(Ysub,i), asubsref(Xsub,i));
+  
+        for(k= asubsref(Xsub,i)-3; k<=( asubsref(Xsub,i)+4); k++)
+        {
+            for(j= asubsref(Ysub,i)-3; j<=( asubsref(Ysub,i)+4); j++)
+            {
+//                printf("%d\t%d\n", j, k);
+                subsref(vecF,i,m) = subsref(Isub,j,k);
+                temp += subsref(vecF,i,m);
+                m++;
+            }
+        }
+        mean = temp/64.0;
+
+        std = 0;
+        for(j=0; j<64; j++)
+        {
+            subsref(vecF,i,j) = subsref(vecF,i,j) - mean;
+            std += subsref(vecF,i,j) * subsref(vecF,i,j);
+        }
+         
+        std = std/64;
+        std = sqrt(std);
+        for(j=0; j<64; j++)
+        {
+            subsref(vecF,i,j) = subsref(vecF,i,j)/std; 
+        }
+    }
+
+    iFreeHandle(Xsub);
+    fFreeHandle(Isub);
+    iFreeHandle(Ysub);
+    return vecF;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/stitch/src/c/getANMS.c b/SD-VBS/benchmarks/stitch/src/c/getANMS.c
new file mode 100644
index 0000000..fa03a85
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/c/getANMS.c
@@ -0,0 +1,145 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "stitch.h"
+
+F2D* getANMS (F2D *points, int r)
+{
+  unsigned int MAX_LIMIT = 10000000;
+  F2D *suppressR;
+  float C_ROBUST = 0.9;
+  F2D *srtdPnts;
+  int n, k;
+  I2D *srtdVIdx, *supId;
+  float r_sq, t, t1;
+  F2D *tempF, *srtdV, *interestPnts;
+  int i, j, validCount=0, cnt, end;
+  F2D *v;
+    int iter, rows, cols;
+    F2D* temp;
+    int supIdPtr = 0;
+
+  v = fMallocHandle(points->height, 1);
+  for(i=0; i<v->height; i++)
+      asubsref(v,i) = subsref(points,i,2);
+
+  r_sq = r * r * 1.0;
+  n = v->height;
+
+    srtdVIdx = fSortIndices (v, 1);
+    srtdPnts = fMallocHandle (srtdVIdx->height, points->width);
+
+    for (i = 0; i < srtdVIdx->height; i++)
+        for(j=0; j<points->width; j++)
+            subsref(srtdPnts,i,j) = subsref(points, asubsref(srtdVIdx,i), j);
+
+    temp = fSetArray (1, 3, 0);
+    suppressR = fSetArray(n, 1, MAX_LIMIT);
+
+    validCount = 0;
+    iter = 0;
+    for (i = 0; i < suppressR->height; i++)
+    {
+            if ( asubsref(suppressR,i) > r_sq)
+        {
+            validCount++;
+        }
+    }
+   
+    k = 0;
+    supId = iMallocHandle(validCount, 1);
+    for (i = 0; i < (suppressR->height*suppressR->width); i++)
+    {
+        if ( asubsref(suppressR,i) > r_sq)
+        {
+            asubsref(supId,k++) = i;
+        }
+    }
+         
+    while (validCount > 0)
+    {
+        F2D *tempp, *temps;
+        asubsref(temp,0) = subsref(srtdPnts, asubsref(supId,0), 0);
+        asubsref(temp,1) = subsref(srtdPnts, asubsref(supId,0), 1);
+        asubsref(temp,2) = subsref(srtdPnts, asubsref(supId,0), 2);
+       
+        if(iter == 0)
+            interestPnts = fDeepCopy(temp);
+        else
+        {
+            tempp = fDeepCopy(interestPnts);
+            fFreeHandle(interestPnts); 
+            interestPnts = ffVertcat(tempp, temp);
+            fFreeHandle(tempp);
+        }
+        iter++;
+
+        tempp = fDeepCopy(srtdPnts);
+        temps = fDeepCopy(suppressR);
+
+        fFreeHandle(srtdPnts);
+        fFreeHandle(suppressR);
+
+        srtdPnts = fMallocHandle(supId->height-1, 3);
+        suppressR = fMallocHandle(supId->height-1, 1);
+        
+        k=0;
+        for(i=1; i<supId->height; i++)
+        {
+            subsref(srtdPnts,k,0) = subsref(tempp, asubsref(supId,i) ,0);
+            subsref(srtdPnts,k,1) = subsref(tempp, asubsref(supId,i) ,1);
+            subsref(srtdPnts,k,2) = subsref(tempp, asubsref(supId,i) ,2);
+            subsref(suppressR,k,0) = subsref(temps, asubsref(supId,i) ,0);
+            k++;
+        }
+         
+        fFreeHandle(tempp);
+        fFreeHandle(temps);
+        rows = interestPnts->height-1;
+        cols = interestPnts->width;
+        for (i = 0; i < srtdPnts->height; i++)
+            {
+            t = 0;
+                t1 = 0;
+
+                if ((C_ROBUST * subsref(interestPnts,rows,2)) >= subsref(srtdPnts, i,2))
+                {
+                        t = subsref(srtdPnts, i,0) - subsref(interestPnts,rows,0);
+                        t1 = subsref(srtdPnts, i,1) - subsref(interestPnts,rows,1);
+                        t = t * t + t1 * t1;
+                t1 = 0;
+            }
+
+                if ((C_ROBUST * subsref(interestPnts,rows,2)) < subsref(srtdPnts, i,2))
+                t1 = 1 * MAX_LIMIT;
+
+                if ( asubsref(suppressR, i) > (t + t1))
+            {
+                    asubsref(suppressR, i) = t + t1;
+            }  
+        }
+        
+        validCount=0;
+        for (i = 0; i < suppressR->height; i++)
+                if ( asubsref(suppressR,i) > r_sq)
+                validCount++;
+   
+        k = 0;
+        iFreeHandle(supId);
+        supId = iMallocHandle(validCount, 1);
+        
+        for (i = 0; i < suppressR->height*suppressR->width; i++)
+            if ( asubsref(suppressR,i) > r_sq)
+                asubsref(supId,k++) = i;
+    }
+  
+    iFreeHandle(supId);
+    iFreeHandle(srtdVIdx);
+    fFreeHandle(srtdPnts);
+    fFreeHandle(temp);
+    fFreeHandle(suppressR);
+    fFreeHandle(v);
+
+    return interestPnts;
+}
diff --git a/SD-VBS/benchmarks/stitch/src/c/harris.c b/SD-VBS/benchmarks/stitch/src/c/harris.c
new file mode 100644
index 0000000..a24c2b4
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/c/harris.c
@@ -0,0 +1,141 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "stitch.h"
+
+F2D* harris(I2D* im)
+{
+    F2D *img1;
+    F2D *g1, *g2, *g;
+    F2D *Ix, *Iy;
+    F2D *Ix2, *Iy2, *IxIy;
+    F2D *v, *R, *Rmax, *Rnm;
+    float eps;
+    F2D *sobel, *sob, *temp, *temp1;    
+    I2D *win, *x, *y;
+    int i;
+    
+    g1 = fSetArray(5,5,0);
+    g2 = fSetArray(3,3,0);
+
+    asubsref(g1,0) = 1;
+    asubsref(g1,1) = 4;
+    asubsref(g1,2) = 6;
+    asubsref(g1,3) = 4;
+    asubsref(g1,4) = 1;
+
+    asubsref(g1,5) = 4;
+    asubsref(g1,6) = 16;
+    asubsref(g1,7) = 24;
+    asubsref(g1,8) = 16;
+    asubsref(g1,9) = 4;
+
+    asubsref(g1,10) = 6;
+    asubsref(g1,11) = 24;
+    asubsref(g1,12) = 36;
+    asubsref(g1,13) = 24;
+    asubsref(g1,14) = 6;
+
+    asubsref(g1,15) = 4;
+    asubsref(g1,16) = 16;
+    asubsref(g1,17) = 24;
+    asubsref(g1,18) = 16;
+    asubsref(g1,19) = 4;
+
+    asubsref(g1,20) = 1;
+    asubsref(g1,21) = 4;
+    asubsref(g1,22) = 6;
+    asubsref(g1,23) = 4;
+    asubsref(g1,24) = 1;
+
+    asubsref(g2,0) = 1;
+    asubsref(g2,1) = 2;
+    asubsref(g2,2) = 1;
+    
+    asubsref(g2,3) = 2;
+    asubsref(g2,4) = 4;
+    asubsref(g2,5) = 2;
+
+    asubsref(g2,6) = 1;
+    asubsref(g2,7) = 2;
+    asubsref(g2,8) = 1;
+    
+    g = fDivide(g1, 256);
+    sob = fMallocHandle(1,3);
+    asubsref(sob,0) = -0.5;
+    asubsref(sob,1) = 0;
+    asubsref(sob,2) = 0.5;
+
+    {
+        F2D* imf;
+        imf = fiDeepCopy(im);
+        img1 = ffConv2(imf, g);
+        fFreeHandle(imf);
+    }
+
+    Ix = ffConv2(img1, sob); 
+    fFreeHandle(sob);
+    sob = fMallocHandle(3,1);
+    asubsref(sob,0) = -0.5;
+    asubsref(sob,1) = 0;
+    asubsref(sob,2) = 0.5;
+    Iy = ffConv2(img1, sob);
+
+    fFreeHandle(g);
+    g = fDivide(g2, 16);
+    eps = 2.2204e-16;
+    sobel = fTimes(Ix, Ix);
+    Ix2 = ffConv2(sobel, g);
+    fFreeHandle(sobel);
+
+    sobel = fTimes(Iy, Iy);
+    Iy2 = ffConv2(sobel, g);
+    fFreeHandle(sobel);
+
+    sobel = fTimes(Ix, Iy);
+    IxIy = ffConv2(sobel, g);
+    fFreeHandle(sobel);
+ 
+    temp = fTimes(Ix2, Iy2);
+    temp1 = fTimes(IxIy, IxIy);
+    sobel = fMinus(temp, temp1);
+
+    fFreeHandle(temp);
+    temp = fPlus(Ix2, Iy2);
+
+    for(i=0; i<(temp->height*temp->width); i++)
+        asubsref(temp,i) += eps;
+
+    R = ffDivide(sobel, temp);
+    
+    win = iSetArray(1,2,3);
+    Rmax = maxWindow(R, win);
+    Rnm = supress(R, Rmax);
+
+    v = fFind3(Rnm);
+    
+    iFreeHandle(win);
+    fFreeHandle(Rmax);
+    fFreeHandle(Rnm);
+    fFreeHandle(R);
+    
+    fFreeHandle(img1);
+    fFreeHandle(g1);
+    fFreeHandle(g2);
+    fFreeHandle(g);
+    fFreeHandle(Ix);
+    fFreeHandle(Iy);
+    fFreeHandle(Ix2);
+    fFreeHandle(Iy2);
+    fFreeHandle(IxIy);
+    fFreeHandle(sobel);
+    fFreeHandle(sob);
+    fFreeHandle(temp);
+    fFreeHandle(temp1);
+//    iFreeHandle(x);
+//    iFreeHandle(y);
+    
+    return v;
+}
+
diff --git a/SD-VBS/benchmarks/stitch/src/c/matchFeatures.c b/SD-VBS/benchmarks/stitch/src/c/matchFeatures.c
new file mode 100644
index 0000000..5450eb9
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/c/matchFeatures.c
@@ -0,0 +1,55 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "stitch.h"
+
+I2D* matchFeatures(F2D* vecF1, F2D* vecF2)
+{
+    int m, n, n1, n2, n1c, n2c, i, j;
+    I2D *id, *retMatch, *t;
+    F2D *val, *temp;
+    int rows, cols;    
+
+    n1 = vecF1->height;
+    n1c = vecF1->width;
+    n2 = vecF2->height;
+    n2c = vecF2->width;
+
+    retMatch = iMallocHandle(1, 2);
+
+    for(i=0; i<n1; i++)
+    {
+        id = iMallocHandle(1, n2);
+        t = iMallocHandle(1, n1c);
+
+        for(j=0; j<n1c; j++)
+            asubsref(t,j) = subsref(vecF1,i,j);
+
+        temp = dist2(t, vecF2);
+        val = fSort(temp,1);
+        id = fSortIndices(temp,1);
+
+        free(temp);
+        free(t);
+        
+        if( asubsref(val,1) != 0 & (( asubsref(val,0) / asubsref(val,1) ) < 0.65))
+        {
+            t = retMatch;
+            rows = t->height + 1;
+            cols = t->width;
+            retMatch = iMallocHandle(rows, cols);
+            n = 0;
+    
+            for(m=0; m<(t->height*t->width); m++)
+            {
+                asubsref(retMatch,n++) = asubsref(t,m);
+            }
+
+            asubsref(retMatch,n++) = i;
+            asubsref(retMatch,n) = asubsref(id,0);
+        }
+    }
+
+    return retMatch;
+}
diff --git a/SD-VBS/benchmarks/stitch/src/c/maxWindow.c b/SD-VBS/benchmarks/stitch/src/c/maxWindow.c
new file mode 100644
index 0000000..07f8dc9
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/c/maxWindow.c
@@ -0,0 +1,51 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "stitch.h"
+
+F2D* maxWindow(F2D* im, I2D* window)
+{
+    int exR, exC, rows, cols, tr, tc, i, j, k;
+    F2D *out, *temp;
+    float t;
+    int m;
+    
+    exR = asubsref(window,0)/2;
+    exC = asubsref(window,1)/2;
+
+    rows = im->height;
+    cols = im->width;
+
+    tr = rows+exR-1;
+    tc = cols+exC-1;
+    temp = fDeepCopy(im);
+    out = fMallocHandle(rows, cols);
+
+    for(i=0; i<rows; i++)
+    {
+        for(j=0; j<cols; j++)
+        {
+            t = 0;
+            for(k=-exR; k<=exR; k++)
+            {
+                for(m=-exC; m<=exC; m++)
+                {
+                    if( (i+k) < 0 || (i+k) >= rows || (j+m) < 0 || (j+m) >= cols)
+                        continue;
+                    if( subsref(temp,(i+k),(j+m)) > t)
+                        t = subsref(temp,(i+k),(j+m));
+                }
+            }
+            subsref(out,i,j) = t;
+        }
+    }
+
+    fFreeHandle(temp);
+    return out;
+}
+
+
+
+
+
diff --git a/SD-VBS/benchmarks/stitch/src/c/script_stitch.c b/SD-VBS/benchmarks/stitch/src/c/script_stitch.c
new file mode 100644
index 0000000..00c9a93
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/c/script_stitch.c
@@ -0,0 +1,65 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "stitch.h"
+#include <malloc.h>
+#include "extra.h"
+#define STITCH_MEM 1<<30
+int main(int argc, char* argv[])
+{
+    SET_UP
+    mallopt(M_TOP_PAD, STITCH_MEM);
+    mallopt(M_MMAP_MAX, 0);
+    int rows, cols;
+    F2D *x, *y, *v, *interestPnts, *Fcur, *int1, *int2;
+    I2D *Icur;
+    int i, j;
+    char im1[100], im2[100];
+    
+
+    printf("Input image: ");
+    scanf("%s", im1);
+    Icur = readImage(im1);
+    rows = Icur->height;
+    cols = Icur->width;
+    
+    printf("start\n");
+    for_each_job{
+        v = harris(Icur);
+        interestPnts = getANMS(v, 24);
+        int1 = fMallocHandle(interestPnts->height, 1);
+        int2 = fSetArray(interestPnts->height, 1, 0);
+        for(i=0; i<int1->height; i++)
+        {
+            asubsref(int1,i) = subsref(interestPnts,i,0);
+            asubsref(int2,i) = subsref(interestPnts,i,1);
+        }
+
+        Fcur = extractFeatures(Icur, int1, int2);  
+    }
+    printf("end..\n");
+    
+
+#ifdef CHECK   
+    /** Self checking - use expected.txt from data directory  **/
+    {
+        int ret=0;
+        float tol = 0.02;
+#ifdef GENERATE_OUTPUT
+        fWriteMatrix(Fcur, argv[1]);
+#endif
+        ret = fSelfCheck(Fcur, "expected_C.txt", tol);
+        if (ret == -1)
+            printf("Error in Stitch\n");
+    }
+#endif
+    iFreeHandle(Icur);
+    fFreeHandle(v);
+    fFreeHandle(interestPnts);
+    fFreeHandle(int1);
+    fFreeHandle(int2);
+    fFreeHandle(Fcur);
+    WRITE_TO_FILE
+    return 0;
+}
diff --git a/SD-VBS/benchmarks/stitch/src/c/stitch.h b/SD-VBS/benchmarks/stitch/src/c/stitch.h
new file mode 100644
index 0000000..e2202fc
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/c/stitch.h
@@ -0,0 +1,22 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#ifndef _SCRIPT_STITCH_
+#define _SCRIPT_STITCH_
+
+#include "sdvbs_common.h"
+
+F2D* dist2(I2D* x, F2D* c);
+F2D* extractFeatures(I2D* I, F2D* x, F2D* y);
+F2D* getANMS (F2D *points, int r);
+F2D* harris(I2D* im);
+I2D* matchFeatures(F2D* vecF1, F2D* vecF2);
+F2D* maxWindow(F2D* im, I2D* window);
+F2D* supress(F2D* im, F2D* im1);
+int script_stitch();
+
+#endif
+
+
+
diff --git a/SD-VBS/benchmarks/stitch/src/c/supress.c b/SD-VBS/benchmarks/stitch/src/c/supress.c
new file mode 100644
index 0000000..6fbdb6c
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/c/supress.c
@@ -0,0 +1,29 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "stitch.h"
+
+F2D* supress(F2D* im, F2D* im1)
+{
+    int rows, cols, i, j;
+    F2D *out;
+
+    rows = im->height;
+    cols = im->width;
+
+    out = fSetArray(rows, cols, 0);
+
+    for(i=0; i<rows; i++)
+    {
+        for(j=0; j<cols; j++)
+        {
+            if( subsref(im,i,j) == subsref(im1,i,j))
+                subsref(out,i,j) = subsref(im,i,j);
+        }
+    }
+    return out;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/calculateH.m b/SD-VBS/benchmarks/stitch/src/matlab/calculateH.m
new file mode 100755
index 0000000..caefd74
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/calculateH.m
@@ -0,0 +1,24 @@
+function retH=calculateH(pnt1, pnt2)
+
+[n temp]=size(pnt1);
+
+X=zeros(0,8);
+b=zeros(0,1);
+
+for i=1:n
+    X=[X; pnt1(i,1) pnt1(i,2) 1 0 0 0 -pnt2(i,1)*pnt1(i,1) -pnt2(i,1)*pnt1(i,2);0, 0, 0, pnt1(i,1), pnt1(i,2), 1, -pnt2(i,2)*pnt1(i,1), -pnt2(i,2)*pnt1(i,2)];
+    b=[b; pnt2(i,1); pnt2(i,2)];
+end
+
+if n==4
+    %if abs(det(X)~=0
+        H=X^(-1)*b;
+    %else
+    %    H=[0 0 0; 0 0 0; 0 0 1];
+    %end
+else
+    Xt = X';
+    H=(Xt*X)^(-1)*Xt*b;
+end
+
+retH=[H(1) H(2) H(3);H(4) H(5) H(6);H(7) H(8) 1];
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/dist2.m b/SD-VBS/benchmarks/stitch/src/matlab/dist2.m
new file mode 100755
index 0000000..89116ac
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/dist2.m
@@ -0,0 +1,31 @@
+function n2 = dist2(x, c)
+%DIST2  Calculates squared distance between two sets of points.
+%
+%       Description
+%       D = DIST2(X, C) takes two matrices of vectors and calculates the
+%       squared Euclidean distance between them.  Both matrices must be of
+%       the same column dimension.  If X has M rows and N columns, and C has
+%       L rows and N columns, then the result has M rows and L columns.  The
+%       I, Jth entry is the  squared distance from the Ith row of X to the
+%       Jth row of C.
+%
+%       See also
+%       GMMACTIV, KMEANS, RBFFWD
+%
+
+%       Copyright (c) Christopher M Bishop, Ian T Nabney (1996, 1997)
+
+[ndata, dimx] = size(x);
+[ncentres, dimc] = size(c);
+if dimx ~= dimc
+        error('Data dimension does not match dimension of centres')
+end
+
+ct = c';
+opt = (x.^2)';
+op2t = (x.^2)';
+tempT = (ones(ncentres, 1) * sum(opt, 1))';
+n2 = tempT + ones(ndata, 1) * sum(op2t,1) - 2.*(x*ct);
+
+
+
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/extractFeatures.m b/SD-VBS/benchmarks/stitch/src/matlab/extractFeatures.m
new file mode 100755
index 0000000..38d2f7c
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/extractFeatures.m
@@ -0,0 +1,56 @@
+function vecF=extractFeatures(I, x, y, dataDir)
+
+Igray = I;
+w = (1/16)*[1 4 6 4 1];
+[n temp]=size(x);
+
+%SUB sample rate s=5
+wt = w';
+Iconv=conv2(w, wt, Igray, 'same');
+Iconv=conv2(w, wt, Iconv, 'same');
+Isub=Iconv(1:5:end,1:5:end);
+[nr nc]=size(Isub);
+    
+Xsub=min(floor(x/5)+1, nc-4);
+Ysub=min(floor(y/5)+1, nr-4);
+
+if(length(Xsub) < 6 || length(Ysub) < 10)
+    vecF = [Xsub Ysub];
+    return;
+end
+
+newSize = 4;
+[rows, cols] = size(I);
+if(rows > 32 & cols >32)
+    newSize = 64;
+end
+
+for i=1:n
+
+    minValy = 3;
+    minValx = 3;
+    if( Ysub(i) < 4)
+        Ysub(i) = 4;
+    end
+    if( Xsub(i) < 4)
+        Xsub(i) = 4;
+    end
+
+    if( Ysub(i) > size(Isub,1)-4)
+        Ysub(i) = size(Isub,1)-4;
+    end
+    if( Xsub(i) > size(Isub,2)-4)
+        Xsub(i) = size(Isub,2)-4;
+    end
+    
+    vecF(i,:)=reshape(Isub(Ysub(i)-minValy:Ysub(i)+4,Xsub(i)-minValx:Xsub(i)+4),1,newSize);
+
+    %normalization
+    vecF(i,:)=vecF(i,:)-mean(vecF(i,:));
+    vecF(i,:)=vecF(i,:)/std(vecF(i,:));
+    %imagesc(reshape(vecF(i,:),8,8)); colormap gray
+    %drawnow
+    %pause    
+end
+
+
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/getANMS.m b/SD-VBS/benchmarks/stitch/src/matlab/getANMS.m
new file mode 100755
index 0000000..caece31
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/getANMS.m
@@ -0,0 +1,25 @@
+function [interestPnts]=getANMS(x, y, v, r, dataDir)
+%interestPnts=[x y v]
+MAX_LIMIT=100000000;
+C_ROBUST=0.9;
+r_sq=r^2;
+points=[x y v];
+[n temp]=size(v);
+[srtdV srtdVIdx]=sort(v,'descend');
+srtdPnts=points(srtdVIdx,:);
+
+interestPnts=zeros(0,3);
+
+suppressR=ones(n,1)*MAX_LIMIT;
+supId=find(suppressR>r_sq);
+
+iter = 0;
+while length(supId)>0
+    interestPnts=[interestPnts; srtdPnts(supId(1),:)];
+    srtdPnts=srtdPnts(supId(2:end),:);
+    suppressR=suppressR(supId(2:end),:);
+    
+    suppressR=min(suppressR,(C_ROBUST*interestPnts(end,3)>srtdPnts(:,3)).*((srtdPnts(:,1)-interestPnts(end,1)).^2 + (srtdPnts(:,2)-interestPnts(end,2)).^2)+(C_ROBUST*interestPnts(end,3)<=srtdPnts(:,3))*MAX_LIMIT);
+    supId=find(suppressR>r_sq);
+    iter = iter + 1;
+end
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/getDirParamLocal.m b/SD-VBS/benchmarks/stitch/src/matlab/getDirParamLocal.m
new file mode 100755
index 0000000..7b36886
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/getDirParamLocal.m
@@ -0,0 +1,4 @@
+function DIR_PARAM=getDirParam
+DIR_PARAM.main_dir=pwd;
+DIR_PARAM.data_dir=fullfile(DIR_PARAM.main_dir,'data');
+DIR_PARAM.report_dir=fullfile(DIR_PARAM.main_dir,'report');
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/harris.m b/SD-VBS/benchmarks/stitch/src/matlab/harris.m
new file mode 100755
index 0000000..423330e
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/harris.m
@@ -0,0 +1,37 @@
+
+% Sample code for detecting Harris corners, following 
+% Brown et al, CVPR 2005
+%        by Alyosha Efros, so probably buggy...
+
+function [x,y,v] = harris(im, dataDir);
+
+g1 = [1,4,6,4,1; 4,16,24,16,4;6,24,36,24,6;4,16,24,16,4;1,4,6,4,1]/256;
+g2 = [1,2,1;2,4,2;1,2,1]/16;
+
+img1 = conv2(im,g1,'same');  % blur image with sigma_d
+     
+Ix = conv2(img1,[-0.5 0 0.5],'same');  % take x derivative 
+Iy = conv2(img1,[-0.5;0;0.5],'same');  % take y derivative
+
+% Compute elements of the Harris matrix H
+%%% we can use blur instead of the summing window
+Ix2 = conv2(Ix.*Ix,g2,'same');
+Iy2 = conv2(Iy.*Iy,g2,'same');
+IxIy = conv2(Ix.*Iy,g2,'same'); 
+
+R = (Ix2.*Iy2 - IxIy.*IxIy) ... % det(H) 
+    ./ (Ix2 + Iy2 + eps);       % trace(H) + epsilon
+
+% don't want corners close to image border
+[rows, cols] = size(im);
+
+% non-maxima supression within 3x3 windows
+nonmax = inline('max(x)');
+Rmax = colfilt(R,[3 3],'sliding',nonmax); % find neighbrhood max
+Rnm = R.*(R == Rmax);  % supress non-max
+
+% extract all interest points
+[y,x,v] = find(Rnm);
+
+
+
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/main.m b/SD-VBS/benchmarks/stitch/src/matlab/main.m
new file mode 100755
index 0000000..9be8504
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/main.m
@@ -0,0 +1,47 @@
+Icur_list=readData('capitol');
+Icur=Icur_list{1};
+%Icur=Icur(1:150,:,:);
+[x y v]=harris(Icur);
+interestPntsCur=getANMS(x, y, v, 24);
+Fcur=extractFeatures(Icur, interestPntsCur(:,1), interestPntsCur(:,2));
+
+for id=2:length(Icur_list)
+    Iprev=Icur;
+    Fprev=Fcur;
+    interestPntsPrev=interestPntsCur;
+    Icur=Icur_list{id};
+    %Icur=Icur(1:150,:,:);
+    [x y v]=harris(Icur);
+    %showInterestPoints(I, x, y)
+    interestPntsCur=getANMS(x, y, v, 16);
+    %showInterestPoints(I, interestPnts(:,1), interestPnts(:,2))
+    Fcur=extractFeatures(Icur, interestPntsCur(:,1), interestPntsCur(:,2));
+    matchedPntsIdx=matchFeatures(Fprev, Fcur);
+    matchedPntsPrev=interestPntsPrev(matchedPntsIdx(:,1),:);
+    matchedPntsCur=interestPntsCur(matchedPntsIdx(:,2),:);
+    
+    %subplot(1,2,1);showInterestPoints(Iprev, matchedPntsPrev(:,1), matchedPntsPrev(:,2));axis image
+    %subplot(1,2,2);showInterestPoints(Icur, matchedPntsCur(:,1), matchedPntsCur(:,2));axis image
+    %drawnow
+    %pause;
+    %printImage(['featureMatching' int2str(id-1) '_' int2str(id)]);
+    [retH retPntsIdx]=ransac(matchedPntsPrev, matchedPntsCur, 10000, 100);  
+    subplot(2,2,1);showInterestPoints(Iprev, matchedPntsPrev(retPntsIdx,1), matchedPntsPrev(retPntsIdx,2));axis image
+    subplot(2,2,2);showInterestPoints(Icur, matchedPntsCur(retPntsIdx,1), matchedPntsCur(retPntsIdx,2));axis image
+    T=maketform('projective', retH');
+    Tfn_Mat=T;
+    [nr nc nd]=size(Iprev);
+    Itrans=imtransform(Iprev,T,'XData', [1 nc], 'YData', [1 nr],'FillValues',[0;0;0]);
+    subplot(2,2,3);imshow(Itrans)    
+    subplot(2,2,4);imagesc(rgb2gray(abs(Icur-Itrans)))
+    drawnow
+    pause;
+    printImage(['ransac' int2str(id-1) '_' int2str(id)]);
+end
+
+    %[Itrans2 XData YData]=imtransform(Iprev,T,'FillValues',[0;0;0]);
+    %for the fast iteration
+    %[Itrans2 XData2 YData2]=imtransform(Iprev,T,'XData', [-2*nc 2*nc], 'YData', [-2*nr 2*nr],'FillValues',[0;0;0]);
+
+    %h=imshow(Itrans);
+
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/matchFeatures.m b/SD-VBS/benchmarks/stitch/src/matlab/matchFeatures.m
new file mode 100755
index 0000000..7af77e0
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/matchFeatures.m
@@ -0,0 +1,13 @@
+function retMatch=matchFeatures(vecF1, vecF2)
+[n1 temp]=size(vecF1);
+[n2 temp]=size(vecF2);
+
+retMatch=zeros(0,2);
+
+for i=1:n1
+    [val id]=sort(dist2(vecF1(i,:),vecF2));
+    if val(2)~=0 & val(1)/val(2)<0.65
+        retMatch=[retMatch; i id(1)];
+    end
+end
+        
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/pics/matched_base_cur.jpg b/SD-VBS/benchmarks/stitch/src/matlab/pics/matched_base_cur.jpg
new file mode 100644
index 0000000..a4bd68b
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/pics/matched_base_cur.jpg
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/pics/ransaced_feat.jpg b/SD-VBS/benchmarks/stitch/src/matlab/pics/ransaced_feat.jpg
new file mode 100644
index 0000000..821ca11
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/pics/ransaced_feat.jpg
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/printImage.m b/SD-VBS/benchmarks/stitch/src/matlab/printImage.m
new file mode 100755
index 0000000..82e74f0
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/printImage.m
@@ -0,0 +1,2 @@
+function printImage(fname, DIR_PARAM)
+print('-djpeg', fullfile(DIR_PARAM, [fname '.jpg']));
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/ransac.m b/SD-VBS/benchmarks/stitch/src/matlab/ransac.m
new file mode 100755
index 0000000..4a3c364
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/ransac.m
@@ -0,0 +1,19 @@
+function [retH retPntsIdx]=ransac(pntsPrev, pntsCur, k, epsilon)
+[n temp]=size(pntsPrev);
+pntsPrev=[pntsPrev(:,1:2) ones(n,1)];
+pntsCur=[pntsCur(:,1:2) ones(n,1)];
+
+inlierIdx=cell(k,1);
+inlierNum=zeros(k,1);
+for i=1:k
+    seed=randperm(n);
+    H=calculateH(pntsPrev(seed(1:4),:), pntsCur(seed(1:4),:));
+    err=(pntsCur-transformH(H,pntsPrev));
+    inlierIdx{i}=find(sum(err(:,1:2).^2,2) < epsilon);
+    inlierNum=length(inlierIdx{i});
+end
+
+[v maxIdx]=max(inlierNum);
+retPntsIdx=inlierIdx{maxIdx};
+retH=calculateH(pntsPrev(retPntsIdx,:), pntsCur(retPntsIdx,:));
+
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/readData.m b/SD-VBS/benchmarks/stitch/src/matlab/readData.m
new file mode 100755
index 0000000..19643bb
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/readData.m
@@ -0,0 +1,9 @@
+function retImgs=readData(imgName, dataDir)
+fn=fullfile(dataDir, imgName, '*.jpg');
+filelist=dir(fn);
+
+retImgs=cell(length(filelist),1);
+for i=1:length(filelist)
+    retImgs{i}=imread(fullfile(dataDir, imgName, filelist(i).name));
+end
+
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/stitch/src/matlab/script_run_profile.m
new file mode 100755
index 0000000..f2ca68b
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/script_run_profile.m
@@ -0,0 +1,38 @@
+function script_run_profile(dataDir, resultDir, type, common, toolDir)
+
+path(path, common);
+image_list = 1;
+
+elapsed = zeros(1,2);
+for i=1:image_list
+    Icur = readImage([dataDir, '/', num2str(i) ,'.bmp']);
+        rows = size(Icur,1);
+        cols = size(Icur,2);    
+        fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
+
+    %% Self check params
+    tol = 1;
+
+    %% Timing
+    start = photonStartTiming;
+    
+    [x y v]=harris(Icur,dataDir);
+    interestPntsCur=getANMS(x, y, v, 24, dataDir);
+    Fcur=extractFeatures(Icur, interestPntsCur(:,1), interestPntsCur(:,2), dataDir);
+    
+    %% Timing
+    stop = photonEndTiming;
+
+    temp = photonReportTiming(start, stop);
+    elapsed(1) = elapsed(1) + temp(1);
+    elapsed(2) = elapsed(2) + temp(2);
+
+
+end
+
+%% Self checking
+fWriteMatrix(Fcur, dataDir);
+
+%% Timing
+photonPrintTiming(elapsed);
+
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/showInterestPoints.m b/SD-VBS/benchmarks/stitch/src/matlab/showInterestPoints.m
new file mode 100755
index 0000000..487cae4
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/showInterestPoints.m
@@ -0,0 +1,7 @@
+function showInterestPoints(im, x, y)
+% show 'em
+imagesc(im);
+colormap(gray);
+hold on;
+plot(x,y,'r.');
+hold off;
\ No newline at end of file
diff --git a/SD-VBS/benchmarks/stitch/src/matlab/transformH.m b/SD-VBS/benchmarks/stitch/src/matlab/transformH.m
new file mode 100755
index 0000000..7a22eb8
--- /dev/null
+++ b/SD-VBS/benchmarks/stitch/src/matlab/transformH.m
@@ -0,0 +1,13 @@
+function retPnts=transformH(H, pnts)
+MAX_LIMIT=10000000;
+[n temp]=size(pnts);
+ 
+pntsT = pnts';
+retPnts=(H*pntsT)';
+for i=1:n
+    if retPnts(i,3)~=0
+        retPnts(i,:)=retPnts(i,:)./retPnts(i,3);
+    else
+        retPnts(i,:)=[MAX_LIMIT MAX_LIMIT 1];
+    end
+end
diff --git a/SD-VBS/benchmarks/svm/Makefile b/SD-VBS/benchmarks/svm/Makefile
new file mode 100644
index 0000000..60cc0ec
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/Makefile
@@ -0,0 +1,3 @@
+include ../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/svm/data/Makefile b/SD-VBS/benchmarks/svm/data/Makefile
new file mode 100644
index 0000000..121b0d2
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/Makefile
@@ -0,0 +1,2 @@
+include ../../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
diff --git a/SD-VBS/benchmarks/svm/data/cif/Makefile b/SD-VBS/benchmarks/svm/data/cif/Makefile
new file mode 100644
index 0000000..c23f2f4
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/cif/Makefile
@@ -0,0 +1,7 @@
+INPUT=cif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=svm
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/svm/data/cif/expected.m b/SD-VBS/benchmarks/svm/data/cif/expected.m
new file mode 100644
index 0000000..5d8f400
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/cif/expected.m
@@ -0,0 +1,100 @@
+0.442753        
+1.168547        
+0.374952        
+0.000000        
+1.178224        
+1.109552        
+0.501479        
+0.317081        
+0.624592        
+0.574789        
+0.000000        
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diff --git a/SD-VBS/benchmarks/svm/data/cif/preload b/SD-VBS/benchmarks/svm/data/cif/preload
new file mode 100755
index 0000000..b2e70fc
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/cif/preload
diff --git a/SD-VBS/benchmarks/svm/data/cif/svm b/SD-VBS/benchmarks/svm/data/cif/svm
new file mode 100755
index 0000000..5fb30b6
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/cif/svm
diff --git a/SD-VBS/benchmarks/svm/data/qcif/Makefile b/SD-VBS/benchmarks/svm/data/qcif/Makefile
new file mode 100644
index 0000000..c36e837
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/qcif/Makefile
@@ -0,0 +1,7 @@
+INPUT=qcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=svm
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/svm/data/qcif/expected.m b/SD-VBS/benchmarks/svm/data/qcif/expected.m
new file mode 100644
index 0000000..b4a2d07
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/qcif/expected.m
@@ -0,0 +1,72 @@
+0.442753        
+1.168547        
+0.374952        
+0.000000        
+1.178224        
+1.109552        
+0.501479        
+0.317081        
+0.624592        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
diff --git a/SD-VBS/benchmarks/svm/data/qcif/svm b/SD-VBS/benchmarks/svm/data/qcif/svm
new file mode 100755
index 0000000..3763840
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/qcif/svm
diff --git a/SD-VBS/benchmarks/svm/data/sim/Makefile b/SD-VBS/benchmarks/svm/data/sim/Makefile
new file mode 100644
index 0000000..5a0679f
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/sim/Makefile
@@ -0,0 +1,7 @@
+INPUT=sim
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=svm
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/svm/data/sim/expected.m b/SD-VBS/benchmarks/svm/data/sim/expected.m
new file mode 100644
index 0000000..1b0ced0
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/sim/expected.m
@@ -0,0 +1,16 @@
+0.000000        
+0.458198        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
diff --git a/SD-VBS/benchmarks/svm/data/sim/svm b/SD-VBS/benchmarks/svm/data/sim/svm
new file mode 100755
index 0000000..09dfa6f
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/sim/svm
diff --git a/SD-VBS/benchmarks/svm/data/sim_fast/Makefile b/SD-VBS/benchmarks/svm/data/sim_fast/Makefile
new file mode 100644
index 0000000..4a6fe9a
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/sim_fast/Makefile
@@ -0,0 +1,6 @@
+INPUT=sim_fast
+
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=svm
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
diff --git a/SD-VBS/benchmarks/svm/data/sim_fast/expected.m b/SD-VBS/benchmarks/svm/data/sim_fast/expected.m
new file mode 100644
index 0000000..5f03bb5
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/sim_fast/expected.m
@@ -0,0 +1,20 @@
+0.437103        
+1.062481        
+0.369936        
+0.122430        
+1.072693        
+1.038255        
+0.507418        
+0.307955        
+0.622252        
+0.561853        
+1.083728        
+1.122061        
+1.212223        
+1.154399        
+1.098361        
+1.074637        
+1.095836        
+1.064618        
+0.746331        
+1.088846        
diff --git a/SD-VBS/benchmarks/svm/data/sim_fast/svm b/SD-VBS/benchmarks/svm/data/sim_fast/svm
new file mode 100755
index 0000000..b3dd14c
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/sim_fast/svm
diff --git a/SD-VBS/benchmarks/svm/data/sqcif/Makefile b/SD-VBS/benchmarks/svm/data/sqcif/Makefile
new file mode 100644
index 0000000..eff95ab
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/sqcif/Makefile
@@ -0,0 +1,6 @@
+INPUT=sqcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=svm
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/svm/data/sqcif/expected.m b/SD-VBS/benchmarks/svm/data/sqcif/expected.m
new file mode 100644
index 0000000..7a68ed5
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/sqcif/expected.m
@@ -0,0 +1,60 @@
+0.442753        
+1.168547        
+0.374952        
+0.000000        
+1.178224        
+1.109552        
+0.501479        
+0.317081        
+0.624592        
+0.574789        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
+0.000000        
diff --git a/SD-VBS/benchmarks/svm/data/sqcif/svm b/SD-VBS/benchmarks/svm/data/sqcif/svm
new file mode 100755
index 0000000..c2df0ee
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/sqcif/svm
diff --git a/SD-VBS/benchmarks/svm/data/test/Makefile b/SD-VBS/benchmarks/svm/data/test/Makefile
new file mode 100644
index 0000000..0e138eb
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/test/Makefile
@@ -0,0 +1,6 @@
+INPUT=test
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=svm
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/svm/data/test/expected.m b/SD-VBS/benchmarks/svm/data/test/expected.m
new file mode 100644
index 0000000..104499a
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/test/expected.m
@@ -0,0 +1,4 @@
+0.078894        
+0.458198        
+0.633676        
+0.723067        
diff --git a/SD-VBS/benchmarks/svm/data/test/svm b/SD-VBS/benchmarks/svm/data/test/svm
new file mode 100755
index 0000000..4abb29f
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/data/test/svm
diff --git a/SD-VBS/benchmarks/svm/src/c/cal_learned_func.c b/SD-VBS/benchmarks/svm/src/c/cal_learned_func.c
new file mode 100644
index 0000000..79fdd68
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/c/cal_learned_func.c
@@ -0,0 +1,42 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "svm.h"
+
+float cal_learned_func(int k, F2D* a, float* b, int N, F2D* Y, F2D* X, int dim)
+{
+    float s, ret;
+    int i, j, m, n;
+    F2D *temp, *temp1;
+
+    s=0;
+    for(i=0; i<N; i++)
+    {
+        if( subsref(a,i,0) > 0)
+        {
+            temp = fMallocHandle(1, X->width);
+            temp1 = fMallocHandle(1, X->width);
+
+            for(m=0; m<X->width; m++)
+            {
+                asubsref(temp,m) = subsref(X,i,m);
+                asubsref(temp1,m) = subsref(X,k,m);
+            }
+
+            s += asubsref(a,i) * asubsref(Y,i) * polynomial(3, temp, temp1, dim);
+
+            free(temp);
+            free(temp1);
+        }
+    }
+
+    s = s- arrayref(b,0);
+    ret = s;
+
+    return ret;
+}
+
+
+
+
diff --git a/SD-VBS/benchmarks/svm/src/c/examineExample.c b/SD-VBS/benchmarks/svm/src/c/examineExample.c
new file mode 100644
index 0000000..5335f35
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/c/examineExample.c
@@ -0,0 +1,67 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "svm.h"
+
+int examineExample(int i, F2D* a, float* b, float C, F2D* e, F2D* X, F2D* Y, float tolerance, int N, float eps, int dim)
+{
+    int  ret, j, k, m, n;
+    float E, r1, randVal;
+    float maxDiff, temp;
+
+    if( ( asubsref(a,i) > 0) && ( asubsref(a,i) <C) )
+        E = asubsref(e,i);
+    else
+        E = cal_learned_func(i, a, b, N, Y, X, dim) - asubsref(Y,i);
+
+    r1 = subsref(Y,i,0) * E;
+    if( ((r1 < (-1*tolerance)) && ( asubsref(a,i) < C)) || ((r1 >tolerance) && ( asubsref(a,i) > 0)) )
+    {
+        maxDiff = 0;
+        j = i;
+
+        for(k=0; k<N; k++)
+        {
+            if( ( asubsref(a,k) > 0) && ( asubsref(a,k) < C) )
+            {
+                temp = fabsf( E - asubsref(e,k));
+                if (temp > maxDiff)
+                    j = k;
+            }
+        }
+
+        if ( i!=j)
+        {
+            ret = takeStep(i, j, a, C, e, Y, X, eps, b, N, dim);
+            if(ret == 1)
+                return ret;
+        }
+
+        randVal = 1.0;
+        for( k= (randVal*(N-2)); k<N; k++)
+        {
+            if( ( asubsref(a,k) > 0) && ( asubsref(a,k) <C) )
+            {
+                ret = takeStep(i, k, a, C, e, Y, X, eps, b, N, dim);
+                if (ret == 1)
+                    return ret;
+            }
+        }
+
+        for(k=0; k<N; k++)
+        {
+            ret = takeStep(i, k, a, C, e, Y, X, eps, b, N, dim);
+            if(ret == 1)
+                return ret;
+        }
+    }
+
+    
+    ret = 0;
+    return ret;
+}
+
+
+
+
diff --git a/SD-VBS/benchmarks/svm/src/c/getAlphaFromTrainSet.c b/SD-VBS/benchmarks/svm/src/c/getAlphaFromTrainSet.c
new file mode 100644
index 0000000..681f2c6
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/c/getAlphaFromTrainSet.c
@@ -0,0 +1,98 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "svm.h"
+
+alphaRet* getAlphaFromTrainSet(int N, F2D* trn1, F2D* trn2, int iterations)
+{
+    float tolerance, C, eps, *b;
+    F2D *a_result, *b_result;
+    int NumChanged, r, ExamineAll, cnt, d, dim, ret, iter, i;
+    F2D *X, *Y;
+    F2D *a, *e;
+
+    b = malloc(sizeof(float));
+    alphaRet* alpha;
+    alpha = (alphaRet*)malloc(sizeof(alphaRet));
+    tolerance = 0.001;
+    C = 0.05;
+    d = -1;
+    dim = 256;
+    eps = 0.001;
+    a_result = fSetArray(iterations, N, 0);
+    b_result = fSetArray(iterations, 1, 0);
+    ret = 0;
+    
+    X = usps_read_partial( trn1, trn2, 0, 1, (N/iterations), iterations);
+    
+    for(iter=0; iter<iterations; iter++)
+    {
+        Y = usps_read_partial( trn1, trn2, iter, 0, N/iterations, iterations);
+        
+        a = fSetArray(N, 1, 0);
+        arrayref(b,0) = 0;                  /** check if ptr **/
+        e = fSetArray(N, 1, 0);
+        ExamineAll = 1;
+        cnt = 0;
+        NumChanged = 0;
+
+        while(NumChanged>0 || ExamineAll == 1)
+        {
+            cnt = cnt + 1;
+            NumChanged = 0;
+            if(ExamineAll == 1)
+            {
+                for(i=0; i<N; i++)
+                {
+                    ret = examineExample(i, a, b, C, e, X, Y, tolerance, N, eps, dim);
+                    NumChanged = NumChanged + ret;
+                }
+            }
+            else
+            {
+                for(i=0; i<N; i++)
+                {
+                    if( asubsref(a,i) > 0 && asubsref(a,i) <C )
+                    {
+                        ret = examineExample(i, a, b, C, e, X, Y, tolerance, N, eps, dim);
+                        NumChanged = NumChanged + ret;
+                    }
+                }
+            }
+            if(ExamineAll == 1)
+                ExamineAll = 0;
+            else if(NumChanged == 0)
+                ExamineAll = 1;
+        }
+
+        for(r=0; r<N; r++)
+            subsref(a_result,iter,r) = asubsref(a,r);   /** a_result has size iteration,N .. Check **/
+        asubsref(b_result,iter) = arrayref(b,0);
+
+        fFreeHandle(Y);
+        fFreeHandle(e);
+        fFreeHandle(a);
+    }
+  
+    alpha->C = C;
+    alpha->d = d;
+    alpha->dim = dim;
+    alpha->eps = eps;
+    alpha->a_result = a_result;
+    alpha->b_result = b_result;
+    alpha->a = a;
+    alpha->b = arrayref(b,0);
+    alpha->X = X;
+    alpha->tolerance = tolerance;
+    alpha->ret;
+    
+    free(b);
+   
+    return alpha; 
+
+}
+
+
+
+
diff --git a/SD-VBS/benchmarks/svm/src/c/polynomial.c b/SD-VBS/benchmarks/svm/src/c/polynomial.c
new file mode 100644
index 0000000..cce9190
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/c/polynomial.c
@@ -0,0 +1,42 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "svm.h"
+
+float polynomial(int d, F2D* a, F2D* b, int dim)
+{
+    float ret;
+    F2D *bt, *bt1;
+    int i,j,r,c;
+
+    r = b->height;
+    c = b->width;
+
+    bt = fMallocHandle(c, r);
+
+    for(i=0; i<r; i++)
+    {
+        for(j=0; j<c; j++)
+        {
+            subsref(bt,j,i) = subsref(b,i,j);
+        }
+    }
+
+    bt1 = fMtimes(a, bt);
+    fFreeHandle(bt);
+    
+    if(bt1->height == 1 && bt1->width ==1)
+        ret = pow(asubsref(bt1,0),d)/dim;
+    else
+    {
+        fFreeHandle(bt1);
+        return -1;
+    }
+
+    fFreeHandle(bt1);
+    return ret;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/svm/src/c/script_svm.c b/SD-VBS/benchmarks/svm/src/c/script_svm.c
new file mode 100644
index 0000000..62a264d
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/c/script_svm.c
@@ -0,0 +1,171 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "svm.h"
+#include <malloc.h>
+#include "extra.h"
+#define SVM_MEM 1<<24
+int main(int argc, char* argv[])
+{
+    SET_UP
+    mallopt(M_TOP_PAD, SVM_MEM);
+    mallopt(M_MMAP_MAX, 0);
+    int iter, N, Ntst, i, j, k, n;
+    F2D* trn1, *tst1, *trn2, *tst2, *Yoffset;
+    alphaRet* alpha;
+    F2D *a_result, *result;
+    F2D *s;
+    F2D *b_result;
+    F2D *Xtst, *Ytst;
+    char im1[256];
+    int dim = 256;
+
+    N = 100;
+    Ntst = 100;
+    iter = 10;
+
+    #ifdef test
+    N = 4;
+    Ntst = 4;
+    iter = 2;
+    #endif
+    
+    #ifdef sim_fast
+    N = 20;
+    Ntst = 20;
+    iter = 2;
+    #endif
+
+    #ifdef sim
+    N = 16;
+    Ntst = 16;
+    iter = 8;
+    #endif
+    
+    #ifdef sqcif
+    N = 60;
+    Ntst = 60;
+    iter = 6;
+    #endif
+    
+    #ifdef qcif
+    N = 72;
+    Ntst = 72;
+    iter = 8;
+    #endif
+    
+    #ifdef vga
+    N = 450;
+    Ntst = 450;
+    iter = 15;
+    #endif
+    
+    #ifdef wuxga
+    N = 1000;
+    Ntst = 1000;
+    iter = 20;
+    #endif
+
+
+    printf("trn file 1: ");
+    scanf("%s", im1);
+    trn1 = readFile(im1);   
+
+    printf("trn file 2: ");
+    scanf("%s", im1);
+    trn2 = readFile(im1);   
+
+    printf("tst file 1: ");
+    scanf("%s", im1);
+    tst1 = readFile(im1);   
+
+    printf("tst file 2: ");
+    scanf("%s", im1);
+    tst2 = readFile(im1);       
+
+    printf("start.\n");
+    for_each_job{
+        alpha = getAlphaFromTrainSet(N, trn1, trn2, iter);
+        a_result = alpha->a_result;
+        b_result = alpha->b_result;
+        Yoffset = fSetArray(iter, N, 0);
+    
+        Xtst = usps_read_partial(tst1, tst2, -1, 1, Ntst/iter, iter);
+        Ytst = usps_read_partial(tst1, tst2, -1, 0, Ntst/iter, iter);
+    
+        for(i=0; i<iter; i++)
+        {
+            F2D *temp;
+            temp = usps_read_partial(trn1, trn2, i, 0, N/iter, iter);
+            for(j=0; j<N; j++)
+                subsref(Yoffset,i,j) = asubsref(temp,j);
+            fFreeHandle(temp);
+        }
+    
+    
+        result = fSetArray(Ntst,1,0);
+        for( n=0; n<Ntst; n++)
+        {
+            float maxs=0;
+            s=fSetArray(iter,1,0);
+            for( i=0; i<iter; i++)
+            {
+                for (j=0; j<N; j++)
+                {
+                    if (subsref(a_result,i,j) > 0)
+                    {
+                        F2D *Xtemp, *XtstTemp, *X;
+                        X = alpha->X;
+                        Xtemp = fDeepCopyRange(X,j,1,0,X->width);
+                        XtstTemp = fDeepCopyRange(Xtst, n,1,0,Xtst->width);
+                        asubsref(s,i) = asubsref(s,i) + subsref(a_result,i,j) * subsref(Yoffset,i,j) * polynomial(3,Xtemp,XtstTemp, dim);
+                        fFreeHandle(Xtemp); 
+                        fFreeHandle(XtstTemp); 
+                    }
+                }
+                asubsref(s,i) = asubsref(s,i) - asubsref(b_result,i);
+                if( asubsref(s,i) > maxs)
+                    maxs = asubsref(s,i);
+            }
+            
+            fFreeHandle(s);
+            asubsref(result,n) = maxs;
+        }
+    }
+    printf("end..\n");
+#ifdef CHECK   
+    /** Self checking - use expected.txt from data directory  **/
+    {
+        int ret=0;
+        float tol = 0.5;
+#ifdef GENERATE_OUTPUT
+        fWriteMatrix(result, argv[1]);
+#endif
+        ret = fSelfCheck(result, "expected_C.txt", tol);
+        if (ret == -1)
+            printf("Error in SVM\n");
+    }
+    /** Self checking done **/
+#endif
+
+    fFreeHandle(trn1);
+    fFreeHandle(tst1);
+    fFreeHandle(trn2);
+    fFreeHandle(tst2);
+    fFreeHandle(Yoffset);
+    fFreeHandle(result);
+    fFreeHandle(alpha->a_result);
+    fFreeHandle(alpha->b_result);
+    fFreeHandle(alpha->X);
+    free(alpha);
+    fFreeHandle(Xtst);
+    fFreeHandle(Ytst);
+    WRITE_TO_FILE
+    return 0;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/svm/src/c/svm.h b/SD-VBS/benchmarks/svm/src/c/svm.h
new file mode 100644
index 0000000..9675371
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/c/svm.h
@@ -0,0 +1,38 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#ifndef _SCRIPT_SVM_
+#define _SCRIPT_SVM_
+
+#include "sdvbs_common.h"
+
+typedef struct
+{
+    F2D* a;
+    float b;
+    float C;
+    int d;
+    int dim;
+    F2D* e;
+    float eps;
+    F2D* a_result;
+    F2D* b_result;
+    F2D* X;
+    F2D *Y;
+    float tolerance;
+    int ret;
+
+}alphaRet;
+
+alphaRet* getAlphaFromTrainSet(int N, F2D* trn1, F2D* trn2, int iterations);
+float polynomial(int d, F2D* a, F2D* b, int dim);
+float cal_learned_func(int k, F2D* a, float* b, int N, F2D* Y, F2D* X, int dim);
+int examineExample(int i, F2D* a, float* b, float C, F2D* e, F2D* X, F2D* Y, float tolerance, int N, float eps, int dim);
+int takeStep(int i, int j, F2D* a, float C, F2D* e, F2D* Y, F2D* X, float eps, float* b, int N, int dim);
+F2D* usps_read_partial(F2D* dcell1, F2D* dcell2, int idx, int opt, int dim, int iterations);
+int script_svm();
+
+#endif
+
+
diff --git a/SD-VBS/benchmarks/svm/src/c/takeStep.c b/SD-VBS/benchmarks/svm/src/c/takeStep.c
new file mode 100644
index 0000000..ae550c2
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/c/takeStep.c
@@ -0,0 +1,188 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "svm.h"
+
+int takeStep(int i, int j, F2D* a, float C, F2D* e, F2D* Y, F2D* X, float eps, float* b, int N, int dim)
+{
+    int ret=1;
+    float s;
+    int m, n, k;
+    float Ei, Ej, gamma, L, H;
+    F2D *a_old;
+    float k11, k12, k22, eta;
+    F2D *temp, *temp1, *temp2;
+    float t, t1, t2;
+    float bnew, delta_b;
+    float c1, c2, Lobj, Hobj;
+    
+    if(i==j)
+        return 0;
+        
+    a_old = fDeepCopy(a);
+    
+    if( asubsref(a_old,i)>0 && asubsref(a_old,i)<C ) 
+        Ei = asubsref(e,i);
+    else
+        Ei = cal_learned_func(i, a, b, N, Y, X, dim) - asubsref(Y,i);
+
+    if( asubsref(a_old,j)>0 && asubsref(a_old,j)<C ) 
+        Ej = asubsref(e,j);
+    else
+        Ej = cal_learned_func(j, a, b, N, Y, X, dim) - asubsref(Y,j);
+
+    s = asubsref(Y,i) * asubsref(Y,j);
+
+    if( asubsref(Y,i) == asubsref(Y,j) )
+    {
+        gamma = asubsref(a_old,i) + asubsref(a_old,j);
+        if(gamma > C)
+        {
+            L = gamma - C;
+            H = C;
+        }
+        else
+        {
+            L = 0;
+            H = gamma;
+        }
+    }
+    else
+    {
+        gamma = asubsref(a_old,i) - asubsref(a_old,j);
+        if(gamma > 0)
+        {
+            L = 0;
+            H = C - gamma;
+        }
+        else
+        {
+            L = -gamma;
+            H = C;
+        }
+    }
+    
+
+    if(L==H)
+    {
+        fFreeHandle(a_old);
+        return 0;
+    }
+           
+    temp = fMallocHandle(1, X->width);
+    temp1 = fMallocHandle(1, X->width);
+
+    for(m=0; m<X->width; m++)
+    {
+        asubsref(temp,m) = subsref(X,i,m);
+        asubsref(temp1,m) = subsref(X,j,m);
+    }
+
+    k11 = polynomial(3, temp, temp, dim);
+    k12 = polynomial(3, temp, temp1, dim);
+    k22 = polynomial(3, temp1, temp1, dim);
+    eta = 2 * k12 - k11 - k22;
+
+    fFreeHandle(temp1);
+    fFreeHandle(temp);
+
+    if(eta<0)
+    {
+        asubsref(a,j) = asubsref(a_old,j) + asubsref(Y,j) * (Ej-Ei)/eta;
+        if( asubsref(a,j) < L)
+            asubsref(a,j) = L;
+        else if( asubsref(a,j) > H )
+            asubsref(a,j) = H;
+    }
+    else
+    {
+        c1 = eta/2;
+        c2 = asubsref(Y,j) * (Ei-Ej) - eta * asubsref(a_old,j);
+        Lobj = c1 * L * L + c2 * L;
+        Hobj = c1 * H * H + c2 * H;
+
+        if (Lobj > (Hobj+eps))
+            asubsref(a,j) = L;
+        else if (Lobj < (Hobj-eps))
+            asubsref(a,j) = H;
+        else
+            asubsref(a,j) = asubsref(a_old,j);
+    }
+    
+    if( fabsf( asubsref(a,j)- asubsref(a_old,j) ) < (eps* (asubsref(a,j) + asubsref(a_old,j) +eps)) )
+    {
+        fFreeHandle(a_old);
+        return 0;
+    }
+
+    asubsref(a,i) = asubsref(a_old,i) - s * ( asubsref(a,j) - asubsref(a_old,j) );
+
+    if( asubsref(a,i) < 0)
+    {
+        asubsref(a,j) = asubsref(a,j) + s * asubsref(a,i);
+        asubsref(a,i) = 0;
+    }
+    else if (asubsref(a,i) > C)
+    {
+        t = asubsref(a,i) - C;
+        asubsref(a,j) = asubsref(a,j) + s * t;
+        asubsref(a,i) = C;
+    }
+
+    /** Update threshold to react change in Lagrange multipliers **/
+
+    if( asubsref(a,i) > 0 && asubsref(a,i) < C )
+        bnew = arrayref(b,0) + Ei + asubsref(Y,i) * (asubsref(a,i) - asubsref(a_old,i)) * k11 + asubsref(Y,j) * (asubsref(a,j) - asubsref(a_old,j)) * k12;
+    else
+    {
+        if( asubsref(a,j) > 0 && asubsref(a,j) < C )
+            bnew = arrayref(b,0) + Ej + asubsref(Y,i) * (asubsref(a,i) - asubsref(a_old,i)) * k12 + asubsref(Y,j) * (asubsref(a,j) - asubsref(a_old,j)) * k22;
+        else
+        {
+            float b1, b2;
+            b1 = arrayref(b,0) + Ei + asubsref(Y,i) * (asubsref(a,i) - asubsref(a_old,i)) * k11 + asubsref(Y,j) * (asubsref(a,j) - asubsref(a_old,j)) * k12;
+            b2 = arrayref(b,0) + Ej + asubsref(Y,i) * (asubsref(a,i) - asubsref(a_old,i)) * k12 + asubsref(Y,j) * (asubsref(a,j) - asubsref(a_old,j)) * k22;
+            bnew = (b1 + b2) / 2;
+        }
+    }
+    delta_b = bnew - arrayref(b,0);
+    arrayref(b,0) = bnew;
+
+    /** Update error cache using new Lagrange multipliers 24ai **/
+
+    t1 = asubsref(Y,i) * (asubsref(a,i)-asubsref(a_old,i));
+    t2 = asubsref(Y,j) * (asubsref(a,j)-asubsref(a_old,j));
+
+    temp = fMallocHandle(1, X->width);
+    temp1 = fMallocHandle(1, X->width);
+    temp2 = fMallocHandle(1, X->width);
+
+    for (k=0; k<N; k++)
+    {
+        if (0 < asubsref(a_old,i) && asubsref(a_old,i) < C )
+        {
+
+            for(m=0; m<X->width; m++)
+            {
+                asubsref(temp,m) = subsref(X,i,m);
+                asubsref(temp1,m) = subsref(X,k,m);
+                asubsref(temp2,m) = subsref(X,j,m);
+            }
+
+            asubsref(e,k) = asubsref(e,k)+t1 * polynomial(3, temp, temp1, dim) + t2 * polynomial(3, temp2, temp1, dim) - delta_b;
+            asubsref(e,i) = 0;
+            asubsref(e,j) = 0;
+        }
+    }
+    
+    fFreeHandle(a_old);
+    fFreeHandle(temp);
+    fFreeHandle(temp1);
+    fFreeHandle(temp2);
+    ret = 1;
+    return ret;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/svm/src/c/usps_read_partial.c b/SD-VBS/benchmarks/svm/src/c/usps_read_partial.c
new file mode 100644
index 0000000..9cc9df0
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/c/usps_read_partial.c
@@ -0,0 +1,85 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "svm.h"
+
+F2D* usps_read_partial(F2D* dcell1, F2D* dcell2, int idx, int opt, int dim, int iterations)
+{
+    F2D *ret, *X, *Y;
+    F2D *ADD;
+    int i, j, k, m, n;
+
+    F2D *temp, *temp1;
+
+    if(opt == 1)
+    {
+        for(i=0; i<iterations; i++)
+        {
+            if(i==0)
+            {
+                X = fMallocHandle(dim, dcell1->width);
+                for(m=0; m<dim; m++)
+                {
+                    for(n=0; n<dcell1->width; n++)
+                    {
+                        subsref(X,m,n) = subsref(dcell1,m,n);
+                    }
+                }
+            }
+            else
+            {
+                temp = fDeepCopy(X);
+                fFreeHandle(X);
+                temp1 = fMallocHandle(dim, dcell2->width);
+
+                for(m=0; m<dim; m++)
+                {
+                    for(n=0; n<dcell2->width; n++)
+                    {
+                        subsref(temp1,m,n) = subsref(dcell2,m,n);
+                    }
+                }
+                X = ffVertcat(temp, temp1);
+                fFreeHandle(temp);
+                fFreeHandle(temp1);
+            }
+        }
+        ret = fDeepCopy(X);
+        fFreeHandle(X);
+    }
+    else
+    {
+        for(i=0; i<iterations; i++)
+        {
+            if(idx == -1)
+                ADD = fSetArray(dim, 1, i+1);
+            else
+            {
+                if( i!= idx)
+                    ADD = fSetArray(dim, 1, -1);
+                else
+                    ADD = fSetArray(dim, 1, 1);
+            }
+            if(i==0)
+            {
+                Y = fDeepCopy(ADD);
+            }
+            else
+            {
+                F2D* t = fDeepCopy(Y);
+                fFreeHandle(Y);
+                Y = ffVertcat(t, ADD);
+                fFreeHandle(t);
+            }
+            fFreeHandle(ADD);
+        }
+        ret = fDeepCopy(Y);
+        fFreeHandle(Y);
+    }
+    
+    return ret;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/svm/src/matlab/Makefile.include b/SD-VBS/benchmarks/svm/src/matlab/Makefile.include
new file mode 100644
index 0000000..0100d2a
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/Makefile.include
@@ -0,0 +1,4 @@
+SRC_PATH=..
+MAT_MAIN=testSVM
+MAT_LIST=$(SRC_PATH)/testSVM.m $(SRC_PATH)/getAlphaFromTrainSet.m $(SRC_PATH)/usps_read_partial.m $(SRC_PATH)/usps_read_partial_opt0.m $(SRC_PATH)/examineExample.m $(SRC_PATH)/cal_learned_func.m $(SRC_PATH)/polynomial.m $(SRC_PATH)/takeStep.m 
+
diff --git a/SD-VBS/benchmarks/svm/src/matlab/cal_learned_func.m b/SD-VBS/benchmarks/svm/src/matlab/cal_learned_func.m
new file mode 100644
index 0000000..de0804b
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/cal_learned_func.m
@@ -0,0 +1,11 @@
+function ret=cal_learned_func(k, a, b, N, Y, X,dim)
+
+s=0;
+for i=1:N
+    if a(i,1) > 0
+        s = s +a(i,1)*Y(i,1)*polynomial(3,X(i,:),X(k,:),dim);        
+    end
+end
+s = s - b;
+ret=s;
+
diff --git a/SD-VBS/benchmarks/svm/src/matlab/d16trn_1.m b/SD-VBS/benchmarks/svm/src/matlab/d16trn_1.m
new file mode 100644
index 0000000..171e79b
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/d16trn_1.m
@@ -0,0 +1,1008 @@
+function out = d16trn_1
+out = [...
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\ No newline at end of file
diff --git a/SD-VBS/benchmarks/svm/src/matlab/d16trn_2.m b/SD-VBS/benchmarks/svm/src/matlab/d16trn_2.m
new file mode 100644
index 0000000..8e80bf4
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/d16trn_2.m
@@ -0,0 +1,734 @@
+function out = d16trn_2
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\ No newline at end of file
diff --git a/SD-VBS/benchmarks/svm/src/matlab/d16tst_1.m b/SD-VBS/benchmarks/svm/src/matlab/d16tst_1.m
new file mode 100644
index 0000000..55eeeca
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/d16tst_1.m
@@ -0,0 +1,267 @@
+function out = d16tst_1
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\ No newline at end of file
diff --git a/SD-VBS/benchmarks/svm/src/matlab/d16tst_2.m b/SD-VBS/benchmarks/svm/src/matlab/d16tst_2.m
new file mode 100644
index 0000000..4aed269
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/d16tst_2.m
@@ -0,0 +1,201 @@
+function out = d16tst_2
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+];
\ No newline at end of file
diff --git a/SD-VBS/benchmarks/svm/src/matlab/examineExample.m b/SD-VBS/benchmarks/svm/src/matlab/examineExample.m
new file mode 100644
index 0000000..a60ee13
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/examineExample.m
@@ -0,0 +1,60 @@
+function [a,b,e,ret]=examineExample(i, a, b, C, e, X, Y, tolerance, N, eps, dim)
+
+ret = 0;
+if (a(i,1) > 0) && (a(i,1) < C)
+    E = e(i,1);
+else
+    E = cal_learned_func(i, a, b, N, Y, X, dim) - Y(i,1);
+end
+
+ r1 = Y(i,1) * E;
+
+ if (r1 < -1*tolerance && a(i,1) < C) || (r1 > tolerance && a(i,1) > 0)
+    %case1 argmax E-E2%
+    maxEDiff=0;
+    j=i;
+    for k=1:N
+        if a(k,1) > 0 && a(k,1) < C
+            temp= abs(E - e(k,1));
+            if temp > maxEDiff
+                j=k;
+            end
+        end
+    end
+    
+    if i~=j
+        [a,b,e,ret]=takeStep(i, j, a, C, e, Y, X, eps, b, N, dim);
+    end
+
+    if(ret ~=1)
+        %iterate through the non-bound example%
+%        for k=round(randWrapper(1,1)*(N-2))+1:N
+        randVal = 1.0;
+        for k=(randVal*(N-1)):N
+            if (a(k,1) > 0 && a(k,1) < C && ret == 0)
+%                           if (i == k)
+%                                   ret = 0;
+%                           else
+                    [a,b,e,ret]=takeStep(i, k, a, C, e, Y, X, eps, b, N, dim);
+%                           end
+            end
+        end
+    end
+
+    if(ret ~= 1)
+        %iter for entire training set%
+        for k=1:N
+            if(ret == 0)
+%                           if (i == k)
+%                                   ret = 0;
+%                           else
+                    [a,b,e,ret]=takeStep(i, k, a, C, e, Y, X, eps, b, N, dim);
+%                           end
+            end
+        end
+    end
+
+    else
+
+end 
+
diff --git a/SD-VBS/benchmarks/svm/src/matlab/getAlphaFromTrainSet.m b/SD-VBS/benchmarks/svm/src/matlab/getAlphaFromTrainSet.m
new file mode 100644
index 0000000..bd2bec7
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/getAlphaFromTrainSet.m
@@ -0,0 +1,58 @@
+function [a,b,C,d,dim,e,eps,a_result,b_result,X,tolerance,Y,ret]=getAlphaFromTrainSet(N, d16trn_1, d16trn_2, Iterations)
+
+
+tolerance=0.001;
+C=0.05;
+d = -1;
+dim=256;
+eps=0.001;
+a_result=zeros(Iterations,N);
+b_result=zeros(Iterations,1);
+ret = 0;
+Y = 0;
+
+X=usps_read_partial(d16trn_1, d16trn_2,1,1,N/Iterations, Iterations);
+
+for iter=1:Iterations
+    Y=usps_read_partial(d16trn_1,d16trn_2,iter,0,N/Iterations, Iterations);
+    if iter==1
+    fWriteMatrix(Y, './');
+    end
+
+    a=zeros(N,1);
+    b=0;
+    e=zeros(N,1);
+    ExamineAll=1;  
+    cnt=0;
+    NumChanged=0;
+    while (NumChanged>0 || ExamineAll == 1)
+        cnt=cnt+1;
+        NumChanged=0;
+        if ExamineAll==1
+            for i=1:N
+                [a,b,e,ret] = examineExample(i, a, b, C, e, X, Y, tolerance, N, eps, dim);
+                NumChanged=NumChanged+ret;
+            end
+        else
+            for i=1:N
+                if a(i,1) > 0 && a(i,1) < C
+                    [a,b,e,ret] = examineExample(i, a, b, C, e, X, Y, tolerance, N, eps, dim);
+                    NumChanged=NumChanged+ret;
+                end
+            end
+        end
+        if ExamineAll==1
+            ExamineAll=0;
+        elseif NumChanged==0 
+            ExamineAll=1;
+        end
+    end
+    
+    for r = 1:N
+        a_result(iter,r) = a(r,1);
+    end
+    
+%    a_result=transpose(a); %KVS: Problem using transpose function here. So wrote the code above
+    b_result(iter,1)=b;
+end
+
diff --git a/SD-VBS/benchmarks/svm/src/matlab/polynomial.m b/SD-VBS/benchmarks/svm/src/matlab/polynomial.m
new file mode 100644
index 0000000..07b0af7
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/polynomial.m
@@ -0,0 +1,5 @@
+function ret = polynomial(d, a, b, dim)

+

+bt = transpose(b);

+ret=(a*bt)^d/dim;

+

diff --git a/SD-VBS/benchmarks/svm/src/matlab/randWrapper.m b/SD-VBS/benchmarks/svm/src/matlab/randWrapper.m
new file mode 100644
index 0000000..dbef132
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/randWrapper.m
@@ -0,0 +1,17 @@
+function out = randWrapper(m,n)
+
+out = zeros(m,n);
+
+seed = 0.9;
+for i=1:m
+    for j=1:n
+        if(i<j)
+            out(i,j) = seed * (i/j);
+        else
+            out(i,j) = seed * (j/i);
+        end
+    end
+end
+
+end
+
diff --git a/SD-VBS/benchmarks/svm/src/matlab/readMatrix.m b/SD-VBS/benchmarks/svm/src/matlab/readMatrix.m
new file mode 100644
index 0000000..fe684c5
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/readMatrix.m
@@ -0,0 +1,28 @@
+function readMatrix(srcImage, outName)
+
+write = fopen([outName '.m'], 'w');
+
+count = fwrite(write, 'function out = ');
+count = fwrite(write, outName);
+fprintf(write, '\n');
+count = fwrite(write, 'out = [...');
+fprintf(write, '\n');    
+
+height = size(srcImage,1);
+width = size(srcImage,2);
+
+for nI=1:height
+    for nJ=1:width
+        fprintf(write, '%f ', srcImage(nI,nJ));
+    end
+    if(nI < height)
+        fprintf(write, ';...\n');
+    end
+end
+
+fprintf(write, '...\n');
+count = fwrite(write, '];');
+
+fclose(write);
+
+end
diff --git a/SD-VBS/benchmarks/svm/src/matlab/readSVM.m b/SD-VBS/benchmarks/svm/src/matlab/readSVM.m
new file mode 100644
index 0000000..60ca9ab
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/readSVM.m
@@ -0,0 +1,103 @@
+function out = readSVM
+out = [...
+1.223457 ;...
+1.855754 ;...
+1.376088 ;...
+0.030422 ;...
+1.856493 ;...
+2.047219 ;...
+1.576963 ;...
+1.232858 ;...
+1.728406 ;...
+1.622006 ;...
+1.604181 ;...
+1.869471 ;...
+1.989414 ;...
+1.848204 ;...
+1.820905 ;...
+1.868821 ;...
+0.286260 ;...
+1.928466 ;...
+1.556423 ;...
+1.319761 ;...
+0.121424 ;...
+1.754355 ;...
+1.794645 ;...
+1.723598 ;...
+1.329587 ;...
+2.062461 ;...
+1.780022 ;...
+2.008189 ;...
+1.908582 ;...
+1.775486 ;...
+1.471500 ;...
+1.721978 ;...
+1.944388 ;...
+1.961474 ;...
+1.329368 ;...
+1.906615 ;...
+0.174616 ;...
+1.827709 ;...
+2.004605 ;...
+1.779342 ;...
+2.086185 ;...
+1.580910 ;...
+1.650439 ;...
+1.206136 ;...
+1.918404 ;...
+1.808864 ;...
+1.865793 ;...
+1.853483 ;...
+1.650675 ;...
+1.727663 ;...
+1.894633 ;...
+2.033492 ;...
+2.063332 ;...
+2.028869 ;...
+1.909349 ;...
+1.908680 ;...
+1.910475 ;...
+1.859123 ;...
+1.346371 ;...
+1.860034 ;...
+1.871194 ;...
+2.141781 ;...
+1.580515 ;...
+1.572692 ;...
+1.913354 ;...
+1.969055 ;...
+1.999745 ;...
+1.827505 ;...
+1.891057 ;...
+1.844511 ;...
+1.761861 ;...
+1.921365 ;...
+1.803054 ;...
+1.806654 ;...
+0.967202 ;...
+1.954018 ;...
+1.755541 ;...
+1.896539 ;...
+0.601093 ;...
+1.522254 ;...
+1.894835 ;...
+1.993057 ;...
+1.905233 ;...
+1.665072 ;...
+1.596733 ;...
+1.887480 ;...
+1.335537 ;...
+1.584868 ;...
+1.850636 ;...
+1.902566 ;...
+2.069785 ;...
+1.629746 ;...
+1.987844 ;...
+1.711571 ;...
+1.784246 ;...
+1.995788 ;...
+1.507318 ;...
+1.487873 ;...
+1.601705 ;...
+1.468391 ...
+];
\ No newline at end of file
diff --git a/SD-VBS/benchmarks/svm/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/svm/src/matlab/script_run_profile.m
new file mode 100644
index 0000000..b84a9d8
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/script_run_profile.m
@@ -0,0 +1,113 @@
+function script_run_profile(dataDir, resultDir, type, commonDir,toolDir)
+
+path(path, commonDir);
+Iterations = 2;
+
+file = [dataDir, '/d16trn_1.txt'];
+trn_1 = readFile(file);
+file = [dataDir, '/d16trn_2.txt'];
+trn_2 = readFile(file);
+file = [dataDir, '/d16tst_1.txt'];
+tst_1 = readFile(file);
+file = [dataDir, '/d16tst_2.txt'];
+tst_2 = readFile(file);
+
+trn_1 = d16trn_1;
+trn_2 = d16trn_2;
+tst_1 = d16tst_1;
+tst_2 = d16tst_2;
+
+    N = 100;
+    Ntst = 100;
+    Iterations = 10;
+
+    if(strcmp(type, 'test'))
+    N = 4;
+    Ntst = 4;
+    Iterations = 2;
+    elseif(strcmp(type, 'sim_fast'))
+    N = 20;
+    Ntst = 20;
+    Iterations = 2;
+    elseif(strcmp(type, 'sim'))
+    N = 16;
+    Ntst = 16;
+    Iterations = 8;
+    elseif(strcmp(type, 'sqcif'))
+    N = 60;
+    Ntst = 60;
+    Iterations = 6;
+    elseif(strcmp(type, 'qcif'))
+    N = 72;
+    Ntst = 72;
+    Iterations = 8;
+    elseif(strcmp(type, 'vga'))
+    N = 450;
+    Ntst = 450;
+    Iterations = 15;
+    elseif(strcmp(type, 'wuxga'))
+    N = 1000;
+    Ntst = 1000;
+    Iterations = 20;
+    end
+    
+fprintf(1,'Input size\t\t- (%dx%dx%d)\n', N, Ntst,Iterations);
+
+elapsed = zeros(1,2);
+%% Timing
+start = photonStartTiming;
+
+[a,b,C,d,dim,e,eps,a_result,b_result,X,tolerance,Y,ret] = getAlphaFromTrainSet(N, trn_1, trn_2, Iterations);
+
+Yoffset=zeros(Iterations,N);
+ 
+Xtst=usps_read_partial(tst_1, tst_2 ,0,1,Ntst/Iterations, Iterations);
+Ytst=usps_read_partial(tst_1, tst_2, 0,0,Ntst/Iterations, Iterations);
+ 
+ for i=1:Iterations
+     temp=usps_read_partial(trn_1,trn_2, i,0,N/Iterations, Iterations);
+     Yoffset(i,:)=transpose(temp);
+ end
+ 
+ 
+ %error=0;
+ result=zeros(Ntst,1);
+ for n=1:Ntst
+     maxs = 0;
+     s=zeros(Iterations,1);
+     for i=1:Iterations
+         for j=1:N
+             if a_result(i,j) > 0
+                 s(i,1) = s(i,1) +a_result(i,j)*Yoffset(i,j)*polynomial(3,X(j,:),Xtst(n,:), dim);        
+             end
+         end
+         s(i,1) = s(i,1) - b_result(i,1);
+         
+         if( s(i,1) > maxs)
+             maxs = s(i,1);
+         end
+     end
+     result(n,1) = maxs;
+ end
+ 
+ %% Timing
+stop = photonEndTiming;
+
+temp = photonReportTiming(start, stop);
+elapsed(1) = elapsed(1) + temp(1);
+elapsed(2) = elapsed(2) + temp(2);
+ 
+ %% Self check
+ fWriteMatrix(result, dataDir);
+ tol = 0.001;
+ ret = fSelfCheck(result,dataDir, tol);
+ if(ret == 0)
+     disp('Error in SVM');
+ end
+
+%% Timing
+photonPrintTiming(elapsed);
+
+
+
+
diff --git a/SD-VBS/benchmarks/svm/src/matlab/selfCheck.m b/SD-VBS/benchmarks/svm/src/matlab/selfCheck.m
new file mode 100644
index 0000000..ac80ebd
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/selfCheck.m
@@ -0,0 +1,33 @@
+function ret = selfCheck(in1, in2, tol)
+
+r1 = size(in1, 1);
+c1 = size(in1, 2);
+
+r2 = size(in2, 1);
+c2 = size(in2, 2);
+
+ret = 1;
+
+if r1~=r2 
+    disp(1298);
+    ret = 0;
+end
+
+if c1 ~= c2
+        disp(1297);
+        ret = 0;
+end
+
+for i=1:r1
+    if(ret == 0)
+        break;
+    end
+    for j=1:c1
+        if( abs(in1(i,j)-in2(i,j)) > tol)
+            ret = 0;
+            break;
+        end
+    end
+end
+
+
diff --git a/SD-VBS/benchmarks/svm/src/matlab/takeStep.m b/SD-VBS/benchmarks/svm/src/matlab/takeStep.m
new file mode 100644
index 0000000..565f9ec
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/takeStep.m
@@ -0,0 +1,137 @@
+function [a,b,e,ret]=takeStep(i, j, a1, C, e1, Y, X, eps, b1, N, dim)
+
+a = a1;
+e = e1;
+b = b1;
+
+ret = 1;
+if i == j
+    ret =0;
+end
+
+if( ret ~= 0)
+     %variable initialization%
+    a_old = a;
+
+    if a_old(i,1) > 0 && a_old(i,1) < C
+        Ei = e(i,1);
+    else
+        Ei = cal_learned_func(i, a, b, N, Y, X, dim) - Y(i,1);
+    end
+
+    if a_old(j,1) > 0 && a_old(j,1) < C
+        Ej = e(j,1);
+    else
+        Ej = cal_learned_func(j, a, b, N, Y, X, dim) - Y(j,1);
+    end
+
+    s = Y(i,1) * Y(j,1);
+
+    %Compute L, H%
+    if Y(i,1) == Y(j,1)
+        gamma = a_old(i,1) + a_old(j,1);
+        if gamma > C
+            L = gamma-C;
+            H = C;
+        else
+            L = 0;
+            H = gamma;
+        end
+    else
+        gamma = a_old(i,1) - a_old(j,1);
+        if gamma > 0
+            L = 0;
+            H = C - gamma;
+        else
+            L = -gamma;
+            H = C;
+        end
+    end
+    
+
+    if L == H
+        ret=0;
+    end
+    
+end    
+
+if(ret ~=0)
+%     %Compute eta
+    k11 = polynomial(3,X(i,:), X(i,:), dim);
+    k12 = polynomial(3,X(i,:), X(j,:), dim);
+    k22 = polynomial(3,X(j,:), X(j,:), dim);
+    eta = 2 * k12 - k11 - k22;
+    
+    if eta < 0
+        a(j,1) = a_old(j,1) + Y(j,1) * (Ej - Ei) / eta;
+        if a(j,1) < L
+            a(j,1) = L;
+        elseif a(j,1) > H
+            a(j,1) = H;
+        end
+    else
+        %Compute Lobj, Hobj: objective function at a2=L, a2=H 22di
+        c1 = eta/2;
+        c2 = Y(j,1) * (Ei-Ej)- eta * a_old(j,1);
+        Lobj = c1 * L * L + c2 * L;
+        Hobj = c1 * H * H + c2 * H;
+
+        if (Lobj > Hobj+eps)
+            a(j,1) = L;
+        elseif (Lobj < Hobj-eps)
+            a(j,1) = H;
+        else
+            a(j,1) = a_old(j,1);
+        end
+    end
+    
+end
+
+
+if( ret~= 0)
+
+    if abs(a(j,1)-a_old(j,1)) < eps*(a(j,1)+a_old(j,1)+eps)
+        ret=0;
+    else
+        a(i,1) = a_old(i,1) - s * (a(j,1) - a_old(j,1));
+        if a(i,1) < 0
+            a(j,1) = a(j,1) + s * a(i,1);
+            a(i,1) = 0;
+        elseif a(i,1) > C
+            t = a(i,1)-C;
+            a(j,1) = a(j,1) + s * t;
+            a(i,1) = C;
+        end
+
+        %Update threshold to reect change in Lagrange multipliers
+        if a(i,1) > 0 && a(i,1) < C
+            bnew = b + Ei + Y(i,1) * (a(i,1) - a_old(i,1)) * k11 + Y(j,1) * (a(j,1) - a_old(j,1)) * k12;
+        else
+            if a(j,1) > 0 && a(j,1) < C
+                bnew = b + Ej + Y(i,1) * (a(i,1) - a_old(i,1)) * k12 + Y(j,1) * (a(j,1) - a_old(j,1)) * k22;
+            else
+                b1 = b + Ei + Y(i,1) * (a(i,1) - a_old(i,1)) * k11 + Y(j,1) * (a(j,1) - a_old(j,1)) * k12;
+                b2 = b + Ej + Y(i,1) * (a(i,1) - a_old(i,1)) * k12 + Y(j,1) * (a(j,1) - a_old(j,1)) * k22;
+                bnew = (b1 + b2) / 2;
+            end
+        end
+        delta_b = bnew - b;
+        b = bnew;
+
+        %Update error cache using new Lagrange multipliers 24ai
+
+        t1 = Y(i,1) * (a(i,1)-a_old(i,1));
+        t2 = Y(j,1) * (a(j,1)-a_old(j,1));
+        for k=1:N
+            if 0 < a_old(i,1) && a_old(i,1) < C
+                e(k,1) = e(k,1)+t1 * polynomial(3,X(i,:),X(k,:),dim) + t2 * polynomial(3,X(j,:),X(k,:),dim) - delta_b;
+                e(i,1) = 0;
+                e(j,1) = 0;
+            end
+        end
+        ret = 1;
+    end
+    
+end
+    
+end
diff --git a/SD-VBS/benchmarks/svm/src/matlab/usps_read_partial.m b/SD-VBS/benchmarks/svm/src/matlab/usps_read_partial.m
new file mode 100644
index 0000000..fab2a8f
--- /dev/null
+++ b/SD-VBS/benchmarks/svm/src/matlab/usps_read_partial.m
@@ -0,0 +1,28 @@
+function ret=usps_read_partial(datacell_1, datacell_2, idx, opt,dim, Iterations)
+
+X=datacell_1(1:dim,:);
+if (opt == 1)
+    for i=2:Iterations
+        temp = datacell_2(1:dim,:);
+        X = [X;temp];
+    end
+else
+     for i=1:Iterations
+         if idx==0
+             ADD=zeros(dim,1)+i;
+         else
+             if i~=idx
+                 ADD=ones(dim,1)*-1;
+             else
+                 ADD=ones(dim,1);
+             end
+         end
+         if i==1
+             X=ADD;
+         else
+             X=[X; ADD];
+         end
+     end
+end
+ret = X;
+ 
diff --git a/SD-VBS/benchmarks/texture_synthesis/Makefile b/SD-VBS/benchmarks/texture_synthesis/Makefile
new file mode 100644
index 0000000..60cc0ec
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/Makefile
@@ -0,0 +1,3 @@
+include ../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/Makefile b/SD-VBS/benchmarks/texture_synthesis/data/Makefile
new file mode 100644
index 0000000..ba33d35
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/Makefile
@@ -0,0 +1,3 @@
+include ../../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/cif/1.bmp b/SD-VBS/benchmarks/texture_synthesis/data/cif/1.bmp
new file mode 100644
index 0000000..2488790
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/cif/1.bmp
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/cif/Makefile b/SD-VBS/benchmarks/texture_synthesis/data/cif/Makefile
new file mode 100644
index 0000000..573e7bd
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/cif/Makefile
@@ -0,0 +1,7 @@
+INPUT=cif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=texture_synthesis
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/cif/expected.m b/SD-VBS/benchmarks/texture_synthesis/data/cif/expected.m
new file mode 100644
index 0000000..9ca0b05
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/cif/expected.m
@@ -0,0 +1,192 @@
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diff --git a/SD-VBS/benchmarks/texture_synthesis/data/cif/texture_synthesis b/SD-VBS/benchmarks/texture_synthesis/data/cif/texture_synthesis
new file mode 100755
index 0000000..066bcaa
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/cif/texture_synthesis
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/fullhd/.expected_C.txt.swp b/SD-VBS/benchmarks/texture_synthesis/data/fullhd/.expected_C.txt.swp
new file mode 100644
index 0000000..0120cee
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/fullhd/.expected_C.txt.swp
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/fullhd/1.bmp b/SD-VBS/benchmarks/texture_synthesis/data/fullhd/1.bmp
new file mode 100644
index 0000000..74918c4
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/fullhd/1.bmp
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/fullhd/Makefile b/SD-VBS/benchmarks/texture_synthesis/data/fullhd/Makefile
new file mode 100644
index 0000000..33ec187
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/fullhd/Makefile
@@ -0,0 +1,7 @@
+INPUT=fullhd
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=texture_synthesis
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/fullhd/texture_synthesis b/SD-VBS/benchmarks/texture_synthesis/data/fullhd/texture_synthesis
new file mode 100755
index 0000000..009b9ae
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/fullhd/texture_synthesis
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/qcif/1.bmp b/SD-VBS/benchmarks/texture_synthesis/data/qcif/1.bmp
new file mode 100644
index 0000000..407d03b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/qcif/1.bmp
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/qcif/Makefile b/SD-VBS/benchmarks/texture_synthesis/data/qcif/Makefile
new file mode 100644
index 0000000..0269ca7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/qcif/Makefile
@@ -0,0 +1,7 @@
+INPUT=qcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=texture_synthesis
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/qcif/expected.m b/SD-VBS/benchmarks/texture_synthesis/data/qcif/expected.m
new file mode 100644
index 0000000..9ca0b05
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/qcif/expected.m
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diff --git a/SD-VBS/benchmarks/texture_synthesis/data/qcif/texture_synthesis b/SD-VBS/benchmarks/texture_synthesis/data/qcif/texture_synthesis
new file mode 100755
index 0000000..7eb8bf7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/qcif/texture_synthesis
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sim/1.bmp b/SD-VBS/benchmarks/texture_synthesis/data/sim/1.bmp
new file mode 100644
index 0000000..46f3539
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sim/1.bmp
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sim/Makefile b/SD-VBS/benchmarks/texture_synthesis/data/sim/Makefile
new file mode 100644
index 0000000..94222e7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sim/Makefile
@@ -0,0 +1,6 @@
+INPUT=sim
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=texture_synthesis
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sim/expected.m b/SD-VBS/benchmarks/texture_synthesis/data/sim/expected.m
new file mode 100644
index 0000000..d17b3c6
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sim/expected.m
@@ -0,0 +1,32 @@
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diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sim/texture_synthesis b/SD-VBS/benchmarks/texture_synthesis/data/sim/texture_synthesis
new file mode 100755
index 0000000..53ca033
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sim/texture_synthesis
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/1.bmp b/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/1.bmp
new file mode 100644
index 0000000..4be8889
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/1.bmp
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/Makefile b/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/Makefile
new file mode 100644
index 0000000..3a56abd
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/Makefile
@@ -0,0 +1,6 @@
+INPUT=sim_fast
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=texture_synthesis
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/expected.m b/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/expected.m
new file mode 100644
index 0000000..445bae4
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/expected.m
@@ -0,0 +1,16 @@
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diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/texture_synthesis b/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/texture_synthesis
new file mode 100755
index 0000000..da8ff88
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sim_fast/texture_synthesis
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sqcif/1.bmp b/SD-VBS/benchmarks/texture_synthesis/data/sqcif/1.bmp
new file mode 100644
index 0000000..81ec8ad
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sqcif/1.bmp
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sqcif/Makefile b/SD-VBS/benchmarks/texture_synthesis/data/sqcif/Makefile
new file mode 100644
index 0000000..01f5b98
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sqcif/Makefile
@@ -0,0 +1,6 @@
+INPUT=sqcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=texture_synthesis
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sqcif/expected.m b/SD-VBS/benchmarks/texture_synthesis/data/sqcif/expected.m
new file mode 100644
index 0000000..9ca0b05
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sqcif/expected.m
@@ -0,0 +1,192 @@
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diff --git a/SD-VBS/benchmarks/texture_synthesis/data/sqcif/texture_synthesis b/SD-VBS/benchmarks/texture_synthesis/data/sqcif/texture_synthesis
new file mode 100755
index 0000000..ead6019
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/sqcif/texture_synthesis
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/test/1.bmp b/SD-VBS/benchmarks/texture_synthesis/data/test/1.bmp
new file mode 100644
index 0000000..6dba615
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/test/1.bmp
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/test/Makefile b/SD-VBS/benchmarks/texture_synthesis/data/test/Makefile
new file mode 100644
index 0000000..e2861e5
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/test/Makefile
@@ -0,0 +1,5 @@
+INPUT=test
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=texture_synthesis
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/test/expected.m b/SD-VBS/benchmarks/texture_synthesis/data/test/expected.m
new file mode 100644
index 0000000..445bae4
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/test/expected.m
@@ -0,0 +1,16 @@
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      251.681241      159.000000      89.975613       67.000000       73.000000       95.096934       171.000000      256.221086      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      250.509668      166.000000      96.804041       66.000000       61.000000       84.854293       168.000000      255.049513      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      250.216775      166.500000      88.268507       53.000000       45.000000       78.879419       169.500000      254.317280      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      252.413474      177.000000      98.511147       58.000000       42.000000       90.829167       188.500000      258.124892      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      254.024387      176.500000      95.950487       57.000000       42.000000       92.536274       191.500000      259.442911      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      253.145707      164.500000      77.172313       44.000000       41.000000       95.950487       194.000000      261.639610      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      251.388348      167.500000      78.879419       36.000000       40.000000       102.778914      201.500000      263.104076      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      251.095454      185.500000      95.950487       36.000000       35.000000       85.707846       177.000000      255.488853      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      251.534794      168.500000      79.732973       48.000000       43.000000       82.293633       176.500000      258.857125      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      250.509668      159.500000      71.197439       45.000000       50.000000       78.025866       173.000000      260.468037      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      251.095454      160.500000      74.611652       63.000000       63.000000       88.268507       167.500000      252.267027      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      253.585047      177.000000      140.335263      132.000000      109.000000      130.946176      194.500000      255.928193      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      258.710678      232.500000      185.573593      135.000000      110.000000      151.431458      219.500000      263.104076      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      260.028698      240.000000      165.088312      99.000000       101.000000      151.431458      217.000000      265.593669      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      255.928193      203.000000      132.653283      101.000000      122.000000      152.285011      202.500000      263.689863      
+288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      288.000000      252.267027      187.000000      124.971302      124.000000      145.000000      158.259885      201.000000      262.518290      
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/test/texture_synthesis b/SD-VBS/benchmarks/texture_synthesis/data/test/texture_synthesis
new file mode 100755
index 0000000..8c62aaa
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/test/texture_synthesis
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/vga/1.bmp b/SD-VBS/benchmarks/texture_synthesis/data/vga/1.bmp
new file mode 100644
index 0000000..b5e5100
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/vga/1.bmp
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/vga/Makefile b/SD-VBS/benchmarks/texture_synthesis/data/vga/Makefile
new file mode 100644
index 0000000..39622f9
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/vga/Makefile
@@ -0,0 +1,7 @@
+INPUT=vga
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=texture_synthesis
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/data/vga/texture_synthesis b/SD-VBS/benchmarks/texture_synthesis/data/vga/texture_synthesis
new file mode 100755
index 0000000..d593fa8
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/data/vga/texture_synthesis
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd
new file mode 100755
index 0000000..e3b1f28
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd.c b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd.c
new file mode 100755
index 0000000..9649dda
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd.c
@@ -0,0 +1,52 @@
+/* 
+RES = innerProd(MAT);
+  Computes mat'*mat  
+  Odelia Schwartz, 8/97.
+*/
+
+#define V4_COMPAT
+#include <mex.h>  
+
+#include <stdio.h>
+#include <ctype.h>
+#include <math.h>
+#include <strings.h>
+#include <stdlib.h>
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 Matrix *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 Matrix *prhs[]     /* Matrices on rhs */
+                 )
+{
+   register double *res, *mat, tmp;
+   register int len, wid, i, k, j, jlen, ilen, imat, jmat;
+   Matrix *arg;
+   
+   /* get matrix input argument */
+   /* should be matrix in which num rows >= num columns */
+   arg=prhs[0];                     
+   mat= mxGetPr(arg);
+   len = (int) mxGetM(arg);
+   wid = (int) mxGetN(arg);
+   if ( wid > len )
+     printf("innerProd: Warning: width %d is greater than length %d.\n",wid,len); 
+   plhs[0] = (Matrix *) mxCreateFull(wid,wid,REAL);
+   if (plhs[0] == NULL) 
+     mexErrMsgTxt(sprintf("Error allocating %dx%d result matrix",wid,wid));
+   res = mxGetPr(plhs[0]);
+
+   for(i=0, ilen=0; i<wid; i++, ilen+=len)
+     {
+      for(j=i, jlen=ilen; j<wid; j++, jlen+=len)
+         {
+            tmp = 0.0;
+            for(k=0, imat=ilen, jmat=jlen; k<len; k++, imat++, jmat++)
+              tmp += mat[imat]*mat[jmat];
+            res[i*wid+j] = tmp;
+            res[j*wid+i] = tmp;
+         }
+   }
+   return;
+
+}
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd.ctf b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd.ctf
new file mode 100755
index 0000000..c6bf079
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd.ctf
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd.prj b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd.prj
new file mode 100755
index 0000000..deba3f8
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd.prj
@@ -0,0 +1,233 @@
+<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
+
+<project>
+
+  <MATLABPath>
+    <Directory>/u/kvs/VisionBenchmark/texture_synthesis/src</Directory>
+    <Directory>/pkg/matlab/toolbox/compiler/deploy</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/general</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/ops</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/lang</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/elmat</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/elfun</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/specfun</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/matfun</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/datafun</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/polyfun</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/funfun</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/sparfun</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/scribe</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/graph2d</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/graph3d</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/specgraph</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/graphics</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/uitools</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/strfun</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/imagesci</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/iofun</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/audiovideo</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/timefun</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/datatypes</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/verctrl</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/codetools</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/helptools</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/demos</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/timeseries</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/hds</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/guide</Directory>
+    <Directory>/pkg/matlab/toolbox/matlab/plottools</Directory>
+    <Directory>/pkg/matlab/toolbox/local</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/controllib</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/simulink</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/blocks</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/components</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/fixedandfloat</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/fixedandfloat/fxpdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/fixedandfloat/obsolete</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/simdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/simdemos/aerospace</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/simdemos/automotive</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/simdemos/simfeatures</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/simdemos/simgeneral</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/dee</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/dastudio</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/glue</Directory>
+    <Directory>/pkg/matlab/toolbox/stateflow/stateflow</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/rtw</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/simulink/modeladvisor</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/simulink/modeladvisor/fixpt</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/simulink/MPlayIO</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/simulink/dataobjectwizard</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/fixedpointlib</Directory>
+    <Directory>/pkg/matlab/toolbox/simulink/dataimportexport</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/hdlshared</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/rtwdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/rtwdemos/rsimdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/targets/asap2/asap2</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/targets/asap2/asap2/user</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/targets/common/can/blocks</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/targets/common/configuration/resource</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/targets/common/tgtcommon</Directory>
+    <Directory>/pkg/matlab/toolbox/stateflow/sfdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/stateflow/coder</Directory>
+    <Directory>/pkg/matlab/toolbox/bioinfo/bioinfo</Directory>
+    <Directory>/pkg/matlab/toolbox/bioinfo/biolearning</Directory>
+    <Directory>/pkg/matlab/toolbox/bioinfo/microarray</Directory>
+    <Directory>/pkg/matlab/toolbox/bioinfo/mass_spec</Directory>
+    <Directory>/pkg/matlab/toolbox/bioinfo/proteins</Directory>
+    <Directory>/pkg/matlab/toolbox/bioinfo/biomatrices</Directory>
+    <Directory>/pkg/matlab/toolbox/bioinfo/biodemos</Directory>
+    <Directory>/pkg/matlab/toolbox/bioinfo/graphtheory</Directory>
+    <Directory>/pkg/matlab/toolbox/commblks/commblks</Directory>
+    <Directory>/pkg/matlab/toolbox/commblks/commmasks</Directory>
+    <Directory>/pkg/matlab/toolbox/commblks/commmex</Directory>
+    <Directory>/pkg/matlab/toolbox/commblks/commblksdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/commblks/commblksobsolete/v3</Directory>
+    <Directory>/pkg/matlab/toolbox/commblks/commblksobsolete/v2p5</Directory>
+    <Directory>/pkg/matlab/toolbox/commblks/commblksobsolete/v2</Directory>
+    <Directory>/pkg/matlab/toolbox/comm/comm</Directory>
+    <Directory>/pkg/matlab/toolbox/comm/commdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/comm/commdemos/commdocdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/comm/commobsolete</Directory>
+    <Directory>/pkg/matlab/toolbox/compiler</Directory>
+    <Directory>/pkg/matlab/toolbox/control/control</Directory>
+    <Directory>/pkg/matlab/toolbox/control/ctrlguis</Directory>
+    <Directory>/pkg/matlab/toolbox/control/ctrlobsolete</Directory>
+    <Directory>/pkg/matlab/toolbox/control/ctrlutil</Directory>
+    <Directory>/pkg/matlab/toolbox/control/ctrldemos</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/slcontrollib</Directory>
+    <Directory>/pkg/matlab/toolbox/curvefit/curvefit</Directory>
+    <Directory>/pkg/matlab/toolbox/curvefit/cftoolgui</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/optimlib</Directory>
+    <Directory>/pkg/matlab/toolbox/database/database</Directory>
+    <Directory>/pkg/matlab/toolbox/database/dbdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/database/vqb</Directory>
+    <Directory>/pkg/matlab/toolbox/dspblks/dspblks</Directory>
+    <Directory>/pkg/matlab/toolbox/dspblks/dspmasks</Directory>
+    <Directory>/pkg/matlab/toolbox/dspblks/dspmex</Directory>
+    <Directory>/pkg/matlab/toolbox/dspblks/dspdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/filterdesignlib</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/targets/ecoder</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/targets/ecoder/ecoderdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/targets/mpt</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/targets/mpt/mpt</Directory>
+    <Directory>/pkg/matlab/toolbox/rtw/targets/mpt/user_specific</Directory>
+    <Directory>/pkg/matlab/toolbox/fixedpoint/fixedpoint</Directory>
+    <Directory>/pkg/matlab/toolbox/fixedpoint/fidemos</Directory>
+    <Directory>/pkg/matlab/toolbox/fixedpoint/fimex</Directory>
+    <Directory>/pkg/matlab/toolbox/fixpoint</Directory>
+    <Directory>/pkg/matlab/toolbox/gads</Directory>
+    <Directory>/pkg/matlab/toolbox/gads/gads</Directory>
+    <Directory>/pkg/matlab/toolbox/gads/gadsdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/ident/ident</Directory>
+    <Directory>/pkg/matlab/toolbox/ident/idobsolete</Directory>
+    <Directory>/pkg/matlab/toolbox/ident/idguis</Directory>
+    <Directory>/pkg/matlab/toolbox/ident/idutils</Directory>
+    <Directory>/pkg/matlab/toolbox/ident/iddemos</Directory>
+    <Directory>/pkg/matlab/toolbox/ident/idhelp</Directory>
+    <Directory>/pkg/matlab/toolbox/images/images</Directory>
+    <Directory>/pkg/matlab/toolbox/images/imuitools</Directory>
+    <Directory>/pkg/matlab/toolbox/images/imdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/images/iptutils</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/imageslib</Directory>
+    <Directory>/pkg/matlab/toolbox/images/medformats</Directory>
+    <Directory>/pkg/matlab/toolbox/instrument/instrument</Directory>
+    <Directory>/pkg/matlab/toolbox/instrument/instrumentdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/map/map</Directory>
+    <Directory>/pkg/matlab/toolbox/map/mapdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/map/mapdisp</Directory>
+    <Directory>/pkg/matlab/toolbox/map/mapformats</Directory>
+    <Directory>/pkg/matlab/toolbox/map/mapproj</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/mapgeodesy</Directory>
+    <Directory>/pkg/matlab/toolbox/slvnv/simcoverage</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nncontrol</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nndemos</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nnanalyze</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nncustom</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nndistance</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nnformat</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nninit</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nnlearn</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nnnetinput</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nnnetwork</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nnperformance</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nnplot</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nnprocess</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nnsearch</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nntopology</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nntrain</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nntransfer</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnet/nnweight</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnguis</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnguis/nftool</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnguis/nntool</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnobsolete</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnresource</Directory>
+    <Directory>/pkg/matlab/toolbox/nnet/nnutils</Directory>
+    <Directory>/pkg/matlab/toolbox/optim</Directory>
+    <Directory>/pkg/matlab/toolbox/pde</Directory>
+    <Directory>/pkg/matlab/toolbox/robust/robust</Directory>
+    <Directory>/pkg/matlab/toolbox/robust/rctlmi</Directory>
+    <Directory>/pkg/matlab/toolbox/robust/rctutil</Directory>
+    <Directory>/pkg/matlab/toolbox/robust/rctdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/robust/rctobsolete/robust</Directory>
+    <Directory>/pkg/matlab/toolbox/robust/rctobsolete/lmi</Directory>
+    <Directory>/pkg/matlab/toolbox/robust/rctobsolete/mutools/commands</Directory>
+    <Directory>/pkg/matlab/toolbox/robust/rctobsolete/mutools/subs</Directory>
+    <Directory>/pkg/matlab/toolbox/signal/signal</Directory>
+    <Directory>/pkg/matlab/toolbox/signal/sigtools</Directory>
+    <Directory>/pkg/matlab/toolbox/signal/sptoolgui</Directory>
+    <Directory>/pkg/matlab/toolbox/signal/sigdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/shared/spcuilib</Directory>
+    <Directory>/pkg/matlab/toolbox/slcontrol/slcontrol</Directory>
+    <Directory>/pkg/matlab/toolbox/slcontrol/slctrlguis</Directory>
+    <Directory>/pkg/matlab/toolbox/slcontrol/slctrlutil</Directory>
+    <Directory>/pkg/matlab/toolbox/slcontrol/slctrldemos</Directory>
+    <Directory>/pkg/matlab/toolbox/splines</Directory>
+    <Directory>/pkg/matlab/toolbox/stats</Directory>
+    <Directory>/pkg/matlab/toolbox/symbolic</Directory>
+    <Directory>/pkg/matlab/toolbox/vipblks/vipblks</Directory>
+    <Directory>/pkg/matlab/toolbox/vipblks/vipmasks</Directory>
+    <Directory>/pkg/matlab/toolbox/vipblks/vipmex</Directory>
+    <Directory>/pkg/matlab/toolbox/vipblks/vipdemos</Directory>
+    <Directory>/pkg/matlab/toolbox/wavelet/wavelet</Directory>
+    <Directory>/pkg/matlab/toolbox/wavelet/wmultisig1d</Directory>
+    <Directory>/pkg/matlab/toolbox/wavelet/wavedemo</Directory>
+    <Directory>/pkg/matlab/work</Directory>
+    <Directory>/pkg/matlab/toolbox/vr/vr</Directory>
+    <Directory>/pkg/matlab/toolbox/vr/vrdemos</Directory>
+  </MATLABPath>
+
+  <MCCProperties>
+    <output/>
+    <wrapper>
+      <type>main</type>
+      <component_name>innerProd</component_name>
+    </wrapper>
+    <link>exe</link>
+    <create_vb_wrapper>false</create_vb_wrapper>
+    <intermediate_dir>../MEX</intermediate_dir>
+    <output_dir>../MEX</output_dir>
+    <generate_code_only>false</generate_code_only>
+    <verbose>false</verbose>
+    <MCR_runtime_options>
+      <share_mcr>false</share_mcr>
+    </MCR_runtime_options>
+    <options_file/>
+    <toolboxes_on_path shortcut="all"/>
+    <debug>false</debug>
+    <warning shortcut="default"/>
+    <license_file/>
+  </MCCProperties>
+
+  <file_info>
+    <category name="Main function">
+      <file>/u/kvs/VisionBenchmark/texture_synthesis/src/innerProd.m</file>
+    </category>
+    <category name="Other files"/>
+    <category name="C/C++ files"/>
+  </file_info>
+
+</project>
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd_main.c b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd_main.c
new file mode 100755
index 0000000..3c828de
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd_main.c
@@ -0,0 +1,103 @@
+/*
+ * MATLAB Compiler: 4.4 (R2006a)
+ * Date: Thu Jul 24 17:19:07 2008
+ * Arguments: "-B" "macro_default" "-m" "-W" "main" "-T" "link:exe" "-d"
+ * "../MEX" "innerProd.m" 
+ */
+
+#include <stdio.h>
+#include "mclmcr.h"
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+extern mclComponentData __MCC_innerProd_component_data;
+
+#ifdef __cplusplus
+}
+#endif
+
+static HMCRINSTANCE _mcr_inst = NULL;
+
+
+static int mclDefaultPrintHandler(const char *s)
+{
+    return fwrite(s, sizeof(char), strlen(s), stdout);
+}
+
+static int mclDefaultErrorHandler(const char *s)
+{
+    int written = 0, len = 0;
+    len = strlen(s);
+    written = fwrite(s, sizeof(char), len, stderr);
+    if (len > 0 && s[ len-1 ] != '\n')
+        written += fwrite("\n", sizeof(char), 1, stderr);
+    return written;
+}
+
+
+/* This symbol is defined in shared libraries. Define it here
+ * (to nothing) in case this isn't a shared library. 
+ */
+#ifndef LIB_innerProd_C_API 
+#define LIB_innerProd_C_API /* No special import/export declaration */
+#endif
+
+LIB_innerProd_C_API 
+bool MW_CALL_CONV innerProdInitializeWithHandlers(
+    mclOutputHandlerFcn error_handler,
+    mclOutputHandlerFcn print_handler
+)
+{
+    if (_mcr_inst != NULL)
+        return true;
+    if (!mclmcrInitialize())
+        return false;
+    if (!mclInitializeComponentInstance(&_mcr_inst,
+                                        &__MCC_innerProd_component_data,
+                                        true, NoObjectType, ExeTarget,
+                                        error_handler, print_handler))
+        return false;
+    return true;
+}
+
+LIB_innerProd_C_API 
+bool MW_CALL_CONV innerProdInitialize(void)
+{
+    return innerProdInitializeWithHandlers(mclDefaultErrorHandler,
+                                           mclDefaultPrintHandler);
+}
+
+LIB_innerProd_C_API 
+void MW_CALL_CONV innerProdTerminate(void)
+{
+    if (_mcr_inst != NULL)
+        mclTerminateInstance(&_mcr_inst);
+}
+
+int run_main(int argc, const char **argv)
+{
+    int _retval;
+    /* Generate and populate the path_to_component. */
+    char path_to_component[(PATH_MAX*2)+1];
+    separatePathName(argv[0], path_to_component, (PATH_MAX*2)+1);
+    __MCC_innerProd_component_data.path_to_component = path_to_component; 
+    if (!innerProdInitialize()) {
+        return -1;
+    }
+    _retval = mclMain(_mcr_inst, argc, argv, "innerProd", 1);
+    if (_retval == 0 /* no error */) mclWaitForFiguresToDie(NULL);
+    innerProdTerminate();
+    mclTerminateApplication();
+    return _retval;
+}
+
+int main(int argc, const char **argv)
+{
+    if (!mclInitializeApplication(
+        __MCC_innerProd_component_data.runtime_options,
+        __MCC_innerProd_component_data.runtime_option_count))
+        return 0;
+    
+    return mclRunMain(run_main, argc, argv);
+}
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd_mcc_component_data.c b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd_mcc_component_data.c
new file mode 100755
index 0000000..df204ee
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/MEX/innerProd_mcc_component_data.c
@@ -0,0 +1,151 @@
+/*
+ * MATLAB Compiler: 4.4 (R2006a)
+ * Date: Thu Jul 24 17:19:07 2008
+ * Arguments: "-B" "macro_default" "-m" "-W" "main" "-T" "link:exe" "-d"
+ * "../MEX" "innerProd.m" 
+ */
+
+#include "mclmcr.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+const unsigned char __MCC_innerProd_session_key[] = {
+        'B', 'C', 'C', '8', 'A', 'E', 'C', 'F', '0', '7', '5', '2', 'D', 'F',
+        'F', '9', '4', '2', '0', 'B', '6', 'F', '5', 'B', 'E', 'A', 'E', '4',
+        'C', '2', 'F', '5', '4', 'D', '1', '4', '6', '3', 'B', 'A', '5', '1',
+        'D', '8', '3', '7', 'F', '5', '4', '6', 'C', '1', 'D', 'B', '9', '3',
+        'C', 'D', 'A', 'D', 'F', '3', '5', 'F', '5', 'A', '2', 'D', '9', 'A',
+        '4', '4', '6', 'D', 'C', '5', '3', '7', '7', '5', '7', '2', '3', '0',
+        'E', '2', 'E', '7', '0', 'F', '7', '4', 'B', 'A', '8', 'B', '9', '8',
+        '5', '8', 'D', 'D', '3', '3', '3', '7', '9', 'E', '8', '1', '3', '9',
+        '1', '2', 'A', '6', 'B', '0', '4', '8', 'F', 'D', '9', 'D', '3', '5',
+        '2', '8', '4', '3', '7', '3', '1', 'D', '7', '0', 'E', '0', '0', '3',
+        'D', '9', '7', '3', '0', 'F', '8', '7', '0', 'C', 'A', 'B', '4', '1',
+        'F', '0', '4', '5', 'E', '1', '7', '4', 'C', 'E', '6', 'A', 'C', 'D',
+        'C', '6', 'F', '8', '6', '5', 'F', '5', '1', 'A', '6', '9', 'F', 'E',
+        '7', '9', 'A', '3', 'E', '7', 'C', '6', '2', '3', '7', 'C', 'E', '9',
+        'A', '0', '6', '3', '5', '9', '3', '4', '1', '5', '9', 'D', '9', '2',
+        '4', 'B', '1', '0', '6', '0', 'A', '3', '5', '8', '2', '1', '8', '4',
+        'E', 'B', 'C', 'D', 'B', '6', '4', '7', 'F', 'D', '9', 'A', '3', '3',
+        'D', '0', '1', '5', 'C', '2', '1', 'B', '5', 'C', '1', '5', '9', '3',
+        '0', '4', '6', '1', '\0'};
+
+const unsigned char __MCC_innerProd_public_key[] = {
+        '3', '0', '8', '1', '9', 'D', '3', '0', '0', 'D', '0', '6', '0', '9',
+        '2', 'A', '8', '6', '4', '8', '8', '6', 'F', '7', '0', 'D', '0', '1',
+        '0', '1', '0', '1', '0', '5', '0', '0', '0', '3', '8', '1', '8', 'B',
+        '0', '0', '3', '0', '8', '1', '8', '7', '0', '2', '8', '1', '8', '1',
+        '0', '0', 'C', '4', '9', 'C', 'A', 'C', '3', '4', 'E', 'D', '1', '3',
+        'A', '5', '2', '0', '6', '5', '8', 'F', '6', 'F', '8', 'E', '0', '1',
+        '3', '8', 'C', '4', '3', '1', '5', 'B', '4', '3', '1', '5', '2', '7',
+        '7', 'E', 'D', '3', 'F', '7', 'D', 'A', 'E', '5', '3', '0', '9', '9',
+        'D', 'B', '0', '8', 'E', 'E', '5', '8', '9', 'F', '8', '0', '4', 'D',
+        '4', 'B', '9', '8', '1', '3', '2', '6', 'A', '5', '2', 'C', 'C', 'E',
+        '4', '3', '8', '2', 'E', '9', 'F', '2', 'B', '4', 'D', '0', '8', '5',
+        'E', 'B', '9', '5', '0', 'C', '7', 'A', 'B', '1', '2', 'E', 'D', 'E',
+        '2', 'D', '4', '1', '2', '9', '7', '8', '2', '0', 'E', '6', '3', '7',
+        '7', 'A', '5', 'F', 'E', 'B', '5', '6', '8', '9', 'D', '4', 'E', '6',
+        '0', '3', '2', 'F', '6', '0', 'C', '4', '3', '0', '7', '4', 'A', '0',
+        '4', 'C', '2', '6', 'A', 'B', '7', '2', 'F', '5', '4', 'B', '5', '1',
+        'B', 'B', '4', '6', '0', '5', '7', '8', '7', '8', '5', 'B', '1', '9',
+        '9', '0', '1', '4', '3', '1', '4', 'A', '6', '5', 'F', '0', '9', '0',
+        'B', '6', '1', 'F', 'C', '2', '0', '1', '6', '9', '4', '5', '3', 'B',
+        '5', '8', 'F', 'C', '8', 'B', 'A', '4', '3', 'E', '6', '7', '7', '6',
+        'E', 'B', '7', 'E', 'C', 'D', '3', '1', '7', '8', 'B', '5', '6', 'A',
+        'B', '0', 'F', 'A', '0', '6', 'D', 'D', '6', '4', '9', '6', '7', 'C',
+        'B', '1', '4', '9', 'E', '5', '0', '2', '0', '1', '1', '1', '\0'};
+
+static const char * MCC_innerProd_matlabpath_data[] = 
+    { "innerProd/", "toolbox/compiler/deploy/", "$TOOLBOXMATLABDIR/general/",
+      "$TOOLBOXMATLABDIR/ops/", "$TOOLBOXMATLABDIR/lang/",
+      "$TOOLBOXMATLABDIR/elmat/", "$TOOLBOXMATLABDIR/elfun/",
+      "$TOOLBOXMATLABDIR/specfun/", "$TOOLBOXMATLABDIR/matfun/",
+      "$TOOLBOXMATLABDIR/datafun/", "$TOOLBOXMATLABDIR/polyfun/",
+      "$TOOLBOXMATLABDIR/funfun/", "$TOOLBOXMATLABDIR/sparfun/",
+      "$TOOLBOXMATLABDIR/scribe/", "$TOOLBOXMATLABDIR/graph2d/",
+      "$TOOLBOXMATLABDIR/graph3d/", "$TOOLBOXMATLABDIR/specgraph/",
+      "$TOOLBOXMATLABDIR/graphics/", "$TOOLBOXMATLABDIR/uitools/",
+      "$TOOLBOXMATLABDIR/strfun/", "$TOOLBOXMATLABDIR/imagesci/",
+      "$TOOLBOXMATLABDIR/iofun/", "$TOOLBOXMATLABDIR/audiovideo/",
+      "$TOOLBOXMATLABDIR/timefun/", "$TOOLBOXMATLABDIR/datatypes/",
+      "$TOOLBOXMATLABDIR/verctrl/", "$TOOLBOXMATLABDIR/codetools/",
+      "$TOOLBOXMATLABDIR/helptools/", "$TOOLBOXMATLABDIR/demos/",
+      "$TOOLBOXMATLABDIR/timeseries/", "$TOOLBOXMATLABDIR/hds/",
+      "$TOOLBOXMATLABDIR/guide/", "$TOOLBOXMATLABDIR/plottools/",
+      "toolbox/local/", "toolbox/compiler/", "toolbox/database/database/" };
+
+static const char * MCC_innerProd_classpath_data[] = 
+    { "java/jar/toolbox/database.jar" };
+
+static const char * MCC_innerProd_libpath_data[] = 
+    { "" };
+
+static const char * MCC_innerProd_app_opts_data[] = 
+    { "" };
+
+static const char * MCC_innerProd_run_opts_data[] = 
+    { "" };
+
+static const char * MCC_innerProd_warning_state_data[] = 
+    { "" };
+
+
+mclComponentData __MCC_innerProd_component_data = { 
+
+    /* Public key data */
+    __MCC_innerProd_public_key,
+
+    /* Component name */
+    "innerProd",
+
+    /* Component Root */
+    "",
+
+    /* Application key data */
+    __MCC_innerProd_session_key,
+
+    /* Component's MATLAB Path */
+    MCC_innerProd_matlabpath_data,
+
+    /* Number of directories in the MATLAB Path */
+    36,
+
+    /* Component's Java class path */
+    MCC_innerProd_classpath_data,
+    /* Number of directories in the Java class path */
+    1,
+
+    /* Component's load library path (for extra shared libraries) */
+    MCC_innerProd_libpath_data,
+    /* Number of directories in the load library path */
+    0,
+
+    /* MCR instance-specific runtime options */
+    MCC_innerProd_app_opts_data,
+    /* Number of MCR instance-specific runtime options */
+    0,
+
+    /* MCR global runtime options */
+    MCC_innerProd_run_opts_data,
+    /* Number of MCR global runtime options */
+    0,
+    
+    /* Component preferences directory */
+    "innerProd_EEEFF7AADF2C5D8569D4742763DAC0AB",
+
+    /* MCR warning status data */
+    MCC_innerProd_warning_state_data,
+    /* Number of MCR warning status modifiers */
+    0,
+
+    /* Path to component - evaluated at runtime */
+    NULL
+
+};
+
+#ifdef __cplusplus
+}
+#endif
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/MEX/mccExcludedFiles.log b/SD-VBS/benchmarks/texture_synthesis/src/MEX/mccExcludedFiles.log
new file mode 100755
index 0000000..981940f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/MEX/mccExcludedFiles.log
@@ -0,0 +1,12 @@
+This file contains the list of various toolbox functions that are not 
+included in the CTF file. An error will be thrown if any of these functions
+ are called at run-time. Some of these functions may be from toolboxes 
+that you are not using in your application. The reason for this is that 
+these toolboxes have overloaded some methods that are called by your code. 
+If you know which toolboxes are being used by your code, you can use the -p
+ flag with the -N flag to list these toolboxes explicitly. This will 
+cause MATLAB Compiler to only look for functions in the specified toolbox 
+directories in addition to the MATLAB directories. Refer to the MCC 
+documentation for more information on this.
+
+0 item(s) excluded by M-file compilabilty rules.
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/c/script_texture_synthesis.c b/SD-VBS/benchmarks/texture_synthesis/src/c/script_texture_synthesis.c
new file mode 100644
index 0000000..01ddefd
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/c/script_texture_synthesis.c
@@ -0,0 +1,197 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "texture.h"
+#include <malloc.h>
+#include "extra.h"
+#define TEXTURE_MEM 1<<28
+int WIDTHin,HEIGHTin;
+F2D *target, *result;
+int WIDTH,HEIGHT;
+int localx, localy,targetin=0;
+int *atlas;
+int *xloopin, *yloopin;
+int *xloopout, *yloopout;
+
+int  main(int argc, char **argv)
+{
+    SET_UP
+    mallopt(M_TOP_PAD, TEXTURE_MEM);
+    mallopt(M_MMAP_MAX, 0);
+    params* data;
+    I2D *im;
+    F2D* image;
+    data = malloc(sizeof(params));
+    im = parse_flags(argc, argv);
+    image = fiDeepCopy(im);
+    init_params(data);
+
+    printf("start.\n");
+    for_each_job{
+        create_texture(image, data);
+    }
+    printf("end..\n");
+#ifdef CHECK
+{
+    int ret=0;
+#ifdef GENERATE_OUTPUT
+    fWriteMatrix(result, argv[1]);
+#endif
+    ret = fSelfCheck(result, "expected_C.txt", 1.0);
+    if(ret < 0)
+        printf("Error in Texture Synthesis\n");
+}
+#endif
+    iFreeHandle(im);
+    fFreeHandle(image);
+    free(data);
+    fFreeHandle(target);
+    fFreeHandle(result);
+    free(atlas);
+    WRITE_TO_FILE
+    return 0;
+}
+
+I2D* parse_flags(int argc, char ** argv)
+{
+    int i, tsx,tsy;
+    I2D* image;
+    char fileNm[256];
+
+    printf("Input image: ");
+    scanf("%s", fileNm);
+    image = readImage(fileNm);
+    WIDTHin = image->width;
+    HEIGHTin = image->height;
+
+    localx = 3;
+    localy = 3;
+
+#ifdef test
+    WIDTH = WIDTHin*2;
+    HEIGHT = HEIGHTin*2;
+    localx = 2;
+    localy = 2;
+#endif
+#ifdef sim_fast
+    WIDTH = WIDTHin*2;
+    HEIGHT = HEIGHTin*2;
+    localx = 3;
+    localy = 3;
+#endif
+#ifdef sim
+    WIDTH = WIDTHin*3;
+    HEIGHT = HEIGHTin*3;
+    localx = 2;
+    localy = 2;
+#endif
+#ifdef sqcif
+    WIDTH = WIDTHin*6;
+    HEIGHT = HEIGHTin*6;
+    localx = 2;
+    localy = 2;
+#endif
+#ifdef qcif
+    WIDTH = WIDTHin*10;
+    HEIGHT = HEIGHTin*10;
+    localx = 2;
+    localy = 2;
+#endif
+#ifdef cif
+    WIDTH = WIDTHin*10;
+    HEIGHT = HEIGHTin*10;
+    localx = 3;
+    localy = 3;
+#endif
+#ifdef vga
+    WIDTH = WIDTHin*20;
+    HEIGHT = HEIGHTin*20;
+    localx = 3;
+    localy = 3;
+#endif
+#ifdef fullhd
+    WIDTH = WIDTHin*20;
+    HEIGHT = HEIGHTin*20;
+    localx = 15;
+    localy = 15;
+#endif
+#ifdef wuxga
+    WIDTH = WIDTHin*20;
+    HEIGHT = HEIGHTin*20;
+    localx = 5;
+    localy = 5;
+#endif
+    printf("Input size\t\t- (%dx%d)\n", HEIGHTin, WIDTHin);
+
+//    xloopin = malloc(2*WIDTHin*sizeof(int));
+//    yloopin = malloc(2*HEIGHTin*sizeof(int));
+//
+//    for(i=-WIDTHin/2;i<WIDTHin+WIDTHin/2;i++)
+//    {
+//        arrayref(xloopin,i+WIDTHin/2) = (WIDTHin+i)%WIDTHin;
+//    }
+//
+//    for(i=-HEIGHTin/2;i<HEIGHTin+HEIGHTin/2;i++)
+//    {
+//        arrayref(yloopin,i+HEIGHTin/2) = (HEIGHTin+i)%HEIGHTin;
+//    }
+//    xloopin += WIDTHin/2; yloopin += HEIGHTin/2;
+
+    result = fMallocHandle(1,HEIGHT*WIDTH);
+    target = fMallocHandle(1, WIDTH*HEIGHT);
+ 
+    atlas = malloc(2*WIDTH*HEIGHT*sizeof(int));
+    xloopout = malloc(2*WIDTH*sizeof(int));
+    yloopout = malloc(2*HEIGHT*sizeof(int));
+    
+    for(i=-WIDTH/2;i<WIDTH+WIDTH/2;i++)
+    {
+        arrayref(xloopout,i+WIDTH/2) = (WIDTH+i)%WIDTH;
+    }
+    for(i=-HEIGHT/2;i<HEIGHT+HEIGHT/2;i++)
+    {
+        arrayref(yloopout,i+HEIGHT/2) = (HEIGHT+i)%HEIGHT;
+    }
+    xloopout += WIDTH/2; yloopout += HEIGHT/2;
+
+    if (result == NULL)
+    {
+        printf("Can't allocate %dx%d image. Exiting.\n",WIDTH,HEIGHT);
+        exit(1);
+    }
+
+    return image;
+}
+
+void init_params(params *data)
+{
+    int i,j;
+    data->localx = localx; data->localy = localy;
+    data->widthin = WIDTHin; data->widthout = WIDTH;
+    data->heightin = HEIGHTin; data->heightout = HEIGHT;
+
+
+    if(!targetin)
+    {
+        for(i=0;i<data->heightout;i++)
+        {
+            for(j=0;j<data->widthout;j++)
+            {
+                asubsref(target,a(j,i,data->widthout)+R) = 1.0;
+//                asubsref(target,a(j,i,data->widthout)+G) = 1.0;
+//                asubsref(target,a(j,i,data->widthout)+B) = 1.0;
+            }
+        }
+    }
+ 
+    for(i=0;i<data->heightout;i++)
+    {
+        for(j=0;j<data->widthout;j++)
+        {
+            asubsref(result,a(j,i,data->widthout)+R)  = 1.0;
+//            asubsref(result,a(j,i,data->widthout)+G)  = 1.0;
+//            asubsref(result,a(j,i,data->widthout)+B)  = 1.0;
+        }
+    }
+}
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/c/texture.c b/SD-VBS/benchmarks/texture_synthesis/src/c/texture.c
new file mode 100644
index 0000000..fb0f1ae
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/c/texture.c
@@ -0,0 +1,396 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "texture.h"
+#include <math.h>
+
+int vrstartx, vrfinishx, vrstarty, vrfinishy;
+extern params data;
+int* candlistx, *candlisty;
+int *atlas;
+int anotherpass=0,maxcand = 40;
+F2D *target, *result;
+int *xloopout, *yloopout;
+int *xloopin, *yloopin;
+
+double compare_rest(F2D *image,int x, int y, F2D *tar,int x1, int y1, params* data);
+
+/*********************************
+This is the main texture synthesis function. Called just once
+from main to generate image from 'image' into 'result'.
+Synthesis parameters (image and neighborhood sizes) are in global
+'data-> structure.
+*********************************/
+
+//void create_texture(F2D *image, F2D *result, params *data)
+void create_texture(F2D *image, params *data)
+{
+
+    int i,j,k, ncand, bestx,besty;
+    double diff,curdiff;
+    int tsx,tsy;
+    srand48(1);
+    candlistx = (int*)malloc(sizeof(int)*(data->localx*(data->localy+1)+1));
+    candlisty = (int*)malloc(sizeof(int)*(data->localx*(data->localy+1)+1));
+//    if(!anotherpass) init(result, image,data);
+    if(!anotherpass) init(image,data);
+    
+    for(i=0;i<data->heightout-data->localy/2;i++)
+    {
+        for(j=0;j<data->widthout;j++)
+        {
+            // First, create a list of candidates for particular pixel.
+            if(anotherpass) ncand = create_all_candidates(j,i, data);
+            else  ncand = create_candidates(j,i, data);
+
+            // If there are multiple candidates, choose the best based on L_2 norm
+
+            if(ncand > 1)
+            {
+                diff = 1e10;
+                for(k=0;k<ncand;k++)
+                {
+                    curdiff = compare_neighb(image, arrayref(candlistx,k),arrayref(candlisty,k),result,j,i, data);
+                    curdiff += compare_rest(image,arrayref(candlistx,k),arrayref(candlisty,k),target,j,i,data);
+                    if(curdiff < diff)
+                    {
+                        diff = curdiff;
+                        bestx = arrayref(candlistx,k);
+                        besty = arrayref(candlisty,k);
+                    }
+                }
+            }
+            else
+            {
+                bestx = arrayref(candlistx,0);
+                besty = arrayref(candlisty,0);
+            }
+
+            // Copy the best candidate to the output image and record its position
+            // in the atlas (atlas is used to create candidates)
+
+            asubsref(result,a(j,i,data->widthout)+R) = asubsref(image,a(bestx,besty,data->widthin)+R);
+//            asubsref(result,a(j,i,data->widthout)+G) = asubsref(image,a(bestx,besty,data->widthin)+G);
+//            asubsref(result,a(j,i,data->widthout)+B) = asubsref(image,a(bestx,besty,data->widthin)+B);
+            arrayref(atlas,aa(j,i)) = bestx;
+            arrayref(atlas,aa(j,i)+1) = besty;
+        }
+    }
+    
+    // Use full neighborhoods for the last few rows. This is a small
+    // fraction of total area - can be ignored for optimization purposes.
+
+    for(;i<data->heightout;i++)
+    {
+        for(j=0;j<data->widthout;j++)
+        {
+            ncand = create_all_candidates(j,i,data);
+            if(ncand > 1)
+            {
+                diff = 1e10;
+                for(k=0;k<ncand;k++)
+                {
+                    curdiff = compare_full_neighb(image, arrayref(candlistx,k),arrayref(candlisty,k),result,j,i, data);
+                    if(curdiff < diff)
+                    {
+                        diff = curdiff;
+                        bestx = arrayref(candlistx,k);
+                        besty = arrayref(candlisty,k);
+                    }
+                }
+            }
+            else
+            {
+                bestx = arrayref(candlistx,0);
+                besty = arrayref(candlisty,0);
+            }
+   
+            asubsref(result,a(j,i,data->widthout)+R) = asubsref(image,a(bestx,besty,data->widthin)+R);
+//            asubsref(result,a(j,i,data->widthout)+G) = asubsref(image,a(bestx,besty,data->widthin)+G);
+//            asubsref(result,a(j,i,data->widthout)+B) = asubsref(image,a(bestx,besty,data->widthin)+B);
+            arrayref(atlas,aa(j,i)) = bestx;
+            arrayref(atlas,aa(j,i)+1) = besty;
+        }
+    }
+
+    /*********************************
+    End of main texture synthesis loop
+    *********************************/
+
+    for(i=0;i<data->localy/2;i++)
+    {
+        for(j=0;j<data->widthout;j++)
+        {
+            ncand = create_all_candidates(j,i,data);
+            if(ncand > 1)
+            {
+                diff = 1e10;
+                for(k=0;k<ncand;k++)
+                {
+                    curdiff = compare_full_neighb(image,arrayref(candlistx,k),arrayref(candlisty,k),result,j,i, data);
+                    if(curdiff < diff)
+                    {
+                        diff = curdiff;
+                        bestx = arrayref(candlistx,k);
+                        besty = arrayref(candlisty,k);
+                    }
+                }
+            }
+            else
+            {
+                bestx = arrayref(candlistx,0);
+                besty = arrayref(candlisty,0);
+            }
+   
+            asubsref(result,a(j,i,data->widthout)+R) = asubsref(image,a(bestx,besty,data->widthin)+R);
+//            asubsref(result,a(j,i,data->widthout)+G) = asubsref(image,a(bestx,besty,data->widthin)+G);
+//            asubsref(result,a(j,i,data->widthout)+B) = asubsref(image,a(bestx,besty,data->widthin)+B);
+            arrayref(atlas,aa(j,i)) = bestx;
+            arrayref(atlas,aa(j,i)+1) = besty;
+        }
+    }
+}
+
+// Creates a list of valid candidates for given pixel using only L-shaped causal area
+
+int create_candidates(int x,int y, params* data)
+{
+    int address,i,j,k,n = 0;
+    for(i=0;i<=data->localy/2;i++)
+    {
+        for(j=-data->localx/2;j<=data->localx/2;j++)
+        {
+            if(i==0 && j>=0) 
+                continue;
+            address = aa( arrayref(xloopout,x+j), arrayref(yloopout,y-i) );
+            arrayref(candlistx,n) = arrayref(atlas,address) - j;
+            arrayref(candlisty,n) = arrayref(atlas,address+1) + i;
+
+            if( arrayref(candlistx,n) >= vrfinishx || arrayref(candlistx,n) < vrstartx) 
+            {
+                arrayref(candlistx,n) = vrstartx + (int)(drand48()*(vrfinishx-vrstartx));
+                arrayref(candlisty,n) = vrstarty + (int)(drand48()*(vrfinishy-vrstarty));
+                n++;
+                continue;
+            }
+
+            if( arrayref(candlisty,n) >= vrfinishy )
+            {
+                arrayref(candlisty,n) = vrstarty + (int)(drand48()*(vrfinishy-vrstarty));
+                arrayref(candlistx,n) = vrstartx + (int)(drand48()*(vrfinishx-vrstartx));
+                n++;
+                continue;
+            }
+            
+            for(k=0;k<n;k++)
+            {
+                if( arrayref(candlistx,n) == arrayref(candlistx,k) && arrayref(candlisty,n) == arrayref(candlisty,k))
+                { 
+                    n--; 
+                    break;
+                }
+            }
+            n++;
+        }
+    }
+        
+    return n;
+}
+
+// Created a list of candidates using the complete square around the pixel
+
+int create_all_candidates(int x,int y, params* data)
+{
+    int address,i,j,k,n = 0;
+    for(i=-data->localy/2;i<=data->localy/2;i++)
+    {
+        for(j=-data->localx/2;j<=data->localx/2;j++)
+        {
+            if(i==0 && j>=0) 
+                continue;
+//            printf("Entering = (%d,%d)\n", i,j);
+            address = aa( arrayref(xloopout,x+j), arrayref(yloopout,y-i) );
+            arrayref(candlistx,n) = arrayref(atlas,address)-j;
+            arrayref(candlisty,n) = arrayref(atlas,address+1)+i;
+
+            if( arrayref(candlistx,n) >= vrfinishx || arrayref(candlistx,n) < vrstartx) 
+            {
+                arrayref(candlistx,n) = vrstartx + (int)(drand48()*(vrfinishx-vrstartx));
+                arrayref(candlisty,n) = vrstarty + (int)(drand48()*(vrfinishy-vrstarty));
+                n++;
+//                printf("1: (%d,%d)\t%d\n", i,j,n);
+                continue;
+            }
+
+            if( arrayref(candlisty,n) >= vrfinishy || arrayref(candlisty,n) < vrstarty)
+            {
+                arrayref(candlisty,n) = vrstarty + (int)(drand48()*(vrfinishy-vrstarty));
+                arrayref(candlistx,n) = vrstartx + (int)(drand48()*(vrfinishx-vrstartx));
+                n++;
+//                printf("2: (%d,%d)\t%d\n", i,j,n);
+                continue;
+            }
+
+            for(k=0;k<n;k++)
+            {
+                if( arrayref(candlistx,n) == arrayref(candlistx,k) && arrayref(candlisty,n) == arrayref(candlisty,k) )
+                { 
+                    n--; 
+//                    printf("3: (%d,%d)\t%d\n", i,j,n);
+                    break;
+                }
+            }
+            n++;
+//            printf("4: (%d,%d)\t%d\n", i,j,n);
+        }
+    }
+    
+    return n;
+}
+
+// Initializes the output image and atlases to a random collection of pixels
+
+//void init(F2D *result, F2D *image, params* data)
+void init(F2D *image, params* data)
+{
+    int i,j,tmpx,tmpy;
+    vrstartx = data->localx/2; vrstarty = data->localy/2;
+    vrfinishx = data->widthin-data->localx/2;
+    vrfinishy = data->heightin-data->localy/2;
+    for(i=0;i<data->heightout;i++)
+    {
+        for(j=0;j<data->widthout;j++)
+        {
+            if(
+            asubsref(target,a(j,i,data->widthout)+R) == 1.0
+//            && asubsref(target,a(j,i,data->widthout)+G) == 1.0
+//            && asubsref(target,a(j,i,data->widthout)+B) == 1.0
+            )
+            {
+                tmpx = vrstartx + (int)(drand48()*(vrfinishx-vrstartx));
+                tmpy = vrstarty + (int)(drand48()*(vrfinishy-vrstarty));
+                if(!anotherpass)
+                {
+                    arrayref(atlas,aa(j,i)) = tmpx; 
+                    arrayref(atlas,aa(j,i)+1) = tmpy;
+                    asubsref(result,a(j,i,data->widthout)+R) = asubsref(image,a(tmpx,tmpy,data->widthin)+R);
+//                    asubsref(result,a(j,i,data->widthout)+G) = asubsref(image,a(tmpx,tmpy,data->widthin)+G);
+//                    asubsref(result,a(j,i,data->widthout)+B) = asubsref(image,a(tmpx,tmpy,data->widthin)+B);
+                }
+            }
+        }
+    }
+    
+    return;
+}
+
+
+// Compares two square neighborhoods, returns L_2 difference
+
+double compare_full_neighb(F2D *image,int x, int y, F2D *image1,int x1, int y1, params* data)
+{
+    double tmp,res = 0;
+    int i,j,addr,addr1;
+    for(i=-(data->localy/2);i<=data->localy/2;i++)
+    {
+        for(j=-(data->localx/2);j<=data->localx/2;j++)
+        {
+            if( !( i > 0 && y1 > data->localy && y1+i < data->heightout) )
+            {
+                addr = a(x+j,y+i,data->widthin);
+                addr1 = a( arrayref(xloopout,x1+j), arrayref(yloopout,y1+i), data->widthout);
+
+                tmp = asubsref(image,addr+R) - asubsref(image1,addr1+R);
+                res += tmp*tmp;
+//                tmp = asubsref(image,addr+G) - asubsref(image1,addr1+G);
+//                res += tmp*tmp;
+//                tmp = asubsref(image,addr+B) - asubsref(image1,addr1+B);
+//                res += tmp*tmp;
+            }
+        }
+    }
+
+    return res;
+}
+
+// Compares two L-shaped neighborhoods, returns L_2 difference
+
+double compare_neighb(F2D *image,int x, int y, F2D *image1,int x1, int y1, params* data)
+{
+    double tmp,res = 0;
+    int i,j,addr1,addr;
+    for(i=-(data->localy/2);i<0;i++)
+    {
+        for(j=-(data->localx/2);j<=data->localx/2;j++)
+        {
+            addr = a(x+j,y+i,data->widthin);
+            addr1 = a( arrayref(xloopout,x1+j), arrayref(yloopout,y1+i), data->widthout);
+
+            tmp = asubsref(image,addr+R) - asubsref(image1,addr1+R);
+            res += tmp*tmp;
+//            tmp = asubsref(image,addr+G) - asubsref(image1,addr1+G);
+//            res += tmp*tmp;
+//            tmp = asubsref(image,addr+B) - asubsref(image1,addr1+B);
+//            res += tmp*tmp;
+        }
+    }
+ 
+    for(j=-(data->localx/2);j<0;j++)
+    {
+        addr = a(x+j,y,data->widthin);
+        addr1 = a( arrayref(xloopout,x1+j), y1, data->widthout);
+
+        tmp = asubsref(image,addr+R) - asubsref(image1,addr1+R);
+        res += tmp*tmp;
+//        tmp = asubsref(image,addr+G) - asubsref(image1,addr1+G);
+//        res += tmp*tmp;
+//        tmp = asubsref(image,addr+B) - asubsref(image1,addr1+B);
+//        res += tmp*tmp;
+    }
+
+    return res;
+}
+
+double compare_rest(F2D *image,int x, int y, F2D *tar,int x1, int y1, params* data)
+{
+    double tmp,res = 0;
+    int i,j,addr,addr1;
+
+    for(i=(data->localy/2);i>0;i--)
+    {
+        for(j=-(data->localx/2);j<=data->localx/2;j++)
+        {
+            addr = a(x+j,y+i,data->widthin);
+            addr1 = a( arrayref(xloopout,x1+j), arrayref(yloopout,y1+i), data->widthout);
+
+            if( asubsref(tar,addr1+R) != 1.0) //KVS?
+            {
+                tmp = asubsref(image,addr+R) - asubsref(tar,addr1+R);
+                res += tmp*tmp;
+//                tmp = asubsref(image,addr+G) - asubsref(tar,addr1+G);
+//                res += tmp*tmp;
+//                tmp = asubsref(image,addr+B) - asubsref(tar,addr1+B);
+//                res += tmp*tmp;
+            }
+        }
+    }
+ 
+    for(j=(data->localx/2);j>0;j--)
+    {
+        addr = a(x+j,y,data->widthin);
+        addr1 = a( arrayref(xloopout,x1+j), y1, data->widthout);
+        if( asubsref(tar,addr1+R) != 1.0)   // KVS?
+        {
+            tmp = asubsref(image,addr+R) - asubsref(tar,addr1+R);
+            res += tmp*tmp;
+//            tmp = asubsref(image,addr+G) - asubsref(tar,addr1+G);
+//            res += tmp*tmp;
+//            tmp = asubsref(image,addr+B) - asubsref(tar,addr1+B);
+//            res += tmp*tmp;
+        }
+    }
+
+    return res;
+}
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/c/texture.h b/SD-VBS/benchmarks/texture_synthesis/src/c/texture.h
new file mode 100644
index 0000000..9819c03
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/c/texture.h
@@ -0,0 +1,48 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#ifndef _TEXTURE_
+#define _TEXTURE_
+
+#include "sdvbs_common.h"
+
+#define R 0
+#define G 1
+#define B 2
+#define a(x,y,W)        (1*((y)*(W)+(x)))
+#define aa(x,y) (2*((y)*data->widthout+(x)))
+
+typedef float pixelvalue;
+
+typedef struct
+{
+ double sign, diff;
+ int x,y;
+ int secondx, secondy;
+}signature;
+
+typedef struct{
+ int localx, localy, localz;
+ int widthin, widthout;
+ int heightin, heightout; 
+ int nfin, nfout;
+}params;
+
+void *SIGNATURES;
+
+//void create_texture(F2D *image, F2D *result, params *data);
+void create_texture(F2D *image, params *data);
+I2D* parse_flags(int argc, char ** argv);
+void init_params(params *data);
+//void init(F2D *result, F2D *image, params* data);
+void init(F2D *image, params* data);
+double compare_full_neighb(F2D *image,int x, int y, F2D *image1,int x1, int y1, params* data);
+double compare_neighb(F2D *image,int x, int y, F2D *image1,int x1, int y1, params* data);
+int create_candidates(int x,int y, params* data);
+int create_all_candidates(int x,int y, params* data);
+
+#endif
+
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/ChangeLog b/SD-VBS/benchmarks/texture_synthesis/src/matlab/ChangeLog
new file mode 100755
index 0000000..f20c499
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/ChangeLog
@@ -0,0 +1,430 @@
+           Log of changes made to matlabPyrTools code
+                (important changes marked with **)
+----------------------------------------------------------------------- 
+2004-10-14  Eero Simoncelli  <eero@sesto.cns.nyu.edu>
+
+        * Made new tarfile (version 1.3) 
+        
+        * Incorporated complex-valued steerable pyramid code (buildSCFpyr,
+        buildSCFpyrLevs,reconSCFpyr) written by Javier Portilla in 9/97,
+        and used in our work on texture representation/synthesis
+        (Portilla&Simoncelli, Int'l Journal of Computer Vision,
+        40(1):49-71, Dec 2000).
+        
+        * Incorporated imGradient.m from personal code.
+        
+        * reagan.pgm out.  feynam.pgm in
+        
+2004-03-20  Eero Simoncelli  <eero@sesto.cns.nyu.edu>
+
+        * blur.m added (just calls blurDn and then upBlur).
+        
+2003-08-06  Eero Simoncelli  <eero@sesto.cns.nyu.edu>
+
+        * blurDn.m (filt): Forced correct scaling of filters in  1D
+
+2003-05-28  Eero Simoncelli  <eero@ferrando.cns.nyu.edu>
+
+        * incorporated setPyrBand.m from local code
+
+2002-10-01  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * incorporated clip.m from local code
+
+2002-09-18  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * pointOp.m: Added the new 'extrap' option for matlab's interp1 to
+          make this m-file version more compatible with the mex version.
+
+Wed Aug 28 2002  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * var2.m: now returns zero (instead of error) for matrix of size 1.
+        * function VECTORIZE renamed to VECTIFY, since it was colliding
+          with a function introduced in standard matlab.
+        
+Dec 27 2001  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * Modified calls to upConv in reconSpyr.m and reconSpyrLevs.m so
+        that the returned result is bound.  Previously, had relied on the
+        MEX version of upConv to destructively modify the result array,
+        users had been getting errors because they were using the m-file
+        version of upConv.
+        
+Wed Sep 19 2001  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+        
+        * buildSFpyrLevs/reconSFpyrLevs: replace use of "i" with sqrt(-1), to
+          avoid  problems if user rebinds it!
+        
+Wed Mar 28 10:22:01 2001  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * Moved innerProd.m and all associated MEX files from the
+        matlabLocal source tree into matlabPyrTools.  
+        * Added innerProd to Contents.m
+        * Updated/clarified WARNINGS in all *.m files that have MEX versions.
+        
+Tue Mar 27 11:21:53 2001  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * Incorporated Windows MEX files (*.dll) into MEX subdirectory.
+         Windows users should either copy these into the main directory,
+         or put the MEX subdirectory in their matlab path.
+        
+Fri Mar 23 14:46:16 2001  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * buildSFpyrLevs.m, reconSFpyrLevs.m: shift the raised-cosine
+        lookup table (Xrcos) instead of incrementing the log-radial image
+        (log_rad).  THis is more efficient...
+
+Fri Oct  1 19:37:03 1999  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * upConv.m: Did not return correct size result when STOP argument
+        was passed.  Thanks to hertzman@mrl.nyu.edu for pointing this out.
+        
+Fri Sep 17 15:53:26 1999  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * buildSFpyrLevs.m: Changed lutsize to 1024, giving a slight
+        increase in accuracy.
+
+Thu Feb 25 18:10:38 1999  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * histo1.m: Modified histo.m to be more compatible (but still not
+        exactly the same) as the MEX file version.
+
+Fri Jun 12 21:15:39 1998  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * TUTORIALS pyramids.m upgraded.
+
+Tue Feb 17 13:22:28 1998  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * showIm.m: Dims are now printed followed by the zoom factor.
+
+Mon Oct 13 14:49:51 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * mkSquare.m: Modified to do raised-cosine soft threshold
+        transitions.
+
+Tue Oct  7 10:13:51 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * upConv.m: Argument order was wrong (this function is not used
+        anyway, unless you don't compile the MEX code). - Thanks to
+        farid@psyche.mit.edu for pointing this out.
+
+Thu Sep 25 16:09:49 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * MEX/wrap.c: Changed #include <malloc.h> to <stdlib.h>, as
+        suggested by David Brainard.  * Incorporated Mac-compiled mex
+        files, courtesy of David Brainard.
+        
+Sat Sep  6 16:10:25 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * MEX/convolve.h:  abstracted out type of images with typedef image_type.
+        Added ansi declarations.
+        
+Fri Aug 29 13:49:16 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** showIm.m: Modified to behave better under resizing (and printing):
+        resets axis units to "normalized".
+
+Thu Aug 28 22:56:52 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** MEX/edges.c: reflect1, reflect2, repeat, extend upgraded to work
+        properly for non-symmetric filters.  reflect2 and extend were also
+        broken for upConv.  Added qreflect2 to handle even-length QMF's
+        which broke under the reflect2 modification.
+        * Added example code to TUTORIALS/matlabPyrTools to illustrate the
+        boundary-handling behavior...
+        
+Thu Aug 21 13:34:17 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * var2, skew2, kurt2: modified to return complex values for complex images.
+        * imStats.m: now gives an error for complex args.
+
+Thu Aug 14 15:24:29 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Modified shift.m: negated the meaning of the offset parameter,
+        such that RES=shift(MTX,OFFSET) means RES(POS)=MTX(POS-OFFSET)
+        (this is more intuitive).
+
+Thu Jul 10 17:06:52 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Modified MEX/Makefile-* to be consistent with matlab5:
+           - call mex instead of cmex
+           - use -V4 flag (creating matlab v4 compatible binaries)
+        
+        * showIm.m (xlbl_offset): Modified to use "points" units, so that
+        printed images look correct.  Still slightly busted for arbitrary figure
+        window sizes and for printing.
+        
+        * Modified upConv.c: does not return ANYTHING if you pass a result
+        argument (this had been causing occasional problems with matlab's 
+        memory manager).
+        
+Mon Jun 30 12:09:30 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * reconSFpyr.m (res): now returns real part (oops).
+
+        * reconSpyrLevs.m (maxLev): got rid of superfluous nbands argument
+        (can be calculated from bfilts).
+
+Mon May 26 12:29:54 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * showIm.m/pgmWrite.m: Modified 'auto3'-scaling to use a
+        histogram.  This gives a significant speedup.
+
+        * fixed a few minor bugs in the TUTORIALS, having to do with 
+        matching image sizes to the machine speed...
+
+Sat May 10 17:27:25 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * pgmWrite.m: fixed auto-scaling bug.  Added new scaling
+        calculations, parallel to those of imShow.
+
+Fri May  9 09:02:56 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * buildSFpyr.m: Changed NBANDS argument to be ORDER, which is one
+        less than the number of orientation bands.  This is consistent
+        with the derivative order, and the labels on the spNFilters files.
+
+Tue May  6 19:08:18 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** Added buildSFpyr, reconSFpyr: Steerable pyramids constructed
+        in the Fourier domain.  Radial functions tile, with a
+        raised-cosine falloff.  Angular functions are
+        cos(theta-k\pi/(K+1))^K, where K is the order (number of bands
+        minus 1).  Compared to the convolution version:
+            + Reconstruction is exact (within floating point errors) 
+            + Can produce any number of orientation bands. 
+            - Typically slower.
+            - Boundary-handling must be circular.
+        Could be made much more efficient by taking advantage of symmetries in
+        the fft!
+        
+        * Added example usage of Fourier steerable pyramid to TUTORIALS/pyramids.m
+        
+        * steer.m:  fixed for harmonic lists including zero.
+
+Sun May  4 15:16:10 1997  Eero Simoncelli  <eero@ferrando.cns.nyu.edu>
+
+        * MEX/Makefile-linux: created.
+        
+        * spyrHt, spyrNumBands: Modified to return 0 for pyramids of height 0.
+        
+        * reconWpyr.m: utilize desctructive addition in calls to upConv.
+        
+        * reconSpyr.m: Added error check to ensure consistancy between
+        pyramid and filter file.  Utilize destructive addition in upConv
+        call on highpass band.  Modified to work properly with pyramids of
+        height 0.
+        
+Mon Apr 28 13:38:10 1997  Eero Simoncelli  <eero@ferrando.cns.nyu.edu>
+
+        * lplot.m: modified to handle complex vectors,  use standard MatLab 
+          indices, and show minimal axes.  Added xrange parameter to allow
+          adjustment of X axis labeling.
+
+Sun Apr 27 20:20:41 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * var2, skew2, kurt2: enhanced to work on complex matrices.
+        
+Sat Apr 26 11:16:12 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Changed parent directory (and distribution) name:
+                   matlabImTools -> matlabPyrTools
+
+        * namedFilter.m: Added two more Daubechies filters, and modified
+        names to match the reference (e.g., daub2 is now a 4-tap filter).
+
+        * Added vectorize.m: trivial function to pack matrix into vector (i.e., 
+        computes mtx(:)).
+        
+        * Added upBlur.m: Upsample and blur (parallels blurDn).
+
+Sun Apr 13 14:23:38 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * TUTORIALS/pyramids.m: Added plots of Fourier spectra for Wavelet bases.
+        
+        * make-tar-file: switched from compress to  gzip  for the
+        distribution tarfile.
+
+        * namedFilter.m: Added a few even-length QMF's from Johnston80.
+
+Fri Apr 11 19:16:21 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * buildWpyr.m, reconWpyr.m: Modified slightly, so that subsampling
+        lattice is better for even-length filters.
+        
+        * TUTORIALS/pyramids.m: Substantially overhauled.
+        
+Thu Apr 10 15:20:23 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * blurDn.m: added this function to downsample an image by a factor
+        2^L.
+
+        * Fixed minor bug in upConv.m: errors in image size checking.
+
+Mon Apr  7 13:25:37 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Changed TUTORIALS/matlabImTools.m to use histo.mex instead of
+        matlab's hist.
+
+Wed Apr  2 13:20:55 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** Incorporated Denis Pelli's ThinkC and MetroWorks projects for
+        Macintosh versions of the MEX code, along with MEX binaries.  These
+        are included as an HQX'ed self-extracting archive
+        (Macintosh-MEX.sit.hqx), in the MEX subdirectory.
+
+Tue Apr  1 15:35:31 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * edges.c: modified by Denis Pelli to support THINK C.  * edges.c:
+        
+        * histo.c, upConv.c, corrDn.c: minor changes in error message
+        printouts, to work around bugs in THINK C.
+        
+        * Included Denis Pelli's MacReadMe file in the MEX subdirectory,
+        which gives instructions for MEX file compilation on a MacIntosh
+        (PPC or 68k).
+        
+        * wrap.c, convolve.c, edges.c: added explicit int function
+        declarations, and return values.
+
+        * range2.m/range2.c: A MEX function for fast min/max computation.
+        Adjusted entropy2.m, histo.m, imStats.m, pgmWrite.m, showIm.m,
+        showLpyr.m, showSpyr.m, showWpyr.m to call it.
+          
+Thu Mar 27 17:23:05 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** histo.m/histo.c: Added MEX function HISTO, a fast replacement
+        for matlab's HIST function.  Modified histoMatch.m, entropy2.m to
+        call it.
+        
+        * Changed main directory  name to matlabImTools.
+        
+        * Added TUTORIALS/README file.
+        
+Wed Mar 19 14:19:51 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Changed directory name: MEX_SRC -> MEX
+
+Wed Mar 12 17:00:03 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * mkGaussian.m: fixed another (X,Y) bug: both dimensions and 
+        cov/mean are now specified in [y,x] order.
+
+Tue Mar 11 19:08:17 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * showSpyr.m: Fixed a bug that was dropping display of one
+        orientation band when there were more than 2 of them!
+
+Mon Mar 10 19:08:24 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * Added shift.m
+        
+        * makeSteerMtx -> steerDir2HarmMtx
+        
+        * Added TUTORIALS/matlab-EPS.m: examples using the code in this
+        distribution.
+
+Sun Mar  9 17:49:18 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** showIm.m:  
+          - args: changed order so that NSHADES is last.
+          - TITLES: Can now pass a string for IM, which will be evaluated
+            in the global environment to get the matrix.  The string is
+            used as a title.  MATLAB v.5 ONLY!!!
+          - Added 'auto3' RANGE value, that scales based on percentiles.
+            THis is more robust to outliers than 'auto2' or 'auto1'.
+        
+        * pixelAxes.m: Made a more serious attempt to reverse-engineer
+          Mathworks' image pixelization.  It is improved, but still makes
+          occasional errors.
+        
+        * Added skew2.m.
+        
+Fri Mar  7 10:11:07 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * pixelAxes.m: Modified to take an optional
+        ZOOM argument.  Fixed dimension ordering bug
+        (positions are reported (x,y), but mtx dims are (y,x)!)
+        
+        * showIm.m: Added an optional ZOOM argument.
+
+Thu Mar  6 14:17:19 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Added showLpyr, showWpyr, showSpyr.  Modified
+        TUTORIALS/pyramids.m to use them.
+        
+        * added pixelAxes.m: Adjusts size (in pixels) of currently
+        displayed image to be a multiple of the matrix dimensions, 
+        thus eliminating display aliasing artifacts.
+         This is now called by all the "show" commands.
+
+Mon Mar  3 17:33:25 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Fixed bug in pgmWrite (dimensions were written in reverse order).
+
+        * Fixed bug in showIm (X and Y coords were swapped on label display).
+        
+        * Fixed bug in reconLpyr (swapped X and Y coords on int_sz)
+        
+        * Changed calls to "reshape" to pass dimensions individually --
+        older version of matlab do not accept the reshape(mtx,[y x]) form.
+        
+        * Fixed bug in mkDisc: sz a scalar.
+        
+        * Added ifftshift.m
+        
+Fri Feb 28 11:07:20 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+        
+        * Re-worked TUTORIALS/pyramids.m
+
+        * buildGpyr and buildLpyr now use 1+maxPyrHt for default height.
+        
+        * Fixed buildGpyr to work on 1D signals.
+        
+        ** Gaussian/Laplacian/Wavelet pyramid build and recon functions:
+          - work properly with new corrDn/upConv.
+          - use separable convolutions 
+          - use destructive modification ability of upConv (less memory
+          allocation)
+        
+        * modulateFlipShift -> modulateFlip.
+        
+        * added lpyrHt, wpyrHt, spyrHt to return number of levels in a pyramid.
+        
+Thu Feb 27 15:39:53 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Changed angular coordinate systems to CLOCKWISE in mkRamp,
+        mkTheta, mkSine, mkSquare.  This is unnatural for screen viewing,
+        but consistent with an origin in the upper left corner of the
+        image, which is the way one addresses the underlying matrix.
+
+        * mkSine and mkSquare can now take a frequency vector or the 
+          period and direction args
+        
+Tue Feb 25 11:58:33 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** Rewrote corrDn/upConv C routines:
+          - more efficient
+          - changed START parameters to have [1 1] origin, consistent with
+            matlab
+          - added STOP parameters
+          - upConv allows destructive modification of a result arg
+          - changed order of other params (sorry)
+          - wrote test file conv_test.m
+        * wrote zconv2.m
+
+Wed Aug 19 20:39:15 1996  Eero Simoncelli  (eero@tarpon.cis.upenn.edu)
+
+        ** Added "pointOp" function (MUCH faster than interp1).
+        ** Added "histoMatch" function.
+
+Fri Aug  2 00:56:31 1996  Eero Simoncelli  (eero@tarpon.cis.upenn.edu)
+
+        * Changed all function/file-names to be of the form "fooBar".  *
+        Fixed entropy2.m (busted due to typo).
+
+Original convolution code was written in Spring 1986, and comes from
+OBVIUS (Object-Based Vision and Image Understanding System), an
+interactive image-processing system written in Common Lisp (with calls
+to C code).
+        
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/Contents.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/Contents.m
new file mode 100755
index 0000000..d19f067
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/Contents.m
@@ -0,0 +1,107 @@
+% Image and Multi-scale Pyramid Tools
+% Version 1.3,  October 2004.
+% Created: Early Spring, 1996. Eero Simoncelli, eero.simoncelli@nyu.edu
+%
+% See README file for brief description.
+% See ChangeLog file for latest modifications. 
+% See TUTORIALS subdirectory for demonstrations.
+% Type "help <command-name>" for documentation on individual commands.
+% -----------------------------------------------------------------
+% Synthetic Images (matrices):
+%   mkImpulse  - Make an image containing an impulse.
+%   mkRamp     - Make an image containing a ramp function.
+%   mkR        - Make an image containing distance from the origin.
+%   mkAngle    - Make an image containing angle about origin.
+%   mkDisc     - Make an image containing a disk image.
+%   mkGaussian - Make an image containing a Gaussian function.
+%   mkZonePlate - Make an image containing a zone plate (cos(r^2)).
+%   mkAngularSine - Make an image containing an angular sine wave (pinwheel).
+%   mkSine     - Make an image containing a sine grating.
+%   mkSquare   - Make an image containing a square grating.
+%   mkFract    - Make an image containing fractal (1/f) noise.
+%
+% Point Operations:
+%   clip       - clip values to a range. 
+%   pointOp    - Lookup table (much faster than interp1) [MEX file]
+%   histo      - Efficient histogram computation [MEX file]
+%   histoMatch - Modify matrix elements to match specified histogram stats.
+%
+% Convolution (first two are significantly faster):
+%   corrDn     - Correlate & downsample with boundary-handling [MEX file]
+%   upConv     - Upsample & convolve with boundary-handling [MEX file]
+%   blurDn     - Blur and subsample a signal/image.
+%   upBlur     - Upsample and blur a signal/image.
+%   blur       - Multi-scale blurring, calls blurDn and then upBlur.
+%   cconv2     - Circular convolution.
+%   rconv2     - Convolution with reflected boundaries.
+%   zconv2     - Convolution assuming zeros beyond image boundaries.
+%
+% General pyramids:
+%   pyrLow     - Access lowpass subband from (any type of) pyramid
+%   pyrBand    - Access a subband from (any type of) pyramid
+%   setPyrBand - Insert an image into (any type of) pyramid as a subband 
+%   pyrBandIndices - Returns indices for given band in a pyramid vector
+%   maxPyrHt   - compute maximum number of scales in a pyramid
+%
+% Gaussian/Laplacian Pyramids:
+%   buildGpyr  - Build a Gaussian pyramid of an input signal/image.
+%   buildLpyr  - Build a Laplacian pyramid of an input signal/image.
+%   reconLpyr  - Reconstruct (invert) the Laplacian pyramid transform.
+%
+% Separable orthonormal QMF/wavelet Pyramids:
+%   buildWpyr  - Build a separable wavelet representation of an input signal/image.
+%   reconWpyr  - Reconstruct (invert) the wavelet transform.
+%   wpyrBand   - Extract a single band of the wavelet representation.
+%   wpyrLev    - Extract (packed) subbands at a particular level
+%   wpyrHt     - Number of levels (height) of a wavelet pyramid.
+%
+% Steerable Pyramids:
+%   buildSpyr  - Build a steerable pyramid representation of an input image.
+%   reconSpyr  - Reconstruct (invert) the steerable pyramid transform.
+%   buildSFpyr - Build a steerable pyramid representation in the Fourier domain.
+%   reconSFpyr - Reconstruct (invert) the (Fourier domain) steerable pyramid transform.
+%   spyrBand   - Extract a single band from a steerable pyramid.
+%   spyrHigh   - Highpass residual band.
+%   spyrLev    - A whole level (i.e., all images at a given scale) of a steerable pyramid.
+%   spyrHt     - Number of levels (height) of a steerable pyramid.
+%   spyrNumBands - Number of orientation bands in a steerable pyramid.
+%
+% Steerable filters / derivatives:
+%   imGradient - Compute gradient of image using directionally accurete filters.
+%   steer      - Steer filters (or responses).
+%   steer2HarmMtx - Construct a matrix mapping direcional basis to angular harmonics. 
+% 
+% Filters:
+%   binomialFilter  - returns a filter of binomial coefficients.
+%   namedFilter     - some typical Laplacian/Wavelet pyramid filters
+%   spNFilters      - Set of Nth order steerable pyramid filters.
+%   derivNFiltersS  - Matched set of S-tap 1D derivatives, orders 0 to N.
+% 
+% Display:
+%   showIm     - Display a matrix (real or complex) as grayscale image(s).
+%                Displays dimensions, subsampling, and range of pixel values.
+%   showLpyr   - Display a Laplacian pyramid.
+%   showWpyr   - Display a separable wavelet pyramid.
+%   showSpyr   - Display a steerable pyramid.
+%   lplot      - "lollipop" plot.
+%   nextFig    - Make next figure window current.
+%   pixelAxes  - Make image display use an integer number of pixels 
+%                per sample to avoid resampling artifacts.
+% 
+% Statistics (for 2D Matrices):
+%   range2     - Min and max of image (matrix) [MEX file]
+%   mean2      - Sample mean of an image (matrix). 
+%   var2       - Sample variance of an image (matrix). 
+%   skew2      - Sample skew (3rd moment / variance^1.5) of an image (matrix). 
+%   kurt2      - Sample kurtosis (4th moment / variance^2) of an image (matrix). 
+%   entropy2   - Sample entropy of an image (matrix).
+%   imStats    - Report sample statistics of an image, or pair of images.
+%
+% Miscellaneous:
+%   pgmRead    - Load a "pgm" image into a MatLab matrix [try einstein.pgm,feynman.pgm]
+%   pgmWrite   - Write a MatLab matrix to a "pgm" image file.
+%   shift      - circular shift a 2D matrix by an arbitrary amount.
+%   vectify    - pack matrix into column vector (i.e., function to compute mtx(:)).
+%   ifftshift  - inverse of MatLab's FFTSHIFT (differs for odd-length dimensions)
+%   rcosFn     - return a lookup table of a raised-cosine threshold fn.
+%   innerProd  - Compute M'*M efficiently (i.e., do not copy) [MEX file]
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/-MacReadMe b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/-MacReadMe
new file mode 100755
index 0000000..898dc0c
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/-MacReadMe
@@ -0,0 +1 @@
+MacReadMe
How to compile a MEX file for Macintosh
(Based on a similar note written by David Brainard and Denis Pelli to accompany the Psychophysics Toolbox.)

A MEX file (short for "MATLAB extension") contains code that implements a new MATLAB function, allowing users to use the full power of the C language and the Macintosh hardware and operating system in implementing a new MATLAB function. This document explains how to produce a MEX file that is "fat" (i.e. will run as native code on both 68K and PowerPC Macs) and is compatible with both MATLAB 4 and 5.

1) To produce a MATLAB MEX file with PowerPC code you must have the Metrowerks CodeWarrior C compiler (version 10 or better, abbreviated as CW below). To produce 68K code we still use the Symantec THINK C compiler (version from Symantec C++ 8 CD-ROM release 5), but we will soon be switching to Metrowerks CodeWarrior. (See note A below.)

2) Place a copy of the MATLAB 4:Extern folder, supplied by Mathworks, on your compiler's search path. We suggest that you name the copy "MEX V4". (See notes B and C, below.) 

3) Build any of the MEX files simply by opening its project file and asking your compiler to "Build Code Resource" (in THINK C) or to "Make" it (in CW).  For each MEX file, e.g. histo.mex, there are two associated projects, e.g. histo.µ for CW, and histo.¹.4 for THINK C. To build a "fat" MEX, that runs native on both 68K and PowerPC, you should first compile in THINK C, and then in CW. (See note A, below.)

Denis Pelli
April 2, 1997

Notes

A) The Mathworks support only the THINK C compiler to make 68K MEX code for MATLAB version 4 and only the CW compiler to make PPC MEX files for MATLAB 4 and both 68K and PPC for MATLAB 5. This archive includes THINK and CW projects. To build a fat MEX file for MATLAB 4, first "make" the THINK C version (e.g. histo.¹.4), producing a file with a .rsrc extension (e.g. histo.µ.rsrc). This is the 68K MEX file. When you then "make" histo.µ, the CW project incorporates the .rsrc file and generates a "fat" MEX file that will run native (i.e. fast) on both 68K and PowerPC. To make a 68K-only MEX file, simply rename, e.g., histo.µ.rsrc to histo.mex after you make the THINK project, and set the file type and creator to match the other MEX files. THINK C is slow and hard to work with. Symantec hasn't significantly upgraded in it many years. There is an error in the math.h header (version from Symantec C++ 8 CD-ROM release 5). We fix that error by some tricky preprocessor defines and undefines in the THINK C Prefix in each of the THINK projects. 

B) The easiest way to put a folder on your compilerÕs search path is simply to put the folder in the same folder as the compiler itself. If you want to use both CW and THINK C, then put the folder under CW, make an alias of it, and put the alias in THINK C's "Aliases" folder.

C) Happily, MATLAB 5 is capable of running both V4 and V5 MEX files. Thus we are currently distributing sources that compile into V4 MEX files. The resulting MEX files run both under V4 and V5. In the future we will drop support for V4 and THINK C. (See note A above.) 
\ No newline at end of file
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.AppleDouble/.Parent b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.AppleDouble/.Parent
new file mode 100755
index 0000000..f242a99
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.AppleDouble/.Parent
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCIndex b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCIndex
new file mode 100755
index 0000000..848736b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCIndex
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCLockFolder/.FBCSemaphoreFile b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCLockFolder/.FBCSemaphoreFile
new file mode 100755
index 0000000..ab2c684
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/.FBCLockFolder/.FBCSemaphoreFile
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-linux b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-linux
new file mode 100755
index 0000000..726dd31
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-linux
@@ -0,0 +1,39 @@
+MLAB = /usr/local/matlab5.1
+
+MXSFX = mexlx
+MEX = ${MLAB}/bin/mex
+
+MFLAGS = -V4
+INC = -I ${MLAB}/extern/include
+LIB = -L ${MLAB}/extern/lib
+
+CC = gcc -Wall -pedantic
+C_OPTIMIZE_SWITCH = -O2    ## For GCC
+CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
+
+all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
+        histo.${MXSFX} range2.${MXSFX}
+
+clean:
+        /bin/rm *.o
+
+corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
+
+upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
+
+pointOp.${MXSFX}: pointOp.o
+        ${MEX} ${MFLAGS} pointOp.o
+
+histo.${MXSFX}: histo.o
+        ${MEX} ${MFLAGS} histo.o
+
+range2.${MXSFX}: range2.o
+        ${MEX} ${MFLAGS} range2.o
+
+convolve.o wrap.o edges.o: convolve.h 
+
+%.o : %.c
+        ${CC} -c ${CFLAGS} $<           
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-ml6-linux b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-ml6-linux
new file mode 100755
index 0000000..f596ad7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-ml6-linux
@@ -0,0 +1,39 @@
+MLAB = /usr/local/matlab6.0
+
+MXSFX = mexglx
+MEX = ${MLAB}/bin/mex
+
+MFLAGS = -V4
+INC = -I ${MLAB}/extern/include
+LIB = -L ${MLAB}/extern/lib
+
+CC = gcc -Wall -pedantic
+C_OPTIMIZE_SWITCH = -O2    ## For GCC
+CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
+
+all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
+        histo.${MXSFX} range2.${MXSFX}
+
+clean:
+        /bin/rm *.o
+
+corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
+
+upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
+
+pointOp.${MXSFX}: pointOp.o
+        ${MEX} ${MFLAGS} pointOp.o
+
+histo.${MXSFX}: histo.o
+        ${MEX} ${MFLAGS} histo.o
+
+range2.${MXSFX}: range2.o
+        ${MEX} ${MFLAGS} range2.o
+
+convolve.o wrap.o edges.o: convolve.h 
+
+%.o : %.c
+        ${CC} -c ${CFLAGS} $<           
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-osx b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-osx
new file mode 100755
index 0000000..352d15b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-osx
@@ -0,0 +1,39 @@
+MLAB = /share/wotan/matlab13
+
+MXSFX = mexosx
+MEX = ${MLAB}/bin/mex
+
+MFLAGS =
+INC = -I ${MLAB}/extern/include
+LIB = -L ${MLAB}/extern/lib
+
+CC = cc -Wall -pedantic -no-cpp-precomp
+C_OPTIMIZE_SWITCH = -O2    ## For GCC
+CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
+
+all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
+        histo.${MXSFX} range2.${MXSFX}
+
+clean:
+        /bin/rm *.o
+
+corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
+
+upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
+
+pointOp.${MXSFX}: pointOp.o
+        ${MEX} ${MFLAGS} pointOp.o
+
+histo.${MXSFX}: histo.o
+        ${MEX} ${MFLAGS} histo.o
+
+range2.${MXSFX}: range2.o
+        ${MEX} ${MFLAGS} range2.o
+
+convolve.o wrap.o edges.o: convolve.h 
+
+%.o : %.c
+        ${CC} -c ${CFLAGS} $<           
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-solaris b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-solaris
new file mode 100755
index 0000000..2be2bdb
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-solaris
@@ -0,0 +1,38 @@
+MLAB = /export/home/Solaris2/matlab5.1
+
+MXSFX = mexsol
+MEX = ${MLAB}/bin/mex
+
+MFLAGS = -V4
+INC = -I ${MLAB}/extern/include
+LIB = -L ${MLAB}/extern/lib
+
+CC = gcc -Wall -pedantic
+C_OPTIMIZE_SWITCH = -O2    ## For GCC
+CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
+
+all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
+        histo.${MXSFX} range2.${MXSFX}
+
+clean:
+        /bin/rm *.o
+
+corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
+
+upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
+
+pointOp.${MXSFX}: pointOp.o
+        ${MEX} ${MFLAGS} pointOp.o
+
+histo.${MXSFX}: histo.o
+        ${MEX} ${MFLAGS} histo.o
+
+range2.${MXSFX}: range2.o
+        ${MEX} ${MFLAGS} range2.o
+
+convolve.o wrap.o edges.o: convolve.h 
+
+%.o : %.c
+        ${CC} -c ${CFLAGS} $<
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-sun4 b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-sun4
new file mode 100755
index 0000000..432b181
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/Makefile-sun4
@@ -0,0 +1,39 @@
+MLAB = /home/alberich/matlab4
+
+MXSFX = mex4
+MEX = ${MLAB}/bin/cmex
+
+MFLAGS = 
+INC = -I ${MLAB}/extern/include
+LIB = -L ${MLAB}/extern/lib/sun4
+
+CC = gcc
+C_OPTIMIZE_SWITCH = -O2    ## For GCC
+CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
+
+all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
+        histo.${MXSFX} range2.${MXSFX}
+
+clean:
+        /bin/rm *.o
+
+corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
+
+upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
+
+pointOp.${MXSFX}: pointOp.o
+        ${MEX} ${MFLAGS} pointOp.o
+
+histo.${MXSFX}: histo.o
+        ${MEX} ${MFLAGS} histo.o
+
+range2.${MXSFX}: range2.o
+        ${MEX} ${MFLAGS} range2.o
+
+convolve.o wrap.o edges.o: convolve.h 
+
+%.o : %.c
+        ${CC} -c ${CFLAGS} $<           
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.c
new file mode 100755
index 0000000..60a11a4
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.c
@@ -0,0 +1,325 @@
+/* 
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;;  File: convolve.c
+;;;  Author: Eero Simoncelli
+;;;  Description: General convolution code for 2D images
+;;;  Creation Date: Spring, 1987.
+;;;  MODIFICATIONS:
+;;;     10/89: approximately optimized the choice of register vars on SPARCS.
+;;;      6/96: Switched array types to double float.
+;;;      2/97: made more robust and readable.  Added STOP arguments.
+;;;      8/97: Bug: when calling internal_reduce with edges in {reflect1,repeat,
+;;;            extend} and an even filter dimension.  Solution: embed the filter
+;;;            in the upper-left corner of a filter with odd Y and X dimensions.
+;;;  ----------------------------------------------------------------
+;;;    Object-Based Vision and Image Understanding System (OBVIUS),
+;;;      Copyright 1988, Vision Science Group,  Media Laboratory,  
+;;;              Massachusetts Institute of Technology.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+*/
+
+#include <stdio.h>
+#include <math.h>
+#include "convolve.h"
+
+/*
+  --------------------------------------------------------------------
+  Correlate FILT with IMAGE, subsampling according to START, STEP, and
+  STOP parameters, with values placed into RESULT array.  RESULT
+  dimensions should be ceil((stop-start)/step).  TEMP should be a
+  pointer to a temporary double array the size of the filter.
+  EDGES is a string specifying how to handle boundaries -- see edges.c.
+  The convolution is done in 9 sections, where the border sections use
+  specially computed edge-handling filters (see edges.c). The origin 
+  of the filter is assumed to be (floor(x_fdim/2), floor(y_fdim/2)).
+------------------------------------------------------------------------ */
+
+/* abstract out the inner product computation */
+#define INPROD(XCNR,YCNR)  \
+        { \
+        sum=0.0; \
+        for (im_pos=YCNR*x_dim+XCNR, filt_pos=0, x_filt_stop=x_fdim; \
+             x_filt_stop<=filt_size; \
+             im_pos+=(x_dim-x_fdim), x_filt_stop+=x_fdim) \
+            for (; \
+                 filt_pos<x_filt_stop; \
+                 filt_pos++, im_pos++) \
+              sum+= image[im_pos]*temp[filt_pos]; \
+        result[res_pos] = sum; \
+        }
+
+int internal_reduce(image, x_dim, y_dim, filt, temp, x_fdim, y_fdim,
+                x_start, x_step, x_stop, y_start, y_step, y_stop,
+                result, edges)
+  register image_type *image, *temp;
+  register int x_fdim, x_dim;
+  register image_type *result;
+  register int x_step, y_step;
+  int x_start, y_start;
+  int x_stop, y_stop;     
+  image_type *filt; 
+  int y_dim, y_fdim;
+  char *edges;
+  { 
+  register double sum;
+  register int filt_pos, im_pos, x_filt_stop;
+  register int x_pos, filt_size = x_fdim*y_fdim;
+  register int y_pos, res_pos;
+  register int y_ctr_stop = y_dim - ((y_fdim==1)?0:y_fdim);
+  register int x_ctr_stop = x_dim - ((x_fdim==1)?0:x_fdim);
+  register int x_res_dim = (x_stop-x_start+x_step-1)/x_step;
+  int x_ctr_start = ((x_fdim==1)?0:1);
+  int y_ctr_start = ((y_fdim==1)?0:1);
+  int x_fmid = x_fdim/2;
+  int y_fmid = y_fdim/2;
+  int base_res_pos;
+  fptr reflect = edge_function(edges);  /* look up edge-handling function */
+
+  if (!reflect) return(-1);
+
+  /* shift start/stop coords to filter upper left hand corner */
+  x_start -= x_fmid;   y_start -=  y_fmid;
+  x_stop -=  x_fmid;   y_stop -=  y_fmid;
+
+  if (x_stop < x_ctr_stop) x_ctr_stop = x_stop;
+  if (y_stop < y_ctr_stop) y_ctr_stop = y_stop;
+
+  for (res_pos=0, y_pos=y_start;              /* TOP ROWS */
+       y_pos<y_ctr_start;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start;                       /* TOP-LEFT CORNER */
+         x_pos<x_ctr_start;
+         x_pos+=x_step, res_pos++)
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-1,temp,REDUCE);
+      INPROD(0,0)
+      }
+
+    (*reflect)(filt,x_fdim,y_fdim,0,y_pos-1,temp,REDUCE);
+    for (;                                    /* TOP EDGE */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(x_pos,0)
+
+    for (;                                    /* TOP-RIGHT CORNER */
+         x_pos<x_stop;
+         x_pos+=x_step, res_pos++) 
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-1,temp,REDUCE);
+      INPROD(x_ctr_stop,0)
+      }
+    } /* end TOP ROWS */   
+
+  y_ctr_start = y_pos;                        /* hold location of top */
+  for (base_res_pos=res_pos, x_pos=x_start;   /* LEFT EDGE */
+       x_pos<x_ctr_start;
+       x_pos+=x_step, base_res_pos++)
+    {
+    (*reflect)(filt,x_fdim,y_fdim,x_pos-1,0,temp,REDUCE);
+    for (y_pos=y_ctr_start, res_pos=base_res_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, res_pos+=x_res_dim)
+      INPROD(0,y_pos)
+    }
+
+  (*reflect)(filt,x_fdim,y_fdim,0,0,temp,REDUCE);
+  for (;                                      /* CENTER */
+       x_pos<x_ctr_stop;
+       x_pos+=x_step, base_res_pos++) 
+    for (y_pos=y_ctr_start, res_pos=base_res_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, res_pos+=x_res_dim)
+      INPROD(x_pos,y_pos)
+
+  for (;                                      /* RIGHT EDGE */
+       x_pos<x_stop;
+       x_pos+=x_step, base_res_pos++)
+    {
+    (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,0,temp,REDUCE);
+    for (y_pos=y_ctr_start, res_pos=base_res_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, res_pos+=x_res_dim)
+      INPROD(x_ctr_stop,y_pos)
+    }
+
+  for (res_pos-=(x_res_dim-1);
+       y_pos<y_stop;                          /* BOTTOM ROWS */
+       y_pos+=y_step) 
+    {
+    for (x_pos=x_start;                       /* BOTTOM-LEFT CORNER */
+         x_pos<x_ctr_start;
+         x_pos+=x_step, res_pos++)
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-y_ctr_stop+1,temp,REDUCE);
+      INPROD(0,y_ctr_stop)
+      }
+
+    (*reflect)(filt,x_fdim,y_fdim,0,y_pos-y_ctr_stop+1,temp,REDUCE);
+    for (;                                    /* BOTTOM EDGE */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(x_pos,y_ctr_stop)
+
+    for (;                                    /* BOTTOM-RIGHT CORNER */
+         x_pos<x_stop;
+         x_pos+=x_step, res_pos++) 
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-y_ctr_stop+1,temp,REDUCE);
+      INPROD(x_ctr_stop,y_ctr_stop)
+      }
+    } /* end BOTTOM */
+  return(0);
+  } /* end of internal_reduce */
+
+
+/*
+  --------------------------------------------------------------------
+  Upsample IMAGE according to START,STEP, and STOP parameters and then
+  convolve with FILT, adding values into RESULT array.  IMAGE
+  dimensions should be ceil((stop-start)/step).  See
+  description of internal_reduce (above).
+
+  WARNING: this subroutine destructively modifies the RESULT array!
+ ------------------------------------------------------------------------ */
+
+/* abstract out the inner product computation */
+#define INPROD2(XCNR,YCNR)  \
+        { \
+        val = image[im_pos]; \
+        for (res_pos=YCNR*x_dim+XCNR, filt_pos=0, x_filt_stop=x_fdim; \
+             x_filt_stop<=filt_size; \
+             res_pos+=(x_dim-x_fdim), x_filt_stop+=x_fdim) \
+            for (; \
+                 filt_pos<x_filt_stop; \
+                 filt_pos++, res_pos++) \
+              result[res_pos] += val*temp[filt_pos]; \
+        }
+
+int internal_expand(image,filt,temp,x_fdim,y_fdim,
+                x_start,x_step,x_stop,y_start,y_step,y_stop,
+                result,x_dim,y_dim,edges)
+  register image_type *result, *temp;
+  register int x_fdim, x_dim;
+  register int x_step, y_step;
+  register image_type *image; 
+  int x_start, y_start;
+  image_type *filt; 
+  int y_fdim, y_dim;
+  char *edges;
+  {
+  register double val;
+  register int filt_pos, res_pos, x_filt_stop;
+  register int x_pos, filt_size = x_fdim*y_fdim;
+  register int y_pos, im_pos;
+  register int x_ctr_stop = x_dim - ((x_fdim==1)?0:x_fdim);
+  int y_ctr_stop = (y_dim - ((y_fdim==1)?0:y_fdim));
+  int x_ctr_start = ((x_fdim==1)?0:1);
+  int y_ctr_start = ((y_fdim==1)?0:1);
+  int x_fmid = x_fdim/2;
+  int y_fmid = y_fdim/2;
+  int base_im_pos, x_im_dim = (x_stop-x_start+x_step-1)/x_step;
+  fptr reflect = edge_function(edges);  /* look up edge-handling function */     
+
+  if (!reflect) return(-1);
+
+  /* shift start/stop coords to filter upper left hand corner */
+  x_start -= x_fmid;   y_start -=  y_fmid;
+  x_stop -=  x_fmid;   y_stop -=  y_fmid;
+
+  if (x_stop < x_ctr_stop) x_ctr_stop = x_stop;
+  if (y_stop < y_ctr_stop) y_ctr_stop = y_stop;
+
+  for (im_pos=0, y_pos=y_start;               /* TOP ROWS */
+       y_pos<y_ctr_start;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start;                       /* TOP-LEFT CORNER */
+         x_pos<x_ctr_start;
+         x_pos+=x_step, im_pos++)
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-1,temp,EXPAND);
+      INPROD2(0,0)
+      }
+
+    (*reflect)(filt,x_fdim,y_fdim,0,y_pos-1,temp,EXPAND);
+    for (;                                    /* TOP EDGE */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(x_pos,0)
+
+    for (;                                    /* TOP-RIGHT CORNER */
+         x_pos<x_stop;
+         x_pos+=x_step, im_pos++) 
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-1,temp,EXPAND);
+      INPROD2(x_ctr_stop,0)
+      }
+    }                                           /* end TOP ROWS */   
+
+  y_ctr_start = y_pos;                        /* hold location of top */
+  for (base_im_pos=im_pos, x_pos=x_start;     /* LEFT EDGE */
+       x_pos<x_ctr_start;
+       x_pos+=x_step, base_im_pos++)
+    {
+    (*reflect)(filt,x_fdim,y_fdim,x_pos-1,0,temp,EXPAND);
+    for (y_pos=y_ctr_start, im_pos=base_im_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, im_pos+=x_im_dim)
+      INPROD2(0,y_pos)
+    }
+
+  (*reflect)(filt,x_fdim,y_fdim,0,0,temp,EXPAND);
+  for (;                                      /* CENTER */
+       x_pos<x_ctr_stop;
+       x_pos+=x_step, base_im_pos++) 
+    for (y_pos=y_ctr_start, im_pos=base_im_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, im_pos+=x_im_dim)
+      INPROD2(x_pos,y_pos)
+
+  for (;                                      /* RIGHT EDGE */
+       x_pos<x_stop;
+       x_pos+=x_step, base_im_pos++)
+    {
+    (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,0,temp,EXPAND);
+    for (y_pos=y_ctr_start, im_pos=base_im_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, im_pos+=x_im_dim)
+      INPROD2(x_ctr_stop,y_pos)
+    }  
+
+  for (im_pos-=(x_im_dim-1);
+       y_pos<y_stop;                          /* BOTTOM ROWS */
+       y_pos+=y_step) 
+    {
+    for (x_pos=x_start;                       /* BOTTOM-LEFT CORNER */
+         x_pos<x_ctr_start;
+         x_pos+=x_step, im_pos++)
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-y_ctr_stop+1,temp,EXPAND);
+      INPROD2(0,y_ctr_stop)
+      }
+
+    (*reflect)(filt,x_fdim,y_fdim,0,y_pos-y_ctr_stop+1,temp,EXPAND);
+    for (;                                    /* BOTTOM EDGE */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(x_pos,y_ctr_stop)
+
+    for (;                                    /* BOTTOM-RIGHT CORNER */
+         x_pos<x_stop;
+         x_pos+=x_step, im_pos++) 
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-y_ctr_stop+1,temp,EXPAND);
+      INPROD2(x_ctr_stop,y_ctr_stop)
+      }
+    } /* end BOTTOM */
+  return(0);
+  } /* end of internal_expand */
+
+
+/* Local Variables: */
+/* buffer-read-only: t */
+/* End: */
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.h b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.h
new file mode 100755
index 0000000..48d55f7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.h
@@ -0,0 +1,55 @@
+/* 
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;;  File: convolve.h
+;;;  Author: Simoncelli
+;;;  Description: Header file for convolve.c
+;;;  Creation Date:
+;;;  ----------------------------------------------------------------
+;;;    Object-Based Vision and Image Understanding System (OBVIUS),
+;;;      Copyright 1988, Vision Science Group,  Media Laboratory,  
+;;;              Massachusetts Institute of Technology.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+*/
+
+#include <stdio.h>
+#include <stdlib.h> 
+
+#define ABS(x)    (((x)>=0) ? (x) : (-(x)))
+#define ROOT2 1.4142135623730951
+#define REDUCE 0
+#define EXPAND 1
+#define IS    ==
+#define ISNT  !=
+#define AND &&
+#define OR ||
+
+typedef  int (*fptr)();
+
+typedef struct 
+  {
+  char *name;
+  fptr func;
+  } EDGE_HANDLER;
+
+typedef double image_type;
+
+fptr edge_function(char *edges);
+int internal_reduce(image_type *image, int x_idim, int y_idim, 
+                    image_type *filt, image_type *temp, int x_fdim, int y_fdim,
+                    int x_start, int x_step, int x_stop, 
+                    int y_start, int y_step, int y_stop,
+                    image_type *result, char *edges);
+int internal_expand(image_type *image, 
+                    image_type *filt, image_type *temp, int x_fdim, int y_fdim,
+                    int x_start, int x_step, int x_stop, 
+                    int y_start, int y_step, int y_stop,
+                    image_type *result, int x_rdim, int y_rdim, char *edges);
+int internal_wrap_reduce(image_type *image, int x_idim, int y_idim, 
+                         image_type *filt, int x_fdim, int y_fdim,
+                         int x_start, int x_step, int x_stop, 
+                         int y_start, int y_step, int y_stop,
+                         image_type *result);
+int internal_wrap_expand(image_type *image, image_type *filt, int x_fdim, int y_fdim,
+                         int x_start, int x_step, int x_stop, 
+                         int y_start, int y_step, int y_stop,
+                         image_type *result, int x_rdim, int y_rdim);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.mexglx b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.mexglx
new file mode 100755
index 0000000..2dea157
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/convolve.mexglx
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/corrDn.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/corrDn.c
new file mode 100755
index 0000000..c74df1f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/corrDn.c
@@ -0,0 +1,145 @@
+/* 
+RES = corrDn(IM, FILT, EDGES, STEP, START, STOP);
+  >>> See corrDn.m for documentation <<<
+  This is a matlab interface to the internal_reduce function. 
+  EPS, 7/96.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  /* Matlab matrices */
+#include <mex.h>
+
+#include "convolve.h"
+
+#define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it))
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+  {
+  double *image,*filt, *temp, *result;
+  int x_fdim, y_fdim, x_idim, y_idim;
+  int x_rdim, y_rdim;
+  int x_start = 1;
+  int x_step = 1;
+  int y_start = 1;
+  int y_step = 1;
+  int x_stop, y_stop;
+  mxArray *arg;
+  double *mxMat;
+  char edges[15] = "reflect1";
+  
+  if (nrhs<2) mexErrMsgTxt("requres at least 2 args.");
+
+  /* ARG 1: IMAGE  */
+  arg = prhs[0];
+  if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a non-sparse double float matrix.");
+  image = mxGetPr(arg);
+  x_idim = (int) mxGetM(arg); /* X is inner index! */
+  y_idim = (int) mxGetN(arg);
+
+  /* ARG 2: FILTER */
+  arg = prhs[1];
+  if notDblMtx(arg) mexErrMsgTxt("FILTER arg must be non-sparse double float matrix.");
+  filt = mxGetPr(arg);
+  x_fdim = (int) mxGetM(arg); 
+  y_fdim = (int) mxGetN(arg);
+
+  if ((x_fdim > x_idim) || (y_fdim > y_idim))
+    {
+    mexPrintf("Filter: [%d %d], Image: [%d %d]\n",x_fdim,y_fdim,x_idim,y_idim);
+    mexErrMsgTxt("FILTER dimensions larger than IMAGE dimensions.");
+    }
+
+  /* ARG 3 (optional): EDGES */
+  if (nrhs>2) 
+      {
+      if (!mxIsChar(prhs[2]))
+        mexErrMsgTxt("EDGES arg must be a string.");
+      mxGetString(prhs[2],edges,15);
+      }
+
+  /* ARG 4 (optional): STEP */
+  if (nrhs>3)
+      {
+      arg = prhs[3];
+      if notDblMtx(arg) mexErrMsgTxt("STEP arg must be a double float matrix.");
+      if (mxGetM(arg) * mxGetN(arg) != 2)
+         mexErrMsgTxt("STEP arg must contain two elements.");
+      mxMat = mxGetPr(arg);
+      x_step = (int) mxMat[0];
+      y_step = (int) mxMat[1];
+      if ((x_step<1) || (y_step<1))
+         mexErrMsgTxt("STEP values must be greater than zero.");
+      }
+
+  /* ARG 5 (optional): START */
+  if (nrhs>4)
+      {
+      arg = prhs[4];
+      if notDblMtx(arg) mexErrMsgTxt("START arg must be a double float matrix.");
+      if (mxGetM(arg) * mxGetN(arg) != 2)
+        mexErrMsgTxt("START arg must contain two elements.");
+      mxMat = mxGetPr(arg);
+      x_start = (int) mxMat[0];
+      y_start = (int) mxMat[1];
+      if ((x_start<1) || (x_start>x_idim) ||
+          (y_start<1) || (y_start>y_idim))
+         mexErrMsgTxt("START values must lie between 1 and the image dimensions.");
+      }
+  x_start--;  /* convert from Matlab to standard C indexes */
+  y_start--;
+
+  /* ARG 6 (optional): STOP */
+  if (nrhs>5)
+      {
+      if notDblMtx(prhs[5]) mexErrMsgTxt("STOP arg must be double float matrix.");
+      if (mxGetM(prhs[5]) * mxGetN(prhs[5]) != 2)
+         mexErrMsgTxt("STOP arg must contain two elements.");
+      mxMat = mxGetPr(prhs[5]);
+      x_stop = (int) mxMat[0];
+      y_stop = (int) mxMat[1];
+      if ((x_stop<x_start) || (x_stop>x_idim) ||
+          (y_stop<y_start) || (y_stop>y_idim))
+         mexErrMsgTxt("STOP values must lie between START and the image dimensions.");
+      }
+  else
+      {
+      x_stop = x_idim;
+      y_stop = y_idim;
+      }
+          
+  x_rdim = (x_stop-x_start+x_step-1) / x_step;
+  y_rdim = (y_stop-y_start+y_step-1) / y_step;
+  
+  /*  mxFreeMatrix(plhs[0]); */
+  plhs[0] = (mxArray *) mxCreateDoubleMatrix(x_rdim,y_rdim,mxREAL);
+  if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix");
+  result = mxGetPr(plhs[0]);
+
+  temp = mxCalloc(x_fdim*y_fdim, sizeof(double));
+  if (temp == NULL)
+    mexErrMsgTxt("Cannot allocate necessary temporary space");
+
+  /*
+    printf("i(%d, %d), f(%d, %d), r(%d, %d), X(%d, %d, %d), Y(%d, %d, %d), %s\n",
+         x_idim,y_idim,x_fdim,y_fdim,x_rdim,y_rdim,
+         x_start,x_step,x_stop,y_start,y_step,y_stop,edges);
+         */
+
+  if (strcmp(edges,"circular") == 0)
+        internal_wrap_reduce(image, x_idim, y_idim, filt, x_fdim, y_fdim,
+                             x_start, x_step, x_stop, y_start, y_step, y_stop,
+                             result);
+  else internal_reduce(image, x_idim, y_idim, filt, temp, x_fdim, y_fdim,
+                       x_start, x_step, x_stop, y_start, y_step, y_stop,
+                       result, edges);
+
+  mxFree((char *) temp);
+  return;
+  } 
+
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.c
new file mode 100755
index 0000000..98b377d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.c
@@ -0,0 +1,647 @@
+/* 
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;;  File: edges.c
+;;;  Author: Eero Simoncelli
+;;;  Description: Boundary handling routines for use with convolve.c
+;;;  Creation Date: Spring 1987.
+;;;  MODIFIED, 6/96, to operate on double float arrays.
+;;;  MODIFIED by dgp, 4/1/97, to support THINK C.
+;;;  MODIFIED, 8/97: reflect1, reflect2, repeat, extend upgraded to 
+;;;       work properly for non-symmetric filters.  Added qreflect2 to handle
+;;;       even-length QMF's which broke under the reflect2 modification.
+;;;  ----------------------------------------------------------------
+;;;    Object-Based Vision and Image Understanding System (OBVIUS),
+;;;      Copyright 1988, Vision Science Group,  Media Laboratory,  
+;;;              Massachusetts Institute of Technology.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+*/
+
+/* This file contains functions which determine how edges are to be
+handled when performing convolutions of images with linear filters.
+Any edge handling function which is local and linear may be defined,
+except (unfortunately) constants cannot be added.  So to treat the
+edges as if the image is surrounded by a gray field, you must paste it
+into a gray image, convolve, and crop it out...  The main convolution
+functions are called internal_reduce and internal_expand and are
+defined in the file convolve.c.  The idea is that the convolution
+function calls the edge handling function which computes a new filter
+based on the old filter and the distance to the edge of the image.
+For example, reflection is done by reflecting the filter through the
+appropriate axis and summing.  Currently defined functions are listed
+below.
+*/
+
+
+#include <stdio.h>
+#include <math.h>
+#include <string.h>
+#include "convolve.h"
+
+#define sgn(a)  ( ((a)>0)?1:(((a)<0)?-1:0) )
+#define clip(a,mn,mx)  ( ((a)<(mn))?(mn):(((a)>=(mx))?(mx-1):(a)) )
+
+int reflect1(), reflect2(), qreflect2(), repeat(), zero(), Extend(), nocompute();
+int ereflect(), predict();
+
+/* Lookup table matching a descriptive string to the edge-handling function */
+#if !THINK_C
+        static EDGE_HANDLER edge_foos[] =
+          {
+            { "dont-compute", nocompute }, /* zero output for filter touching edge */
+            { "zero",     zero     },   /* zero outside of image */
+            { "repeat",   repeat   },   /* repeat edge pixel */
+            { "reflect1", reflect1 },   /* reflect about edge pixels  */
+            { "reflect2", reflect2 },   /* reflect image, including edge pixels  */
+            { "qreflect2", qreflect2 },   /* reflect image, including edge pixels
+                                             for even-length QMF decompositions */
+            { "extend",   Extend   },   /* extend (reflect & invert) */
+            { "ereflect", ereflect },   /* orthogonal QMF reflection */
+          };
+#else
+        /*
+        This is really stupid, but THINK C won't allow initialization of static variables in
+        a code resource with string addresses. So we do it this way.
+        The 68K code for a MATLAB 4 MEX file can only be created by THINK C.
+        However, for MATLAB 5, we'll be able to use Metrowerks CodeWarrior for both 68K and PPC, so this
+        cludge can be dropped when we drop support for MATLAB 4.
+        Denis Pelli, 4/1/97. 
+        */
+        static EDGE_HANDLER edge_foos[8];
+
+        void InitializeTable(EDGE_HANDLER edge_foos[])
+        {
+                static int i=0;
+                
+                if(i>0) return;
+                edge_foos[i].name="dont-compute";
+                edge_foos[i++].func=nocompute;
+                edge_foos[i].name="zero";
+                edge_foos[i++].func=zero;
+                edge_foos[i].name="repeat";
+                edge_foos[i++].func=repeat;
+                edge_foos[i].name="reflect1";
+                edge_foos[i++].func=reflect1;
+                edge_foos[i].name="reflect2";
+                edge_foos[i++].func=reflect2;
+                edge_foos[i].name="qreflect2";
+                edge_foos[i++].func=qreflect2;
+                edge_foos[i].name="extend";
+                edge_foos[i++].func=Extend;
+                edge_foos[i].name="ereflect";
+                edge_foos[i++].func=ereflect;
+        }
+#endif
+
+/*
+Function looks up an edge handler id string in the structure above, and
+returns the associated function 
+*/
+fptr edge_function(char *edges)
+  {
+  int i;
+
+#if THINK_C
+  InitializeTable(edge_foos);
+#endif
+  for (i = 0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++)
+    if (strcmp(edges,edge_foos[i].name) IS 0)
+      return(edge_foos[i].func);
+  printf("Error: '%s' is not the name of a valid edge-handler!\n",edges);
+  for (i=0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++)
+      {
+      if (i IS 0) printf("  Options are: ");
+      else printf(", ");
+      printf("%s",edge_foos[i].name);
+      }
+  printf("\n");
+  return(0);
+  }
+
+/* 
+---------------- EDGE HANDLER ARGUMENTS ------------------------
+filt - array of filter taps.
+x_dim, y_dim - x and y dimensions of filt.
+x_pos - position of filter relative to the horizontal image edges. Negative
+       values indicate left edge, positive indicate right edge.  Zero 
+       indicates that the filter is not touching either edge.  An absolute
+       value of 1 indicates that the edge tap of the filter is over the 
+       edge pixel of the image.
+y_pos - analogous to x_pos.
+result - array where the resulting filter will go.  The edge
+       of this filter will be aligned with the image for application...
+r_or_e - equal to one of the two constants EXPAND or REDUCE.
+-------------------------------------------------------------------- 
+*/ 
+
+
+/* --------------------------------------------------------------------
+nocompute() - Return zero for values where filter hangs over the edge.
+*/
+
+int nocompute(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  register int i;
+  register int size = x_dim*y_dim;
+
+  if ( (x_pos>1) OR (x_pos<-1) OR (y_pos>1) OR (y_pos<-1) )
+    for (i=0; i<size; i++)  result[i] = 0.0;
+  else
+    for (i=0; i<size; i++)  result[i] = filt[i];
+
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+zero() - Zero outside of image.  Discontinuous, but adds zero energy. */
+
+int zero(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  int filt_sz = x_dim*y_dim;
+  int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_res=y_start;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    if ((y_res >= 0) AND (y_res < filt_sz))
+      for (x_filt=y_filt, x_res=x_start;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        if ((x_res >= 0) AND (x_res < x_dim))
+          result[y_res+x_res] = filt[x_filt];
+  return(0);
+  }
+
+
+/* --------------------------------------------------------------------
+reflect1() - Reflection through the edge pixels.  Continuous, but
+discontinuous first derivative.  This is the right thing to do if you
+are subsampling by 2, since it maintains parity (even pixels positions
+remain even, odd ones remain odd).
+*/       
+
+int reflect1(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  int filt_sz = x_dim*y_dim;
+  register int y_filt,x_filt, y_res, x_res;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); 
+  int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0);
+  int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+  int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2);
+  int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2));
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  if (r_or_e IS REDUCE)
+    for (y_filt=0, y_res=y_overhang-y_base;
+         y_filt<filt_sz;
+         y_filt+=x_dim, y_res+=x_dim)
+      for (x_filt=y_filt, x_res=x_overhang-x_base;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        result[ABS(y_base-ABS(y_res)) + ABS(x_base-ABS(x_res))]
+          += filt[x_filt];
+  else {
+      y_overhang = ABS(y_overhang); 
+      x_overhang = ABS(x_overhang);
+      for (y_res=y_base, y_filt = y_base-y_overhang;
+           y_filt > y_base-filt_sz;
+           y_filt-=x_dim, y_res-=x_dim)
+          {
+          for (x_res=x_base, x_filt=x_base-x_overhang;
+               x_filt > x_base-x_dim;
+               x_res--, x_filt--)
+            result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+          if ((x_overhang ISNT mx_pos) AND (x_pos ISNT 0))
+            for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang;
+                 x_filt > x_base-x_dim;
+                 x_res--, x_filt--)
+              result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+          }
+      if ((y_overhang ISNT my_pos) AND (y_pos ISNT 0))
+        for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang;
+             y_filt > y_base-filt_sz;
+             y_filt-=x_dim, y_res-=x_dim)
+            {
+            for (x_res=x_base, x_filt=x_base-x_overhang;
+                 x_filt > x_base-x_dim;
+                 x_res--, x_filt--)
+              result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+            if  ((x_overhang ISNT mx_pos) AND (x_pos ISNT 0))
+              for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang;
+                   x_filt > x_base-x_dim;
+                   x_res--, x_filt--)
+                result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+            }
+      }
+
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+reflect2() - Reflect image at boundary.  The edge pixel is repeated,
+then the next pixel, etc.  Continuous, but discontinuous first
+derivative.
+*/
+
+int reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  int filt_sz = x_dim*y_dim;
+  register int y_filt,x_filt, y_res, x_res;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); 
+  int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0);
+  int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+  int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2);
+  int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2));
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  if (r_or_e IS REDUCE)
+    for (y_filt=0, y_res = (y_overhang-y_base) - ((y_pos>0)?x_dim:0);
+         y_filt<filt_sz;
+         y_filt+=x_dim, y_res+=x_dim)
+        {
+        if (y_res IS 0) y_res+=x_dim;
+        for (x_filt=y_filt, x_res = (x_overhang-x_base) - ((x_pos>0)?1:0);
+             x_filt<y_filt+x_dim;
+             x_filt++, x_res++)
+            {
+            if (x_res IS 0) x_res++;
+            result[ABS(y_base-ABS(y_res)+x_dim) + ABS(x_base-ABS(x_res)+1)]
+              += filt[x_filt];
+            }
+        }
+  else {
+      y_overhang = ABS(y_overhang); 
+      x_overhang = ABS(x_overhang);
+      for (y_res=y_base, y_filt = y_base-y_overhang;
+           y_filt > y_base-filt_sz;
+           y_filt-=x_dim, y_res-=x_dim)
+          {
+          for (x_res=x_base, x_filt=x_base-x_overhang;
+               x_filt > x_base-x_dim;
+               x_res--, x_filt--)
+            result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+          if (x_pos ISNT 0)
+            for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1;
+                 x_filt > x_base-x_dim;
+                 x_res--, x_filt--)
+              result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+          }
+       if (y_pos ISNT 0)
+         for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang-x_dim;
+              y_filt > y_base-filt_sz;
+              y_filt-=x_dim, y_res-=x_dim)
+             {
+             for (x_res=x_base, x_filt=x_base-x_overhang;
+                  x_filt > x_base-x_dim;
+                  x_res--, x_filt--)
+               result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+             if (x_pos ISNT 0)
+               for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1;
+                    x_filt > x_base-x_dim;
+                    x_res--, x_filt--)
+                 result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+             }
+      }
+
+  return(0);
+  }
+
+
+/* --------------------------------------------------------------------
+qreflect2() - Modified version of reflect2 that  works properly for 
+even-length QMF filters.
+*/
+
+int qreflect2(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  double *filt, *result;
+  int x_dim, y_dim, x_pos, y_pos, r_or_e;
+  {
+  reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,0);
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+repeat() - repeat edge pixel.  Continuous, with discontinuous first
+derivative.
+*/
+
+int repeat(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res, y_tmp, x_tmp;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); 
+  int x_overhang = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int filt_sz = x_dim*y_dim;
+  int mx_pos = (x_dim/2);
+  int my_pos = x_dim * (y_dim/2);
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  if (r_or_e IS REDUCE)
+    for (y_filt=0, y_res=y_overhang;
+         y_filt<filt_sz;
+         y_filt+=x_dim, y_res+=x_dim)
+      for (x_filt=y_filt, x_res=x_overhang;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        /* Clip the index: */
+        result[((y_res>=0)?((y_res<filt_sz)?y_res:(filt_sz-x_dim)):0) 
+               + ((x_res>=0)?((x_res<x_dim)?x_res:(x_dim-1)):0)]      
+                 += filt[x_filt];
+  else {
+    if ((y_base-y_overhang) ISNT my_pos)
+      for (y_res=y_base, y_filt=y_base-ABS(y_overhang);
+           y_filt > y_base-filt_sz;
+           y_filt-=x_dim, y_res-=x_dim)
+        if ((x_base-x_overhang) ISNT mx_pos)
+          for (x_res=x_base, x_filt=x_base-ABS(x_overhang);
+               x_filt > x_base-x_dim;
+               x_res--, x_filt--)
+            result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+        else  /* ((x_base-x_overhang) IS mx_pos) */
+          for (x_res=x_base, x_filt=x_base-ABS(x_overhang);
+               x_filt > x_base-x_dim;
+               x_filt--, x_res--)
+            for(x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--)
+              result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_tmp)];
+    else /* ((y_base-y_overhang) IS my_pos) */
+      for (y_res=y_base, y_filt=y_base-ABS(y_overhang);
+           y_filt > y_base-filt_sz;
+           y_filt-=x_dim, y_res-=x_dim)
+        for (y_tmp=y_filt; y_tmp > y_base-filt_sz; y_tmp-=x_dim)
+          if  ((x_base-x_overhang) ISNT mx_pos)
+            for (x_res=x_base, x_filt=x_base-ABS(x_overhang);
+                 x_filt > x_base-x_dim;
+                 x_filt--, x_res--)
+              result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_tmp)+ABS(x_filt)];
+          else /* ((x_base-x_overhang) IS mx_pos) */
+            for (x_res=x_base, x_filt=x_base-ABS(x_overhang);
+                 x_filt > x_base-x_dim;
+                 x_filt--, x_res--)
+              for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--)
+                result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_tmp)+ABS(x_tmp)];
+    } /* End, if r_or_e IS EXPAND */
+
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+extend() - Extend image by reflecting and inverting about edge pixel
+value.  Maintains continuity in intensity AND first derivative (but
+not higher derivs).
+*/
+
+int Extend(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  int filt_sz = x_dim*y_dim;
+  register int y_filt,x_filt, y_res,x_res, y_tmp, x_tmp;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); 
+  int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0);
+  int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2);
+  int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  /* Modeled on reflect1() */
+  if (r_or_e IS REDUCE)
+    for (y_filt=0, y_res=y_overhang;
+         y_filt<filt_sz;
+         y_filt+=x_dim, y_res+=x_dim)
+      if ((y_res>=0) AND (y_res<filt_sz))
+        for (x_filt=y_filt, x_res=x_overhang;
+             x_filt<y_filt+x_dim;
+             x_filt++, x_res++)
+          if ((x_res>=0) AND (x_res<x_dim))
+            result[y_res+x_res] += filt[x_filt];
+          else
+              {
+              result[y_res+ABS(x_base-ABS(x_res-x_base))] -= filt[x_filt];
+              result[y_res+x_base] += 2*filt[x_filt];
+              }
+      else
+        for (x_filt=y_filt, x_res=x_overhang;
+             x_filt<y_filt+x_dim;
+             x_filt++, x_res++)
+          if ((x_res>=0) AND (x_res<x_dim))
+              {
+              result[ABS(y_base-ABS(y_res-y_base))+x_res] -= filt[x_filt];
+              result[y_base+x_res] += 2*filt[x_filt];
+              }
+          else
+              {
+              result[ABS(y_base-ABS(y_res-y_base))+ABS(x_base-ABS(x_res-x_base))] 
+                -= filt[x_filt];
+              result[y_base+x_base] += 2*filt[x_filt];
+              }
+  else {  /* r_or_e ISNT  REDUCE */
+      y_overhang = ABS(y_overhang); 
+      x_overhang = ABS(x_overhang);
+      for (y_res=y_base, y_filt = y_base-y_overhang;
+           y_filt > y_base-filt_sz;
+           y_filt-=x_dim, y_res-=x_dim)
+          {
+          for (x_res=x_base, x_filt=x_base-x_overhang;
+               x_filt > x_base-x_dim;
+               x_res--, x_filt--)
+            result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+          if (x_pos ISNT 0)
+            if (x_overhang ISNT mx_pos)
+              for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang;
+                   x_filt > x_base-x_dim;
+                   x_res--, x_filt--)
+                result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)];
+            else /* x_overhang IS mx_pos */
+              for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1;
+                   x_filt > x_base-x_dim;
+                   x_res--, x_filt--)
+                for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--)
+                  result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_filt)+ABS(x_tmp)];
+          }
+       if (y_pos ISNT 0)
+         if (y_overhang ISNT my_pos)
+           for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang;
+                y_filt > y_base-filt_sz;
+                y_filt-=x_dim, y_res-=x_dim)
+               {
+               for (x_res=x_base, x_filt=x_base-x_overhang;
+                    x_filt > x_base-x_dim;
+                    x_res--, x_filt--)
+                 result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)];
+               if ((x_pos ISNT 0) AND (x_overhang ISNT mx_pos))
+                 for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang;
+                      x_filt > x_base-x_dim;
+                      x_res--, x_filt--)
+                   result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)];
+               }
+         else /* y_overhang IS my_pos */
+           for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang-x_dim;
+                y_filt > y_base-filt_sz;
+                y_res-=x_dim, y_filt-=x_dim)
+             for (y_tmp=y_filt; y_tmp > y_base-filt_sz; y_tmp-=x_dim)
+                 {
+                 for (x_res=x_base, x_filt=x_base-x_overhang;
+                      x_filt > x_base-x_dim;
+                      x_res--, x_filt--)
+                   result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_tmp)+ABS(x_filt)];
+                 if ((x_pos ISNT 0) AND (x_overhang IS mx_pos))
+                   for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1;
+                        x_filt > x_base-x_dim;
+                        x_res--, x_filt--)
+                     for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--)
+                       result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_tmp)+ABS(x_tmp)];
+                 }
+      }  /* r_or_e ISNT  REDUCE */
+
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+predict() - Simple prediction.  Like zero, but multiplies the result
+by the reciprocal of the percentage of filter being used.  (i.e. if
+50% of the filter is hanging over the edge of the image, multiply the
+taps being used by 2).  */
+
+int predict(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  register double taps_used = 0.0; /* int *** */
+  register double fraction = 0.0;
+  int filt_sz = x_dim*y_dim;
+  int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_res=y_start;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    if ((y_res >= 0) AND (y_res < filt_sz))
+      for (x_filt=y_filt, x_res=x_start;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        if ((x_res >= 0) AND (x_res < x_dim))
+          {
+            result[y_res+x_res] = filt[x_filt];
+            taps_used += ABS(filt[x_filt]);
+          }
+
+  if (r_or_e IS REDUCE)
+      {
+      /* fraction = ( (double) filt_sz ) / ( (double) taps_used ); */
+      for (i=0; i<filt_sz; i++) fraction += ABS(filt[i]);
+      fraction = ( fraction / taps_used );
+      for (i=0; i<filt_sz; i++) result[i] *= fraction;
+      }
+  return(0);
+  }
+
+
+/* --------------------------------------------------------------------
+Reflect, multiplying tap of filter which is at the edge of the image
+by root 2.  This maintains orthogonality of odd-length linear-phase
+QMF filters, but it is not useful for most applications, since it
+alters the DC level.  */
+
+int ereflect(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); 
+  int filt_sz = x_dim*y_dim;
+  int x_overhang = (x_pos>1)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0);
+  int y_overhang = x_dim * ( (y_pos>1)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0) );
+  int i;
+  double norm,onorm;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  /* reflect at boundary */       
+  for (y_filt=0, y_res=y_overhang;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    for (x_filt=y_filt, x_res=x_overhang;
+         x_filt<y_filt+x_dim;
+         x_filt++, x_res++)
+      result[ABS(y_base-ABS(y_res)) + ABS(x_base-ABS(x_res))]
+        += filt[x_filt];
+
+  /* now multiply edge by root 2 */
+  if (x_pos ISNT 0) 
+    for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim)
+      result[y_filt] *= ROOT2;
+  if (y_pos ISNT 0) 
+    for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++)
+      result[x_filt] *= ROOT2;
+
+  /* now normalize to norm of original filter */
+  for (norm=0.0,i=0; i<filt_sz; i++)
+    norm += (result[i]*result[i]);
+  norm=sqrt(norm);
+
+  for (onorm=0.0,i=0; i<filt_sz; i++)
+    onorm += (filt[i]*filt[i]);
+  onorm = sqrt(onorm);
+
+  norm = norm/onorm;
+  for (i=0; i<filt_sz; i++)
+    result[i] /= norm;
+  return(0);
+  }
+
+
+/* ------- printout stuff for testing ------------------------------
+  printf("Xpos: %d, Ypos: %d", x_pos, y_pos);
+    for (y_filt=0; y_filt<y_dim; y_filt++)
+      {
+      printf("\n");
+      for (x_filt=0; x_filt<x_dim; x_filt++)
+        printf("%6.1f", result[y_filt*x_dim+x_filt]);
+      }
+  printf("\n");
+*/
+
+
+
+/* Local Variables: */
+/* buffer-read-only: t */
+/* End: */
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.mexa64 b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.mexa64
new file mode 100755
index 0000000..4839d1e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/edges.mexa64
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/histo.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/histo.c
new file mode 100755
index 0000000..43a99c7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/histo.c
@@ -0,0 +1,140 @@
+/* 
+[N, X] = histo(MTX, NBINS_OR_BINSIZE, BIN_CENTER)
+  >>> See histo.m for documentation <<<
+  EPS, ported from OBVIUS, 3/97.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  /* Matlab matrices */
+#include <mex.h>
+
+#include <stddef.h>  /* NULL */
+#include <math.h>  /* ceil */
+
+#define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it))
+
+#define PAD 0.49999 /* A hair below 1/2, to avoid roundoff errors */
+#define MAXBINS 20000
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+  {
+  register double temp;
+  register int binnum, i, size;
+  register double *im, binsize;
+  register double origin, *hist, mn, mx, mean;
+  register int nbins;
+  double *bincenters; 
+  mxArray *arg;
+  double *mxMat;
+
+  if (nrhs < 1 ) mexErrMsgTxt("requires at least 1 argument.");
+
+  /* ARG 1: MATRIX  */
+  arg = prhs[0];
+  if notDblMtx(arg) mexErrMsgTxt("MTX arg must be a real non-sparse matrix.");
+  im = mxGetPr(arg);
+  size = (int) mxGetM(arg) * mxGetN(arg);
+
+  /* FIND min, max, mean values of MTX */
+  mn = *im;   mx = *im;  binsize = 0;
+  for (i=1; i<size; i++)
+    {
+      temp = im[i];
+      if (temp < mn)
+        mn = temp;
+      else if (temp > mx)
+        mx = temp;
+      binsize += temp;
+    }
+  mean = binsize / size;
+
+  /* ARG 3: BIN_CENTER */
+  if (nrhs > 2)
+    {
+    arg = prhs[2];
+    if notDblMtx(arg) mexErrMsgTxt("BIN_CENTER arg must be a real scalar.");
+    if (mxGetM(arg) * mxGetN(arg) != 1)
+      mexErrMsgTxt("BIN_CENTER must be a real scalar.");
+    mxMat= mxGetPr(arg);
+    origin = *mxMat;
+    }
+  else
+    origin = mean;
+
+  /* ARG 2: If positive, NBINS.  If negative, -BINSIZE. */
+  if (nrhs > 1)
+    {
+    arg = prhs[1];
+    if notDblMtx(arg) mexErrMsgTxt("NBINS_OR_BINSIZE arg must be a real scalar.");
+    if (mxGetM(arg) * mxGetN(arg) != 1)
+      mexErrMsgTxt("NBINS_OR_BINSIZE must be a real scalar.");
+    mxMat= mxGetPr(arg);
+    binsize = *mxMat;
+    }
+  else
+    {
+    binsize = 101;  /* DEFAULT: 101 bins */
+    }
+
+  /* --------------------------------------------------
+     Adjust origin, binsize, nbins such that
+        mx <= origin + (nbins-1)*binsize + PAD*binsize
+        mn >= origin - PAD*binsize
+     -------------------------------------------------- */
+  if (binsize < 0)              /* user specified BINSIZE */
+      {
+      binsize = -binsize;
+      origin -= binsize * ceil((origin-mn-PAD*binsize)/binsize);
+      nbins = (int) ceil((mx-origin-PAD*binsize)/binsize) + 1;
+      }
+  else                          /* user specified NBINS */
+      {
+      nbins = (int) (binsize + 0.5);    /* round to int */
+      if (nbins == 0)
+        mexErrMsgTxt("NBINS must be greater than zero.");
+      binsize = (mx-mn)/(nbins-1+2*PAD);   /* start with lower bound */
+      i = ceil((origin-mn-binsize/2)/binsize);
+      if ( mn < (origin-i*binsize-PAD*binsize) )
+        binsize = (origin-mn)/(i+PAD);
+      else if ( mx > (origin+(nbins-1-i)*binsize+PAD*binsize) )
+        binsize = (mx-origin)/((nbins-1-i)+PAD);
+      origin -= binsize * ceil((origin-mn-PAD*binsize)/binsize);
+      }
+
+  if (nbins > MAXBINS)
+      {
+      mexPrintf("nbins: %d,  MAXBINS: %d\n",nbins,MAXBINS);
+      mexErrMsgTxt("Number of histo bins has exceeded maximum");
+      }
+
+  /* Allocate hist  and xvals */
+  plhs[0] = (mxArray *) mxCreateDoubleMatrix(1,nbins,mxREAL);
+  if (plhs[0] == NULL) mexErrMsgTxt("Error allocating result matrix");
+  hist = mxGetPr(plhs[0]);
+
+  if (nlhs > 1)
+      {
+      plhs[1] = (mxArray *) mxCreateDoubleMatrix(1,nbins,mxREAL);
+      if (plhs[1] == NULL) mexErrMsgTxt("Error allocating result matrix");
+      bincenters = mxGetPr(plhs[1]);
+      for (i=0, temp=origin; i<nbins; i++, temp+=binsize)
+        bincenters[i] = temp;
+      }
+
+  for (i=0; i<size; i++)
+      {
+      binnum = (int) ((im[i] - origin)/binsize + 0.5);
+      if ((binnum < nbins) && (binnum >= 0))
+        (hist[binnum]) += 1.0;
+      else
+        printf("HISTO warning: value %f outside of range [%f,%f]\n",
+               im[i], origin-0.5*binsize, origin+(nbins-0.5)*binsize);
+      }
+
+  return;
+  }      
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.c
new file mode 100755
index 0000000..8fa1224
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.c
@@ -0,0 +1,52 @@
+/* 
+RES = innerProd(MAT);
+  Computes mat'*mat  
+  Odelia Schwartz, 8/97.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  
+
+#include <stdio.h>
+#include <ctype.h>
+#include <math.h>
+#include <strings.h>
+#include <stdlib.h>
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+{
+   register double *res, *mat, tmp;
+   register int len, wid, i, k, j, jlen, ilen, imat, jmat;
+   mxArray *arg;
+   
+   /* get matrix input argument */
+   /* should be matrix in which num rows >= num columns */
+   arg=prhs[0];                     
+   mat= mxGetPr(arg);
+   len = (int) mxGetM(arg);
+   wid = (int) mxGetN(arg);
+   if ( wid > len )
+     printf("innerProd: Warning: width %d is greater than length %d.\n",wid,len); 
+   plhs[0] = (mxArray *) mxCreateDoubleMatrix(wid,wid,mxREAL);
+   if (plhs[0] == NULL) 
+     mexErrMsgTxt(sprintf("Error allocating %dx%d result matrix",wid,wid));
+   res = mxGetPr(plhs[0]);
+
+   for(i=0, ilen=0; i<wid; i++, ilen+=len)
+     {
+      for(j=i, jlen=ilen; j<wid; j++, jlen+=len)
+         {
+            tmp = 0.0;
+            for(k=0, imat=ilen, jmat=jlen; k<len; k++, imat++, jmat++)
+              tmp += mat[imat]*mat[jmat];
+            res[i*wid+j] = tmp;
+            res[j*wid+i] = tmp;
+         }
+   }
+   return;
+
+}
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.dll b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.dll
new file mode 100755
index 0000000..40ac896
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.dll
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexa64 b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexa64
new file mode 100755
index 0000000..e31a97e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexa64
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexglx b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexglx
new file mode 100755
index 0000000..749a5b5
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexglx
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexlx b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexlx
new file mode 100755
index 0000000..151b08f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexlx
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexmac b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexmac
new file mode 100755
index 0000000..6e11fcd
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexmac
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexsol b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexsol
new file mode 100755
index 0000000..d761ed8
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/innerProd.mexsol
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/pointOp.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/pointOp.c
new file mode 100755
index 0000000..6ffcb45
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/pointOp.c
@@ -0,0 +1,126 @@
+/* 
+RES = pointOp(IM, LUT, ORIGIN, INCREMENT, WARNINGS)
+  >>> See pointOp.m for documentation <<<
+  EPS, ported from OBVIUS, 7/96.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  /* Matlab matrices */
+#include <mex.h>
+
+#include <stddef.h>  /* NULL */
+
+#define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it))
+
+void internal_pointop();
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+  {
+  double *image, *lut, *res;
+  double origin, increment;
+  int x_dim, y_dim, lx_dim, ly_dim;
+  int warnings = 1;
+  mxArray *arg;
+  double *mxMat;
+
+  if (nrhs < 4 ) mexErrMsgTxt("requres  at least 4 args.");
+
+  /* ARG 1: IMAGE  */
+  arg = prhs[0];
+  if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a real non-sparse matrix.");
+  image = mxGetPr(arg);
+  x_dim = (int) mxGetM(arg); /* X is inner index! */
+  y_dim = (int) mxGetN(arg);
+
+  /* ARG 2: Lookup table */
+  arg = prhs[1];
+  if notDblMtx(arg) mexErrMsgTxt("LUT arg must be a real non-sparse matrix.");
+  lut = mxGetPr(arg);
+  lx_dim = (int) mxGetM(arg); /* X is inner index! */
+  ly_dim = (int) mxGetN(arg);
+  if ( (lx_dim != 1) && (ly_dim != 1) )
+    mexErrMsgTxt("Lookup table must be a row or column vector.");
+
+  /* ARG 3: ORIGIN */
+  arg = prhs[2];
+  if notDblMtx(arg) mexErrMsgTxt("ORIGIN arg must be a real scalar.");
+  if (mxGetM(arg) * mxGetN(arg) != 1)
+     mexErrMsgTxt("ORIGIN arg must be a real scalar.");
+  mxMat = mxGetPr(arg);
+  origin = *mxMat;
+
+  /* ARG 4: INCREMENT */
+  arg = prhs[3];
+  if notDblMtx(arg) mexErrMsgTxt("INCREMENT arg must be a real scalar.");
+  if (mxGetM(arg) * mxGetN(arg) != 1)
+     mexErrMsgTxt("INCREMENT arg must be a real scalar.");
+  mxMat = mxGetPr(arg);
+  increment = *mxMat;
+
+  /* ARG 5: WARNINGS */
+  if (nrhs>4)
+    {
+    arg = prhs[4];
+    if notDblMtx(arg) mexErrMsgTxt("WARINGS arg must be a real scalar.");
+    if (mxGetM(arg) * mxGetN(arg) != 1)
+      mexErrMsgTxt("WARNINGS arg must be a real scalar.");
+    mxMat = mxGetPr(arg);
+    warnings = (int) *mxMat;
+    }
+
+  plhs[0] = (mxArray *)  mxCreateDoubleMatrix(x_dim,y_dim,mxREAL);
+  if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix");
+  res = mxGetPr(plhs[0]);
+      
+  internal_pointop(image, res, x_dim*y_dim, lut, lx_dim*ly_dim, 
+                   origin, increment, warnings);
+  return;
+  }      
+
+
+/* Use linear interpolation on a lookup table.
+   Taken from OBVIUS.  EPS, Spring, 1987.
+ */
+void internal_pointop (im, res, size, lut, lutsize, origin, increment, warnings)
+  register double *im, *res, *lut;
+  register double origin, increment; 
+  register int size, lutsize, warnings;
+  {
+  register int i, index;
+  register double pos;
+  register int l_unwarned = warnings;
+  register int r_unwarned = warnings;
+
+  lutsize = lutsize - 2;        /* Maximum index value */
+  if (increment > 0)
+    for (i=0; i<size; i++)
+        {
+        pos = (im[i] - origin) / increment;
+        index = (int) pos;   /* Floor */
+        if (index < 0)
+            {
+            index = 0;
+            if (l_unwarned)
+                {
+                mexPrintf("Warning: Extrapolating to left of lookup table...\n");
+                l_unwarned = 0;
+                }
+            }
+        else if (index > lutsize)
+            {
+            index = lutsize;
+            if (r_unwarned)
+                {
+                mexPrintf("Warning: Extrapolating to right of lookup table...\n");
+                r_unwarned = 0;
+                }
+            }
+        res[i] = lut[index] + (lut[index+1] - lut[index]) * (pos - index);
+        }
+  else
+    for (i=0; i<size; i++) res[i] = *lut;
+  }
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/range2.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/range2.c
new file mode 100755
index 0000000..b84f4e1
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/range2.c
@@ -0,0 +1,56 @@
+/* 
+[MIN, MAX] = range2(MTX)
+  >>> See range2.m for documentation <<<
+  EPS, 3/97.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  /* Matlab matrices */
+#include <mex.h>
+
+#include <stddef.h>  /* NULL */
+
+#define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it))
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+  {
+  register double temp, mn, mx;
+  register double *mtx;
+  register int i, size;
+  mxArray *arg;
+
+  if (nrhs != 1) mexErrMsgTxt("requires 1 argument.");
+
+  /* ARG 1: MATRIX  */
+  arg = prhs[0];
+  if notDblMtx(arg) mexErrMsgTxt("MTX arg must be a real non-sparse matrix.");
+  mtx = mxGetPr(arg);
+  size = (int) mxGetM(arg) * mxGetN(arg);
+
+  /* FIND min, max values of MTX */
+  mn = *mtx;   mx = *mtx;  
+  for (i=1; i<size; i++)
+      {
+      temp = mtx[i];
+      if (temp < mn)
+        mn = temp;
+      else if (temp > mx)
+        mx = temp;
+      }
+
+  plhs[0] = (mxArray *) mxCreateDoubleMatrix(1,1,mxREAL);
+  if (plhs[0] == NULL) mexErrMsgTxt("Error allocating result matrix");
+  plhs[1] = (mxArray *) mxCreateDoubleMatrix(1,1,mxREAL);
+  if (plhs[1] == NULL) mexErrMsgTxt("Error allocating result matrix");
+  mtx = mxGetPr(plhs[0]);
+  mtx[0] = mn;
+  mtx = mxGetPr(plhs[1]);
+  mtx[0] = mx;
+
+  return;
+  }      
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/upConv.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/upConv.c
new file mode 100755
index 0000000..3708f8a
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/upConv.c
@@ -0,0 +1,195 @@
+/* 
+RES = upConv(IM, FILT, EDGES, STEP, START, STOP, RES);
+  >>> See upConv.m for documentation <<<
+  This is a matlab interface to the internal_expand function. 
+  EPS, 7/96.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  /* Matlab matrices */
+#include <mex.h>
+
+#include "convolve.h"
+
+#define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it))
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+  {
+  double *image,*filt, *temp, *result, *orig_filt;
+  int x_fdim, y_fdim, x_idim, y_idim;
+  int orig_x = 0, orig_y, x, y;
+  int x_rdim, y_rdim;
+  int x_start = 1;
+  int x_step = 1;
+  int y_start = 1;
+  int y_step = 1;
+  int x_stop, y_stop;
+  mxArray *arg;
+  double *mxMat;
+  char edges[15] = "reflect1";
+
+  if (nrhs<2) mexErrMsgTxt("requres at least 2 args.");
+
+  /* ARG 1: IMAGE  */
+  arg = prhs[0];
+  if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a non-sparse double float matrix.");
+  image = mxGetPr(arg);
+  x_idim = (int) mxGetM(arg); /* X is inner index! */
+  y_idim = (int) mxGetN(arg);
+
+  /* ARG 2: FILTER */
+  arg = prhs[1];
+  if notDblMtx(arg) mexErrMsgTxt("FILTER arg must be non-sparse double float matrix.");  filt = mxGetPr(arg);
+  x_fdim = (int) mxGetM(arg); 
+  y_fdim = (int) mxGetN(arg);
+
+  /* ARG 3 (optional): EDGES */
+  if (nrhs>2) 
+          {
+          if (!mxIsChar(prhs[2]))
+                mexErrMsgTxt("EDGES arg must be a string.");
+          mxGetString(prhs[2],edges,15);
+          }
+
+  /* ARG 4 (optional): STEP */
+  if (nrhs>3)
+      {
+      arg = prhs[3];
+      if notDblMtx(arg) mexErrMsgTxt("STEP arg must be double float matrix.");
+      if (mxGetM(arg) * mxGetN(arg) != 2)
+         mexErrMsgTxt("STEP arg must contain two elements.");
+      mxMat = mxGetPr(arg);
+      x_step = (int) mxMat[0];
+      y_step = (int) mxMat[1];
+      if ((x_step<1) || (y_step<1))
+         mexErrMsgTxt("STEP values must be greater than zero.");
+      }
+
+  /* ARG 5 (optional): START */
+  if (nrhs>4)
+      {
+      arg = prhs[4];
+      if notDblMtx(arg) mexErrMsgTxt("START arg must be double float matrix.");
+      if (mxGetM(arg) * mxGetN(arg) != 2)
+        mexErrMsgTxt("START arg must contain two elements.");
+      mxMat = mxGetPr(arg);
+      x_start = (int) mxMat[0];
+      y_start = (int) mxMat[1];
+      if ((x_start<1) || (y_start<1))
+         mexErrMsgTxt("START values must be greater than zero.");
+      }
+  x_start--;  /* convert to standard C indexes */
+  y_start--;
+
+  /* ARG 6 (optional): STOP */
+  if (nrhs>5)
+      {
+      if notDblMtx(prhs[5]) mexErrMsgTxt("STOP arg must be double float matrix.");
+      if (mxGetM(prhs[5]) * mxGetN(prhs[5]) != 2)
+         mexErrMsgTxt("STOP arg must contain two elements.");
+      mxMat = mxGetPr(prhs[5]);
+      x_stop = (int) mxMat[0];
+      y_stop = (int) mxMat[1];
+      if ((x_stop<x_start) || (y_stop<y_start))
+         mexErrMsgTxt("STOP values must be greater than START values.");
+      }
+  else
+      { /* default: make res dims a multiple of STEP size */
+      x_stop = x_step * ((x_start/x_step) + x_idim);
+      y_stop = y_step * ((y_start/y_step) + y_idim);
+      }
+
+  /* ARG 6 (optional): RESULT image */
+  if (nrhs>6)
+      {
+      arg = prhs[6];
+      if notDblMtx(arg) mexErrMsgTxt("RES arg must be double float matrix.");
+
+      /* 7/10/97: Returning one of the args causes problems with Matlab's memory 
+         manager, so we don't return anything if the result image is passed */
+      /*  plhs[0] = arg;  */
+      result = mxGetPr(arg);
+      x_rdim =  (int) mxGetM(arg); /* X is inner index! */
+      y_rdim = (int) mxGetN(arg);
+      if  ((x_stop>x_rdim) || (y_stop>y_rdim))
+        mexErrMsgTxt("STOP values must within image dimensions.");
+      }
+  else
+      {
+      x_rdim = x_stop; 
+      y_rdim = y_stop;
+      /*  x_rdim = x_step * ((x_stop+x_step-1)/x_step);
+          y_rdim = y_step * ((y_stop+y_step-1)/y_step);  */
+
+      plhs[0] = (mxArray *) mxCreateDoubleMatrix(x_rdim,y_rdim,mxREAL);
+      if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix");
+      result = mxGetPr(plhs[0]);
+      }
+          
+  if ( (((x_stop-x_start+x_step-1) / x_step) != x_idim) ||
+       (((y_stop-y_start+y_step-1) / y_step) != y_idim) )
+    {
+      mexPrintf("Im dims: [%d %d]\n",x_idim,y_idim);
+      mexPrintf("Start:   [%d %d]\n",x_start,y_start);
+      mexPrintf("Step:    [%d %d]\n",x_step,y_step);
+      mexPrintf("Stop:    [%d %d]\n",x_stop,y_stop);
+      mexPrintf("Res dims: [%d %d]\n",x_rdim,y_rdim);
+      mexErrMsgTxt("Image sizes and upsampling args are incompatible!");
+    }
+
+  /* upConv has a bug for even-length kernels when using the 
+     reflect1, extend, or repeat edge-handlers */
+  if ((!strcmp(edges,"reflect1") || !strcmp(edges,"extend") || !strcmp(edges,"repeat"))
+      &&
+      ((x_fdim%2 == 0) || (y_fdim%2 == 0)))
+      {
+      orig_filt = filt;
+      orig_x = x_fdim; 
+      orig_y = y_fdim;
+      x_fdim = 2*(orig_x/2)+1;
+      y_fdim = 2*(orig_y/2)+1;
+      filt = mxCalloc(x_fdim*y_fdim, sizeof(double));
+      if (filt == NULL)
+        mexErrMsgTxt("Cannot allocate necessary temporary space");
+      for (y=0; y<orig_y; y++)
+        for (x=0; x<orig_x; x++)
+            filt[y*x_fdim + x] = orig_filt[y*orig_x + x];
+      }
+
+  if ((x_fdim > x_rdim) || (y_fdim > y_rdim))
+    {
+    mexPrintf("Filter: [%d %d], ",x_fdim,y_fdim);
+    mexPrintf("Result: [%d %d]\n",x_rdim,y_rdim);
+    mexErrMsgTxt("FILTER dimensions larger than RESULT dimensions.");
+    }
+ 
+  temp = mxCalloc(x_fdim*y_fdim, sizeof(double));
+  if (temp == NULL)
+    mexErrMsgTxt("Cannot allocate necessary temporary space");
+
+  /*
+  printf("(%d, %d), (%d, %d), (%d, %d), (%d, %d), (%d, %d), %s\n",
+         x_idim,y_idim,x_fdim,y_fdim,x_rdim,y_rdim,
+         x_start,x_step,y_start,y_step,edges);
+         */
+
+  if (strcmp(edges,"circular") == 0)
+        internal_wrap_expand(image, filt, x_fdim, y_fdim,
+                             x_start, x_step, x_stop, y_start, y_step, y_stop,
+                             result, x_rdim, y_rdim);
+  else internal_expand(image, filt, temp, x_fdim, y_fdim,
+                       x_start, x_step, x_stop, y_start, y_step, y_stop,
+                       result, x_rdim, y_rdim, edges);
+
+  if (orig_x) mxFree((char *) filt);
+  mxFree((char *) temp);
+
+  return;
+  }      
+
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/wrap.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/wrap.c
new file mode 100755
index 0000000..a081123
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/MEX/wrap.c
@@ -0,0 +1,281 @@
+/* 
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;;  File: wrap.c
+;;;  Author: Eero Simoncelli
+;;;  Description: Circular convolution on 2D images.
+;;;  Creation Date: Spring, 1987.
+;;;  MODIFICATIONS:
+;;;      6/96: Switched array types to double float.
+;;;      2/97: made more robust and readable.  Added STOP arguments.
+;;;  ----------------------------------------------------------------
+;;;    Object-Based Vision and Image Understanding System (OBVIUS),
+;;;      Copyright 1988, Vision Science Group,  Media Laboratory,  
+;;;              Massachusetts Institute of Technology.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+*/
+
+#include <stdlib.h>
+
+#include "convolve.h"
+
+/*
+ --------------------------------------------------------------------
+ Performs correlation (i.e., convolution with filt(-x,-y)) of FILT
+ with IMAGE followed by subsampling (a.k.a. REDUCE in Burt&Adelson81).
+ The operations are combined to avoid unnecessary computation of the
+ convolution samples that are to be discarded in the subsampling
+ operation.  The convolution is done in 9 sections so that mod
+ operations are not performed unnecessarily.  The subsampling lattice
+ is specified by the START, STEP and STOP parameters.
+ -------------------------------------------------------------------- */
+
+/* abstract out the inner product computation */
+#define INPROD(YSTART,YIND,XSTART,XIND) \
+      { \
+      sum=0.0; \
+      for (y_im=YSTART, filt_pos=0, x_filt_stop=x_fdim; \
+           x_filt_stop<=filt_size; \
+           y_im++, x_filt_stop+=x_fdim) \
+         for (x_im=XSTART ; \
+              filt_pos<x_filt_stop; \
+              filt_pos++, x_im++) \
+           sum += imval[YIND][XIND] * filt[filt_pos]; \
+      result[res_pos] = sum; \
+      }
+
+int internal_wrap_reduce(image, x_dim, y_dim, filt, x_fdim, y_fdim,
+                     x_start, x_step, x_stop, y_start, y_step, y_stop, 
+                     result)
+  register image_type *filt, *result;
+  register int x_dim, y_dim, x_fdim, y_fdim;
+  image_type *image;
+  int x_start, x_step, x_stop, y_start, y_step, y_stop;
+  {
+  register double sum;
+  register int filt_size = x_fdim*y_fdim;
+  image_type **imval;
+  register int filt_pos, x_im, y_im, x_filt_stop;
+  register int x_pos, y_pos, res_pos;
+  int x_ctr_stop = x_dim - x_fdim + 1;
+  int y_ctr_stop = y_dim - y_fdim + 1;
+  int x_ctr_start = 0;
+  int y_ctr_start = 0;
+  int x_fmid = x_fdim/2;
+  int y_fmid = y_fdim/2;
+  
+  /* shift start/stop coords to filter upper left hand corner */
+  x_start -= x_fmid;   y_start -=  y_fmid;
+  x_stop -=  x_fmid;   y_stop -=  y_fmid;
+
+  if (x_stop < x_ctr_stop) x_ctr_stop = x_stop;
+  if (y_stop < y_ctr_stop) y_ctr_stop = y_stop;
+
+  /* Set up pointer array for rows */
+  imval = (image_type **) malloc(y_dim*sizeof(image_type *));
+  if (imval IS NULL)
+      {
+      printf("INTERNAL_WRAP: Failed to allocate temp array!");
+      return(-1);
+      }
+  for (y_pos=y_im=0;y_pos<y_dim;y_pos++,y_im+=x_dim)
+    imval[y_pos] = (image+y_im);
+  
+  for (res_pos=0, y_pos=y_start;              /* TOP ROWS */
+       y_pos<y_ctr_start;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start;
+         x_pos<x_ctr_start;
+         x_pos+=x_step, res_pos++)
+      INPROD(y_pos+y_dim, y_im%y_dim, x_pos+x_dim, x_im%x_dim)
+
+    for (; 
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos+y_dim, y_im%y_dim, x_pos, x_im)
+
+    for (; 
+         x_pos<x_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos+y_dim, y_im%y_dim, x_pos, x_im%x_dim)
+    } /* end TOP ROWS */
+  
+  for (;                        /* MID ROWS */
+       y_pos<y_ctr_stop;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start;
+         x_pos<x_ctr_start;
+         x_pos+=x_step, res_pos++)
+      INPROD(y_pos, y_im, x_pos+x_dim, x_im%x_dim)
+
+    for (;                      /* CENTER SECTION */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos, y_im, x_pos, x_im)
+
+    for (; 
+         x_pos<x_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos, y_im, x_pos, x_im%x_dim)
+    } /* end MID ROWS */
+  
+  for (;                        /* BOTTOM ROWS */
+       y_pos<y_stop;
+       y_pos+=y_step) 
+     {
+    for (x_pos=x_start;
+         x_pos<x_ctr_start;
+         x_pos+=x_step, res_pos++)
+      INPROD(y_pos, y_im%y_dim, x_pos+x_dim, x_im%x_dim)
+
+    for (; 
+         x_pos<x_ctr_stop; 
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos, y_im%y_dim, x_pos, x_im)
+
+    for (;
+         x_pos<x_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos, y_im%y_dim, x_pos, x_im%x_dim)
+    } /* end BOTTOM ROWS */
+
+  free ((image_type **) imval);
+
+  return(0);
+  }     /* end of internal_wrap_reduce */
+
+
+
+/*
+ --------------------------------------------------------------------
+ Performs upsampling (padding with zeros) followed by convolution of
+ FILT with IMAGE (a.k.a. EXPAND in Burt&Adelson81).  The operations
+ are combined to avoid unnecessary multiplication of filter samples
+ with zeros in the upsampled image.  The convolution is done in 9
+ sections so that mod operation is not performed unnecessarily.
+ Arguments are described in the comment above internal_wrap_reduce.
+
+ WARNING: this subroutine destructively modifes the RESULT image, so
+ the user must zero the result before invocation!
+ -------------------------------------------------------------------- */
+
+/* abstract out the inner product computation */
+#define INPROD2(YSTART,YIND,XSTART,XIND) \
+      { \
+      val = image[im_pos]; \
+      for (y_res=YSTART, filt_pos=0, x_filt_stop=x_fdim; \
+           x_filt_stop<=filt_size; \
+           y_res++, x_filt_stop+=x_fdim) \
+        for (x_res=XSTART; \
+             filt_pos<x_filt_stop; \
+             filt_pos++, x_res++) \
+          imval[YIND][XIND] += val * filt[filt_pos]; \
+      }
+
+int internal_wrap_expand(image, filt, x_fdim, y_fdim,
+              x_start, x_step, x_stop, y_start, y_step, y_stop,
+              result, x_dim, y_dim)
+  register image_type *filt, *result;
+  register int x_fdim, y_fdim, x_dim, y_dim;
+  image_type *image; 
+  int x_start, x_step, x_stop, y_start, y_step, y_stop;
+  {
+  register double val;
+  register int filt_size = x_fdim*y_fdim;
+  image_type **imval;
+  register int filt_pos, x_res, y_res, x_filt_stop;
+  register int x_pos, y_pos, im_pos;
+  int x_ctr_stop = x_dim - x_fdim + 1;
+  int y_ctr_stop = y_dim - y_fdim + 1;
+  int x_ctr_start = 0;
+  int y_ctr_start = 0;
+  int x_fmid = x_fdim/2;
+  int y_fmid = y_fdim/2;
+  
+  /* shift start/stop coords to filter upper left hand corner */
+  x_start -= x_fmid;   y_start -=  y_fmid;
+  x_stop -=  x_fmid;   y_stop -=  y_fmid;
+
+  if (x_stop < x_ctr_stop) x_ctr_stop = x_stop;
+  if (y_stop < y_ctr_stop) y_ctr_stop = y_stop;
+
+  /* Set up pointer array for rows */
+  imval = (image_type **) malloc(y_dim*sizeof(image_type *));
+  if (imval IS NULL)
+      {
+      printf("INTERNAL_WRAP: Failed to allocate temp array!");
+      return(-1);
+      }
+  for (y_pos=y_res=0;y_pos<y_dim;y_pos++,y_res+=x_dim)
+    imval[y_pos] = (result+y_res);
+  
+  for (im_pos=0, y_pos=y_start; /* TOP ROWS */
+       y_pos<y_ctr_start;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start; 
+         x_pos<x_ctr_start;
+         x_pos+=x_step, im_pos++)
+      INPROD2(y_pos+y_dim, y_res%y_dim, x_pos+x_dim, x_res%x_dim)
+        
+    for (; 
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos+y_dim, y_res%y_dim, x_pos, x_res)
+
+    for (; 
+         x_pos<x_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos+y_dim, y_res%y_dim, x_pos, x_res%x_dim)
+    } /* end TOP ROWS */
+  
+  for (;                        /* MID ROWS */
+       y_pos<y_ctr_stop;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start; 
+         x_pos<x_ctr_start;
+         x_pos+=x_step, im_pos++)
+      INPROD2(y_pos, y_res, x_pos+x_dim, x_res%x_dim)
+        
+    for (;                      /* CENTER SECTION */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos, y_res, x_pos, x_res)
+
+    for (; 
+         x_pos<x_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos, y_res, x_pos, x_res%x_dim)
+    } /* end MID ROWS */
+  
+  for (;                        /* BOTTOM ROWS */
+       y_pos<y_stop;
+       y_pos+=y_step) 
+    {
+    for (x_pos=x_start; 
+         x_pos<x_ctr_start;
+         x_pos+=x_step, im_pos++)
+      INPROD2(y_pos, y_res%y_dim, x_pos+x_dim, x_res%x_dim)
+        
+    for (; 
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos, y_res%y_dim, x_pos, x_res)
+
+    for (; 
+         x_pos<x_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos, y_res%y_dim, x_pos, x_res%x_dim)
+    } /* end BOTTOM ROWS */
+
+  free ((image_type **) imval);
+  return(0);
+  } /* end of internal_wrap_expand */
+
+
+
+/* Local Variables: */
+/* buffer-read-only: t */
+/* End: */
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/README b/SD-VBS/benchmarks/texture_synthesis/src/matlab/README
new file mode 100755
index 0000000..8f339f3
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/README
@@ -0,0 +1,55 @@
+This package contains some MatLab tools for multi-scale image
+processing.  Briefly, the tools include:
+  - Recursive multi-scale image decompositions (pyramids), including
+    Laplacian pyramids, QMFs, Wavelets, and steerable pyramids.  These
+    operate on 1D or 2D signals of arbitrary dimension.  Data
+    structures are compatible with the MatLab wavelet toolbox.
+  - Fast 2D convolution routines, with subsampling and boundary-handling.
+  - Fast point-operations, histograms, histogram-matching.
+  - Fast synthetic image generation: sine gratings, zone plates, fractals, etc.
+  - Display routines for images and pyramids.  These include several
+    auto-scaling options, rounding to integer zoom factors to avoid 
+    resampling artifacts, and useful labeling (dimensions and gray-range).
+
+The package is available as a gnu-zipped UNIX "tar" file, 
+accessible from the web page: 
+  http://www.cns.nyu.edu/~lcv/software.html
+
+The code works in Matlab versions 4.2 and higher, and has been fully tested
+on Linux and Macintosh OSX platforms (it should, however, port easily to
+others).  To use the code (these lines are for UNIX):
+  1) gunzip matlabPyrTools.tar.gz       # unpack g'zipped file
+  2) tar tvf matlabPyrTools.tar         # view contents
+  3) tar xvf matlabPyrTools.tar         # extract contents
+  4) rm matlabPyrTools.tar              # delete tarfile
+  5) Run matlab, and execute:
+      path(<pathname-of-matlabPyrTools>, path);
+      help matlabPyrTools
+
+A few functions are actually MEX interfaces to C code.  These are
+contained in the subdirectory called MEX.  The MEX files have been
+tested on Sun (Solaris), LinuX on a Pentium platform, and Macintosh
+OSX on a PowerPC, but should not be difficult to compile on most other
+platforms.  Source code is included in the MEX directory, as well as
+Make files.  I've included pre-compiled versions for a number of
+platforms (Solaris,Linux,Mac,Windows).  To make sure these are in your
+matlab path, you can do *one* of the following:
+  1) Create a symbolic link (or macintosh "alias") for the relavent files 
+     in the main matlabPyrTools directory,   or
+  2) Copy the relavent files into the main matlabPyrTools directory, or 
+  3) Put the MEX subdirectory in your matlab path.
+
+Some example script files showing usage of the code are in the
+directory <dir>/TUTORIALS.  There is a README file in that directory
+describing the contents.
+
+Incremental changes to the code are documented in the ChangeLog file.
+
+Comments/Suggestions/Bugs to:
+  Eero P. Simoncelli
+  Associate Professor,
+  Center for Neural Science, and
+  Courant Institute for Mathematical Sciences
+  New York University
+  eero.simoncelli@nyu.edu
+  http://www.cns.nyu.edu/~eero/
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr1s.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr1s.m
new file mode 100755
index 0000000..81f428d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr1s.m
@@ -0,0 +1,63 @@
+% [newX, snr1, M] = adjustCorr1s(X, Cx, MODE, p) 
+%
+% Linearly adjust variables in X to have correlation Cx.
+% Rows of X and newX are samples of a (random) row-vector, such that:
+%    1:  newX = X * M    
+%    2:  newX' * newX = Cx 
+%
+% MODE is optional:
+%   0 => choose randomly from the space of linear solutions
+%   1 => simplest soln
+%   2 => minimize angle change (DEFAULT) 
+%   3 => SVD minimal vector change soln
+%
+% p is optional:
+%   Imposes an intermediate value of correlation between the current one
+%   C and Cx:
+%       Cx' = (1-p)*C + p*Cx;
+%   DEFAULT is p=1.
+
+%  EPS, 11/23/97.
+
+function [newX, snr1, M] = adjustCorr1s(X,Co,mode,p)
+
+if (exist('mode') ~= 1)
+  mode = 2;
+end
+
+if (exist('p') ~= 1)
+  p = 1;
+end
+
+C = innerProd(X) / size(X,1);
+[E, D] = eig(C);
+D = diag(D);
+[junk,Ind] = sort(D);
+D = diag(sqrt(D(Ind(size(Ind,1):-1:1))));
+E = E(:,Ind(size(Ind,1):-1:1));
+
+Co0 = Co;
+Co = (1-p)*C + p*Co;
+
+[Eo,Do] = eig(Co);
+Do = diag(Do);
+[junk,Ind] = sort(Do);
+Do = diag(sqrt(Do(Ind(size(Ind,1):-1:1))));
+Eo = Eo(:,Ind(size(Ind,1):-1:1));
+
+if (mode == 0)
+  Orth = orth(rand(size(C)));
+elseif (mode == 1) % eye
+  Orth = eye(size(C));
+elseif (mode == 2) % simple
+  Orth = E' * Eo;
+else     % SVD
+  [U,S,V] = svd(D * E' * Eo * inv(Do));
+  Orth = U * V';
+end
+
+M =  E * inv(D) * Orth * Do * Eo';
+
+newX = X * M;
+
+snr1=10*log10(sum(sum(Co0.^2))/sum(sum((Co0-C).^2)));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr2s.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr2s.m
new file mode 100755
index 0000000..3bd0c2e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/adjustCorr2s.m
@@ -0,0 +1,99 @@
+% [newX, snr1, snr2, Mx, My] = adjustCorr2s(X, Cx, Y, Cxy, MODE, p) 
+%
+% Linearly adjust variables in X to have correlation Cx, and cross-correlation Cxy.
+% Rows of X, Y, and newX are samples of (random) row-vectors, such that:
+%   1:  newX = X * Mx + Y * My
+%   2:  newX' * newX = Cx
+%   3:  newX' * Y = Cxy
+%
+% MODE is optional:
+%   0 => choose randomly from the space of linear solutions
+%   1 => simplest soln
+%   2 => minimize angle change
+%   3 => Simple rotational (DEFAULT) 
+%   4 => SVD minimal vector change soln
+%
+% p is optional:
+%   Imposes an intermediate value of correlation between the current ones
+%   Bx and Bxy and the specified Cx and Cxy:
+%       Cx' = (1-p)*Bx + p*Cx;
+%       Cxy' = (1-p)*Bxy + p*Cxy;
+%   DEFAULT is p=1.
+
+
+% EPS, 11/25/97
+
+function [newX,snr1,snr2,Mx,My] = adjustCorr2s(X, Cx, Y, Cxy, mode, p)
+
+Warn = 0; % Set to 1 if you want to display warning messages
+if (exist('mode') ~= 1)
+  mode = 3;
+end
+if (exist('p') ~= 1)
+  p = 1;
+end
+
+Bx = innerProd(X) / size(X,1);
+Bxy = (X' * Y) / size(X,1);
+By = innerProd(Y) / size(X,1);
+iBy = inv(By);
+
+Current = Bx - (Bxy * iBy * Bxy');
+Cx0 = Cx;
+Cx = (1-p)*Bx + p*Cx;
+Cxy0 = Cxy;
+Cxy = (1-p)*Bxy + p*Cxy;
+Desired = Cx - (Cxy * iBy * Cxy');
+
+[E, D] = eig(Current);
+D = diag(D);
+if any(D < 0) & Warn
+  ind = find(D<0);
+  fprintf(1,'Warning: negative current eigenvalues: %d\n',D(ind)');
+end
+[junk,Ind] = sort(D);
+D = diag(sqrt(D(Ind(size(Ind,1):-1:1))));
+E = E(:,Ind(size(Ind,1):-1:1));
+
+[Eo,Do] = eig(Desired);
+Do = diag(Do);
+if any(Do < 0) & Warn
+  ind = find(Do<0);
+  fprintf(1,'Warning: negative desired eigenvalues: %d\n',Do(ind)');
+end
+[junk,Ind] = sort(Do);
+Do = diag(sqrt(Do(Ind(size(Ind,1):-1:1))));
+Eo = Eo(:,Ind(size(Ind,1):-1:1));
+
+if (mode == 0)
+  Orth = orth(rand(size(D)));
+elseif (mode == 1) % eye
+  Orth = eye(size(D));
+elseif (mode == 2) % simple
+  A = [ eye(size(Cx)); -iBy*Bxy' ];
+  Ao =  [ eye(size(Cx)); -iBy*Cxy' ];
+  [U,S,V] = svd(E' * pinv(A) * Ao * Eo);
+  Orth = U * V';
+elseif (mode == 3)
+  Orth = E' * Eo;
+else     % SVD
+  A = [ eye(size(Cx)); -iBy*Bxy' ];
+  Ao =  [ eye(size(Cx)); -iBy*Cxy' ];
+  [U,S,V] = svd(D * E' * pinv(A) * Ao * Eo * inv(Do));
+  Orth = U * V';
+end
+
+Mx =  E * inv(D) * Orth * Do * Eo';
+My =  iBy * (Cxy' - Bxy' * Mx);
+newX = X * Mx + Y * My;
+
+if Cx0~=Bx,
+        snr1=10*log10(sum(sum(Cx0.^2))/sum(sum((Cx0-Bx).^2)));
+else
+        snr1 = Inf;
+end
+if Cxy0~=Bxy,
+        snr2=10*log10(sum(sum(Cxy0.^2))/sum(sum((Cxy0-Bxy).^2)));
+else
+        snr2 = Inf;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/binomialFilter.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/binomialFilter.m
new file mode 100755
index 0000000..e5670c7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/binomialFilter.m
@@ -0,0 +1,18 @@
+% KERNEL = binomialFilter(size)
+%
+% Returns a vector of binomial coefficients of order (size-1) .
+
+% Eero Simoncelli, 2/97.
+
+function [kernel] = binomialFilter(sz)
+
+if (sz < 2)
+  error('size argument must be larger than 1');
+end
+
+kernel = [0.5 0.5]';
+
+for n=1:sz-2
+  kernel = conv([0.5 0.5]', kernel);
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/blur.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/blur.m
new file mode 100755
index 0000000..f993d09
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/blur.m
@@ -0,0 +1,28 @@
+% RES = blur(IM, LEVELS, FILT)
+%
+% Blur an image, by filtering and downsampling LEVELS times
+% (default=1), followed by upsampling and filtering LEVELS times.  The
+% blurring is done with filter kernel specified by FILT (default =
+% 'binom5'), which can be a string (to be passed to namedFilter), a
+% vector (applied separably as a 1D convolution kernel in X and Y), or
+% a matrix (applied as a 2D convolution kernel).  The downsampling is
+% always by 2 in each direction.
+
+% Eero Simoncelli, 3/04.
+
+function res = blur(im, nlevs, filt)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('nlevs') ~= 1) 
+  nlevs = 1;
+end
+
+if (exist('filt') ~= 1) 
+  filt = 'binom5';
+end
+
+%------------------------------------------------------------
+
+res = upBlur(blurDn(im,nlevs,filt));
\ No newline at end of file
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/blurDn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/blurDn.m
new file mode 100755
index 0000000..8120c04
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/blurDn.m
@@ -0,0 +1,59 @@
+% RES = blurDn(IM, LEVELS, FILT)
+%
+% Blur and downsample an image.  The blurring is done with filter
+% kernel specified by FILT (default = 'binom5'), which can be a string
+% (to be passed to namedFilter), a vector (applied separably as a 1D
+% convolution kernel in X and Y), or a matrix (applied as a 2D
+% convolution kernel).  The downsampling is always by 2 in each
+% direction.
+%
+% The procedure is applied recursively LEVELS times (default=1).
+
+% Eero Simoncelli, 3/97.
+
+function res = blurDn(im, nlevs, filt)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('nlevs') ~= 1) 
+  nlevs = 1;
+end
+
+if (exist('filt') ~= 1) 
+  filt = 'binom5';
+end
+
+%------------------------------------------------------------
+
+if isstr(filt)
+  filt = namedFilter(filt);
+end  
+
+filt = filt/sum(filt(:));
+
+if nlevs > 1
+  im = blurDn(im,nlevs-1,filt);
+end
+
+if (nlevs >= 1)
+  if (any(size(im)==1))
+    if (~any(size(filt)==1))
+      error('Cant  apply 2D filter to 1D signal');
+    end
+    if (size(im,2)==1)
+      filt = filt(:);
+    else
+      filt = filt(:)';
+    end
+    res = corrDn(im,filt,'reflect1',(size(im)~=1)+1);
+  elseif (any(size(filt)==1))
+    filt = filt(:);
+    res = corrDn(im,filt,'reflect1',[2 1]);
+    res = corrDn(res,filt','reflect1',[1 2]);
+  else
+    res = corrDn(im,filt,'reflect1',[2 2]);
+  end
+else
+  res = im;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildGpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildGpyr.m
new file mode 100755
index 0000000..3f3d07b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildGpyr.m
@@ -0,0 +1,82 @@
+% [PYR, INDICES] = buildGpyr(IM, HEIGHT, FILT, EDGES)
+%
+% Construct a Gaussian pyramid on matrix IM.
+%
+% HEIGHT (optional) specifies the number of pyramid levels to build. Default
+% is 1+maxPyrHt(size(IM),size(FILT)). 
+% You can also specify 'auto' to use this value.
+%
+% FILT (optional) can be a string naming a standard filter (see
+% namedFilter), or a vector which will be used for (separable)
+% convolution.  Default = 'binom5'.  EDGES specifies edge-handling, and
+% defaults to 'reflect1' (see corrDn).
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+
+% Eero Simoncelli, 6/96.
+
+function [pyr,pind] = buildGpyr(im, ht, filt, edges)
+
+if (nargin < 1)
+  error('First argument (IM) is required');
+end
+
+im_sz = size(im);
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('filt') ~= 1)
+  filt = 'binom5';
+end
+
+if isstr(filt)
+  filt = namedFilter(filt);
+end
+
+if ( (size(filt,1) > 1) & (size(filt,2) > 1) )
+  error('FILT should be a 1D filter (i.e., a vector)');
+else
+  filt = filt(:);
+end
+
+max_ht = 1 + maxPyrHt(im_sz, size(filt,1));
+if ( (exist('ht') ~= 1) | (ht == 'auto') )
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+%------------------------------------------------------------
+
+if (ht <= 1)
+
+  pyr = im(:);
+  pind = im_sz;
+
+else
+
+  if (im_sz(2) == 1)
+    lo2 = corrDn(im, filt, edges, [2 1], [1 1]);
+  elseif (im_sz(1) == 1)
+    lo2 = corrDn(im, filt', edges, [1 2], [1 1]);
+  else
+    lo = corrDn(im, filt', edges, [1 2], [1 1]);
+    lo2 = corrDn(lo, filt, edges, [2 1], [1 1]);
+  end
+  
+  [npyr,nind] = buildGpyr(lo2, ht-1, filt, edges);
+
+  pyr = [im(:); npyr];
+  pind = [im_sz; nind];
+  
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildLpyr.m
new file mode 100755
index 0000000..facb0f3
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildLpyr.m
@@ -0,0 +1,109 @@
+% [PYR, INDICES] = buildLpyr(IM, HEIGHT, FILT1, FILT2, EDGES)
+%
+% Construct a Laplacian pyramid on matrix (or vector) IM.
+%
+% HEIGHT (optional) specifies the number of pyramid levels to build. Default
+% is 1+maxPyrHt(size(IM),size(FILT)).  You can also specify 'auto' to
+% use this value.
+%
+% FILT1 (optional) can be a string naming a standard filter (see
+% namedFilter), or a vector which will be used for (separable)
+% convolution.  Default = 'binom5'.  FILT2 specifies the "expansion"
+% filter (default = filt1).  EDGES specifies edge-handling, and
+% defaults to 'reflect1' (see corrDn).
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+
+% Eero Simoncelli, 6/96.
+
+function [pyr,pind] = buildLpyr(im, ht, filt1, filt2, edges)
+
+if (nargin < 1)
+  error('First argument (IM) is required');
+end
+
+im_sz = size(im);
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('filt1') ~= 1)
+  filt1 = 'binom5';
+end
+ 
+if isstr(filt1)
+  filt1 = namedFilter(filt1);
+end
+
+if ( (size(filt1,1) > 1) & (size(filt1,2) > 1) )
+  error('FILT1 should be a 1D filter (i.e., a vector)');
+else
+  filt1 = filt1(:);
+end
+
+if (exist('filt2') ~= 1)
+  filt2 = filt1;
+end
+
+if isstr(filt2)
+  filt2 = namedFilter(filt2);
+end
+
+if ( (size(filt2,1) > 1) & (size(filt2,2) > 1) )
+  error('FILT2 should be a 1D filter (i.e., a vector)');
+else
+  filt2 = filt2(:);
+end
+
+max_ht = 1 + maxPyrHt(im_sz, max(size(filt1,1), size(filt2,1)));
+if ( (exist('ht') ~= 1) | (ht == 'auto') )
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+%------------------------------------------------------------
+
+if (ht <= 1)
+
+  pyr = im(:);
+  pind = im_sz;
+
+else
+
+  if (im_sz(2) == 1)
+    lo2 = corrDn(im, filt1, edges, [2 1], [1 1]);
+  elseif (im_sz(1) == 1)
+    lo2 = corrDn(im, filt1', edges, [1 2], [1 1]);
+  else
+    lo = corrDn(im, filt1', edges, [1 2], [1 1]);
+    int_sz = size(lo);
+    lo2 = corrDn(lo, filt1, edges, [2 1], [1 1]);
+  end
+
+  [npyr,nind] = buildLpyr(lo2, ht-1, filt1, filt2, edges);
+
+  if (im_sz(1) == 1)
+    hi2 = upConv(lo2, filt2', edges, [1 2], [1 1], im_sz);
+  elseif (im_sz(2) == 1)
+    hi2 = upConv(lo2, filt2, edges, [2 1], [1 1], im_sz);
+  else
+    hi = upConv(lo2, filt2, edges, [2 1], [1 1], int_sz);
+    hi2 = upConv(hi, filt2', edges, [1 2], [1 1], im_sz);
+  end
+
+  hi2 = im - hi2;
+
+  pyr = [hi2(:); npyr];
+  pind = [im_sz; nind];
+
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyr.m
new file mode 100755
index 0000000..101b6d2
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyr.m
@@ -0,0 +1,90 @@
+% [PYR, INDICES, STEERMTX, HARMONICS] = buildSCFpyr(IM, HEIGHT, ORDER, TWIDTH)
+%
+% This is a modified version of buildSFpyr, that constructs a
+% complex-valued steerable pyramid  using Hilbert-transform pairs
+% of filters.  Note that the imaginary parts will *not* be steerable.
+%
+% To reconstruct from this representation, either call reconSFpyr
+% on the real part of the pyramid, *or* call reconSCFpyr which will
+% use both real and imaginary parts (forcing analyticity).
+%
+% Description of this transform appears in: Portilla & Simoncelli,
+% Int'l Journal of Computer Vision, 40(1):49-71, Oct 2000.
+% Further information: http://www.cns.nyu.edu/~eero/STEERPYR/
+
+% Original code: Eero Simoncelli, 5/97.
+% Modified by Javier Portilla to return complex (quadrature pair) channels,
+% 9/97.
+
+function [pyr,pind,steermtx,harmonics] = buildSCFpyr(im, ht, order, twidth)
+
+%-----------------------------------------------------------------
+%% DEFAULTS:
+
+max_ht = floor(log2(min(size(im)))) - 2;
+
+if (exist('ht') ~= 1)
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+if (exist('order') ~= 1)
+  order = 3;
+elseif ((order > 15)  | (order < 0))
+  fprintf(1,'Warning: ORDER must be an integer in the range [0,15]. Truncating.\n');
+  order = min(max(order,0),15);
+else
+  order = round(order);
+end
+nbands = order+1;
+
+if (exist('twidth') ~= 1)
+  twidth = 1;
+elseif (twidth <= 0)
+  fprintf(1,'Warning: TWIDTH must be positive.  Setting to 1.\n');
+  twidth = 1;
+end
+
+%-----------------------------------------------------------------
+%% Steering stuff:
+
+if (mod((nbands),2) == 0)
+  harmonics = [0:(nbands/2)-1]'*2 + 1;
+else
+  harmonics = [0:(nbands-1)/2]'*2;
+end
+
+steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even');
+
+%-----------------------------------------------------------------
+
+dims = size(im);
+ctr = ceil((dims+0.5)/2);
+
+[xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ...
+    ([1:dims(1)]-ctr(1))./(dims(1)/2) );
+angle = atan2(yramp,xramp);
+log_rad = sqrt(xramp.^2 + yramp.^2);
+log_rad(ctr(1),ctr(2)) =  log_rad(ctr(1),ctr(2)-1);
+log_rad  = log2(log_rad);
+
+%% Radial transition function (a raised cosine in log-frequency):
+[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
+Yrcos = sqrt(Yrcos);
+
+YIrcos = sqrt(1.0 - Yrcos.^2);
+lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+imdft = fftshift(fft2(im));
+lo0dft =  imdft .* lo0mask;
+
+[pyr,pind] = buildSCFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands);
+
+hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+hi0dft =  imdft .* hi0mask;
+hi0 = ifft2(ifftshift(hi0dft));
+
+pyr = [real(hi0(:)) ; pyr];
+pind = [size(hi0); pind];
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyrLevs.m
new file mode 100755
index 0000000..bd75695
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSCFpyrLevs.m
@@ -0,0 +1,73 @@
+% [PYR, INDICES] = buildSCFpyrLevs(LODFT, LOGRAD, XRCOS, YRCOS, ANGLE, HEIGHT, NBANDS)
+%
+% Recursive function for constructing levels of a steerable pyramid.  This
+% is called by buildSCFpyr, and is not usually called directly.
+
+% Original code: Eero Simoncelli, 5/97.
+% Modified by Javier Portilla to generate complex bands in 9/97.
+
+function [pyr,pind] = buildSCFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands);
+
+if (ht <= 0)
+
+  lo0 = ifft2(ifftshift(lodft));
+  pyr = real(lo0(:));
+  pind = size(lo0);
+
+else
+
+  bands = zeros(prod(size(lodft)), nbands);
+  bind = zeros(nbands,2);
+
+%  log_rad = log_rad + 1;
+  Xrcos = Xrcos - log2(2);  % shift origin of lut by 1 octave.
+
+  lutsize = 1024;
+  Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize;  % [-2*pi:pi]
+  order = nbands-1;
+  %% divide by sqrt(sum_(n=0)^(N-1)  cos(pi*n/N)^(2(N-1)) )
+  %% Thanks to Patrick Teo for writing this out :)
+  const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order));
+
+%
+%  Ycosn = sqrt(const) * (cos(Xcosn)).^order;
+%
+  % analityc version: only take one lobe
+  alfa= mod(pi+Xcosn,2*pi)-pi;
+  Ycosn = 2*sqrt(const) * (cos(Xcosn).^order) .* (abs(alfa)<pi/2);
+
+  himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+
+  for b = 1:nbands
+    anglemask = pointOp(angle, Ycosn, Xcosn(1)+pi*(b-1)/nbands, Xcosn(2)-Xcosn(1));
+    banddft = ((-i)^(nbands-1)) .* lodft .* anglemask .* himask;
+    band = ifft2(ifftshift(banddft));
+
+%    bands(:,b) = real(band(:));
+    % analytic version: full complex value
+    bands(:,b)=band(:);
+    bind(b,:)  = size(band);
+  end
+
+  dims = size(lodft);
+  ctr = ceil((dims+0.5)/2);
+  lodims = ceil((dims-0.5)/2);
+  loctr = ceil((lodims+0.5)/2);
+  lostart = ctr-loctr+1;
+  loend = lostart+lodims-1;
+
+  log_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2));
+  angle = angle(lostart(1):loend(1),lostart(2):loend(2));
+  lodft = lodft(lostart(1):loend(1),lostart(2):loend(2));
+  YIrcos = abs(sqrt(1.0 - Yrcos.^2));
+  lomask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+
+  lodft = lomask .* lodft;
+
+  [npyr,nind] = buildSCFpyrLevs(lodft, log_rad, Xrcos, Yrcos, angle, ht-1, nbands);
+
+  pyr = [bands(:); npyr];
+  pind = [bind; nind];
+
+end
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyr.m
new file mode 100755
index 0000000..ae67206
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyr.m
@@ -0,0 +1,102 @@
+% [PYR, INDICES, STEERMTX, HARMONICS] = buildSFpyr(IM, HEIGHT, ORDER, TWIDTH)
+%
+% Construct a steerable pyramid on matrix IM, in the Fourier domain.
+% This is similar to buildSpyr, except that:
+%
+%    + Reconstruction is exact (within floating point errors)
+%    + It can produce any number of orientation bands.
+%    - Typically slower, especially for non-power-of-two sizes.
+%    - Boundary-handling is circular.
+%
+% HEIGHT (optional) specifies the number of pyramid levels to build. Default
+% is maxPyrHt(size(IM),size(FILT));
+%
+% The squared radial functions tile the Fourier plane, with a raised-cosine
+% falloff.  Angular functions are cos(theta-k\pi/(K+1))^K, where K is
+% the ORDER (one less than the number of orientation bands, default= 3).
+%
+% TWIDTH is the width of the transition region of the radial lowpass
+% function, in octaves (default = 1, which gives a raised cosine for
+% the bandpass filters).
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+% See the function STEER for a description of STEERMTX and HARMONICS.
+
+% Eero Simoncelli, 5/97.
+% See http://www.cns.nyu.edu/~eero/STEERPYR/ for more
+% information about the Steerable Pyramid image decomposition.
+
+function [pyr,pind,steermtx,harmonics] = buildSFpyr(im, ht, order, twidth)
+
+%-----------------------------------------------------------------
+%% DEFAULTS:
+
+max_ht = floor(log2(min(size(im)))) - 2;
+
+if (exist('ht') ~= 1)
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+if (exist('order') ~= 1)
+  order = 3;
+elseif ((order > 15)  | (order < 0))
+  fprintf(1,'Warning: ORDER must be an integer in the range [0,15]. Truncating.\n');
+  order = min(max(order,0),15);
+else
+  order = round(order);
+end
+nbands = order+1;
+
+if (exist('twidth') ~= 1)
+  twidth = 1;
+elseif (twidth <= 0)
+  fprintf(1,'Warning: TWIDTH must be positive.  Setting to 1.\n');
+  twidth = 1;
+end
+
+%-----------------------------------------------------------------
+%% Steering stuff:
+
+if (mod((nbands),2) == 0)
+  harmonics = [0:(nbands/2)-1]'*2 + 1;
+else
+  harmonics = [0:(nbands-1)/2]'*2;
+end
+
+steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even');
+
+%-----------------------------------------------------------------
+
+dims = size(im);
+ctr = ceil((dims+0.5)/2);
+
+[xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ...
+    ([1:dims(1)]-ctr(1))./(dims(1)/2) );
+angle = atan2(yramp,xramp);
+log_rad = sqrt(xramp.^2 + yramp.^2);
+log_rad(ctr(1),ctr(2)) =  log_rad(ctr(1),ctr(2)-1);
+log_rad  = log2(log_rad);
+
+%% Radial transition function (a raised cosine in log-frequency):
+[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
+Yrcos = sqrt(Yrcos);
+
+YIrcos = sqrt(1.0 - Yrcos.^2);
+lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+imdft = fftshift(fft2(im));
+lo0dft =  imdft .* lo0mask;
+
+[pyr,pind] = buildSFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands);
+
+hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+hi0dft =  imdft .* hi0mask;
+hi0 = ifft2(ifftshift(hi0dft));
+
+pyr = [real(hi0(:)) ; pyr];
+pind = [size(hi0); pind];
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyrLevs.m
new file mode 100755
index 0000000..472d861
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSFpyrLevs.m
@@ -0,0 +1,63 @@
+% [PYR, INDICES] = buildSFpyrLevs(LODFT, LOGRAD, XRCOS, YRCOS, ANGLE, HEIGHT, NBANDS)
+%
+% Recursive function for constructing levels of a steerable pyramid.  This
+% is called by buildSFpyr, and is not usually called directly.
+
+% Eero Simoncelli, 5/97.
+
+function [pyr,pind] = buildSFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands);
+
+if (ht <= 0)
+
+  lo0 = ifft2(ifftshift(lodft));
+  pyr = real(lo0(:));
+  pind = size(lo0);
+
+else
+
+  bands = zeros(prod(size(lodft)), nbands);
+  bind = zeros(nbands,2);
+
+%  log_rad = log_rad + 1;
+  Xrcos = Xrcos - log2(2);  % shift origin of lut by 1 octave.
+
+  lutsize = 1024;
+  Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize;  % [-2*pi:pi]
+  order = nbands-1;
+  %% divide by sqrt(sum_(n=0)^(N-1)  cos(pi*n/N)^(2(N-1)) )
+  %% Thanks to Patrick Teo for writing this out :)
+  const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order));
+  Ycosn = sqrt(const) * (cos(Xcosn)).^order;
+  himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+
+  for b = 1:nbands
+    anglemask = pointOp(angle, Ycosn, Xcosn(1)+pi*(b-1)/nbands, Xcosn(2)-Xcosn(1));
+    banddft = ((-sqrt(-1))^(nbands-1)) .* lodft .* anglemask .* himask;
+    band = ifft2(ifftshift(banddft));
+
+    bands(:,b) = real(band(:));
+    bind(b,:)  = size(band);
+  end
+
+  dims = size(lodft);
+  ctr = ceil((dims+0.5)/2);
+  lodims = ceil((dims-0.5)/2);
+  loctr = ceil((lodims+0.5)/2);
+  lostart = ctr-loctr+1;
+  loend = lostart+lodims-1;
+
+  log_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2));
+  angle = angle(lostart(1):loend(1),lostart(2):loend(2));
+  lodft = lodft(lostart(1):loend(1),lostart(2):loend(2));
+  YIrcos = abs(sqrt(1.0 - Yrcos.^2));
+  lomask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+
+  lodft = lomask .* lodft;
+
+  [npyr,nind] = buildSFpyrLevs(lodft, log_rad, Xrcos, Yrcos, angle, ht-1, nbands);
+
+  pyr = [bands(:); npyr];
+  pind = [bind; nind];
+
+end
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyr.m
new file mode 100755
index 0000000..b2bead6
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyr.m
@@ -0,0 +1,61 @@
+% [PYR, INDICES, STEERMTX, HARMONICS] = buildSpyr(IM, HEIGHT, FILTFILE, EDGES)
+%
+% Construct a steerable pyramid on matrix IM.
+%
+% HEIGHT (optional) specifies the number of pyramid levels to build. Default
+% is maxPyrHt(size(IM),size(FILT)). 
+% You can also specify 'auto' to use this value.
+%
+% FILTFILE (optional) should be a string referring to an m-file that
+% returns the rfilters.  (examples: 'sp0Filters', 'sp1Filters',
+% 'sp3Filters','sp5Filters'.  default = 'sp1Filters'). EDGES specifies
+% edge-handling, and defaults to 'reflect1' (see corrDn).
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+% See the function STEER for a description of STEERMTX and HARMONICS.
+
+% Eero Simoncelli, 6/96.
+% See http://www.cis.upenn.edu/~eero/steerpyr.html for more
+% information about the Steerable Pyramid image decomposition.
+
+function [pyr,pind,steermtx,harmonics] = buildSpyr(im, ht, filtfile, edges)
+
+%-----------------------------------------------------------------
+%% DEFAULTS:
+
+if (exist('filtfile') ~= 1)
+  filtfile = 'sp1Filters';
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+if (isstr(filtfile) & (exist(filtfile) == 2))
+   [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filtfile);
+else
+  fprintf(1,'\nUse buildSFpyr for pyramids with arbitrary numbers of orientation bands.\n');
+  error('FILTFILE argument must be the name of an M-file containing SPYR filters.');
+end
+
+max_ht = maxPyrHt(size(im), size(lofilt,1));
+if ( (exist('ht') ~= 1) | (ht == 'auto') )
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+%-----------------------------------------------------------------
+
+hi0 = corrDn(im, hi0filt, edges);
+lo0 = corrDn(im, lo0filt, edges);
+
+[pyr,pind] = buildSpyrLevs(lo0, ht, lofilt, bfilts, edges);
+
+pyr = [hi0(:) ; pyr];
+pind = [size(hi0); pind];
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyrLevs.m
new file mode 100755
index 0000000..4c00077
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildSpyrLevs.m
@@ -0,0 +1,37 @@
+% [PYR, INDICES] = buildSpyrLevs(LOIM, HEIGHT, LOFILT, BFILTS, EDGES)
+%
+% Recursive function for constructing levels of a steerable pyramid.  This
+% is called by buildSpyr, and is not usually called directly.
+
+% Eero Simoncelli, 6/96.
+
+function [pyr,pind] = buildSpyrLevs(lo0,ht,lofilt,bfilts,edges);
+
+if (ht <= 0)
+
+  pyr = lo0(:);
+  pind = size(lo0);
+
+else
+
+  % Assume square filters:
+  bfiltsz =  round(sqrt(size(bfilts,1)));
+
+  bands = zeros(prod(size(lo0)),size(bfilts,2));
+  bind = zeros(size(bfilts,2),2);
+
+  for b = 1:size(bfilts,2)
+    filt = reshape(bfilts(:,b),bfiltsz,bfiltsz);
+    band = corrDn(lo0, filt, edges);
+    bands(:,b) = band(:);
+    bind(b,:)  = size(band);
+  end
+        
+  lo = corrDn(lo0, lofilt, edges, [2 2], [1 1]);
+  
+  [npyr,nind] = buildSpyrLevs(lo, ht-1, lofilt, bfilts, edges);
+
+  pyr = [bands(:); npyr];
+  pind = [bind; nind];
+        
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildWpyr.m
new file mode 100755
index 0000000..22ae32f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/buildWpyr.m
@@ -0,0 +1,100 @@
+% [PYR, INDICES] = buildWpyr(IM, HEIGHT, FILT, EDGES)
+%
+% Construct a separable orthonormal QMF/wavelet pyramid on matrix (or vector) IM.
+%
+% HEIGHT (optional) specifies the number of pyramid levels to build. Default
+% is maxPyrHt(IM,FILT).  You can also specify 'auto' to use this value.
+%
+% FILT (optional) can be a string naming a standard filter (see
+% namedFilter), or a vector which will be used for (separable)
+% convolution.  Filter can be of even or odd length, but should be symmetric. 
+% Default = 'qmf9'.  EDGES specifies edge-handling, and
+% defaults to 'reflect1' (see corrDn).
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+
+% Eero Simoncelli, 6/96.
+
+function [pyr,pind] = buildWpyr(im, ht, filt, edges)
+
+if (nargin < 1)
+  error('First argument (IM) is required');
+end
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('filt') ~= 1)
+  filt = 'qmf9';
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+if isstr(filt)
+  filt = namedFilter(filt);
+end
+
+if ( (size(filt,1) > 1) & (size(filt,2) > 1) )
+  error('FILT should be a 1D filter (i.e., a vector)');
+else
+  filt = filt(:);
+end
+
+hfilt = modulateFlip(filt);
+
+% Stagger sampling if filter is odd-length:
+if (mod(size(filt,1),2) == 0)
+  stag = 2;
+else
+  stag = 1;
+end
+
+im_sz = size(im);
+
+max_ht = maxPyrHt(im_sz, size(filt,1));
+if ( (exist('ht') ~= 1) | (ht == 'auto') )
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+if (ht <= 0)
+
+  pyr = im(:);
+  pind = im_sz;
+
+else
+
+  if (im_sz(2) == 1)
+    lolo = corrDn(im, filt, edges, [2 1], [stag 1]);
+    hihi = corrDn(im, hfilt, edges, [2 1], [2 1]);
+  elseif (im_sz(1) == 1)
+    lolo = corrDn(im, filt', edges, [1 2], [1 stag]);
+    hihi = corrDn(im, hfilt', edges, [1 2], [1 2]);
+  else
+    lo = corrDn(im, filt, edges, [2 1], [stag 1]);
+    hi = corrDn(im, hfilt, edges, [2 1], [2 1]);
+    lolo = corrDn(lo, filt', edges, [1 2], [1 stag]);
+    lohi = corrDn(hi, filt', edges, [1 2], [1 stag]); % horizontal
+    hilo = corrDn(lo, hfilt', edges, [1 2], [1 2]); % vertical
+    hihi = corrDn(hi, hfilt', edges, [1 2], [1 2]); % diagonal
+  end
+
+  [npyr,nind] = buildWpyr(lolo, ht-1, filt, edges);
+
+  if ((im_sz(1) == 1) | (im_sz(2) == 1))
+    pyr = [hihi(:); npyr];
+    pind = [size(hihi); nind];
+  else
+    pyr = [lohi(:); hilo(:); hihi(:); npyr];
+    pind = [size(lohi); size(hilo); size(hihi); nind];
+  end
+
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/cconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/cconv2.m
new file mode 100755
index 0000000..efba438
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/cconv2.m
@@ -0,0 +1,50 @@
+% RES = CCONV2(MTX1, MTX2, CTR)
+%
+% Circular convolution of two matrices.  Result will be of size of
+% LARGER vector.
+% 
+% The origin of the smaller matrix is assumed to be its center.
+% For even dimensions, the origin is determined by the CTR (optional) 
+% argument:
+%      CTR   origin
+%       0     DIM/2      (default)
+%       1     (DIM/2)+1  
+
+% Eero Simoncelli, 6/96.  Modified 2/97.
+
+function c = cconv2(a,b,ctr)
+
+if (exist('ctr') ~= 1)
+  ctr = 0;
+end
+
+if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
+    large = a; small = b;
+elseif  (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
+    large = b; small = a;
+else
+  error('one arg must be larger than the other in both dimensions!');
+end
+
+ly = size(large,1);
+lx = size(large,2);
+sy = size(small,1);
+sx = size(small,2);
+
+%% These values are the index of the small mtx that falls on the
+%% border pixel of the large matrix when computing the first
+%% convolution response sample:
+sy2 = floor((sy+ctr+1)/2);
+sx2 = floor((sx+ctr+1)/2);
+
+% pad:
+clarge = [ ...
+    large(ly-sy+sy2+1:ly,lx-sx+sx2+1:lx), large(ly-sy+sy2+1:ly,:), ...
+        large(ly-sy+sy2+1:ly,1:sx2-1); ...
+    large(:,lx-sx+sx2+1:lx), large, large(:,1:sx2-1); ...
+    large(1:sy2-1,lx-sx+sx2+1:lx), ...
+        large(1:sy2-1,:), ...
+        large(1:sy2-1,1:sx2-1) ];
+
+c = conv2(clarge,small,'valid');
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/clip.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/clip.m
new file mode 100755
index 0000000..28804f3
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/clip.m
@@ -0,0 +1,32 @@
+% [RES] = clip(IM, MINVALorRANGE, MAXVAL)
+%
+% Clip values of matrix IM to lie between minVal and maxVal:
+%      RES = max(min(IM,MAXVAL),MINVAL)
+% The first argument can also specify both min and max, as a 2-vector.
+% If only one argument is passed, the range defaults to [0,1].
+
+function res = clip(im, minValOrRange, maxVal)
+
+if (exist('minValOrRange') ~= 1) 
+  minVal = 0; 
+  maxVal = 1;
+elseif (length(minValOrRange) == 2)
+  minVal = minValOrRange(1);
+  maxVal = minValOrRange(2);
+elseif (length(minValOrRange) == 1)
+  minVal = minValOrRange;
+  if (exist('maxVal') ~= 1)
+    maxVal=minVal+1;
+  end
+else
+  error('MINVAL must be  a scalar or a 2-vector');
+end
+
+if ( maxVal < minVal )
+  error('MAXVAL should be less than MINVAL');
+end
+
+res = im;
+res(find(im < minVal)) = minVal;
+res(find(im > maxVal)) = maxVal;
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/corrDn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/corrDn.m
new file mode 100755
index 0000000..7e07abf
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/corrDn.m
@@ -0,0 +1,63 @@
+% RES = corrDn(IM, FILT, EDGES, STEP, START, STOP)
+%
+% Compute correlation of matrices IM with FILT, followed by
+% downsampling.  These arguments should be 1D or 2D matrices, and IM
+% must be larger (in both dimensions) than FILT.  The origin of filt
+% is assumed to be floor(size(filt)/2)+1.
+% 
+% EDGES is a string determining boundary handling:
+%    'circular' - Circular convolution
+%    'reflect1' - Reflect about the edge pixels
+%    'reflect2' - Reflect, doubling the edge pixels
+%    'repeat'   - Repeat the edge pixels
+%    'zero'     - Assume values of zero outside image boundary
+%    'extend'   - Reflect and invert
+%    'dont-compute' - Zero output when filter overhangs input boundaries
+%
+% Downsampling factors are determined by STEP (optional, default=[1 1]), 
+% which should be a 2-vector [y,x].
+% 
+% The window over which the convolution occurs is specfied by START 
+% (optional, default=[1,1], and STOP (optional, default=size(IM)).
+% 
+% NOTE: this operation corresponds to multiplication of a signal
+% vector by a matrix whose rows contain copies of the FILT shifted by
+% multiples of STEP.  See upConv.m for the operation corresponding to
+% the transpose of this matrix.
+
+% Eero Simoncelli, 6/96, revised 2/97.
+
+function res = corrDn(im, filt, edges, step, start, stop)
+
+%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
+
+%fprintf(1,'WARNING: You should compile the MEX version of "corrDn.c",\n         found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path.  It is MUCH faster, and provides more boundary-handling options.\n');
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('edges') == 1) 
+  if (strcmp(edges,'reflect1') ~= 1)
+    warning('Using REFLECT1 edge-handling (use MEX code for other options).');
+  end
+end
+
+if (exist('step') ~= 1)
+        step = [1,1];
+end     
+
+if (exist('start') ~= 1)
+        start = [1,1];
+end     
+
+if (exist('stop') ~= 1)
+        stop = size(im);
+end     
+
+%------------------------------------------------------------
+
+% Reverse order of taps in filt, to do correlation instead of convolution
+filt = filt(size(filt,1):-1:1,size(filt,2):-1:1);
+
+tmp = rconv2(im,filt);
+res = tmp(start(1):step(1):stop(1),start(2):step(2):stop(2));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/edges-orig.c b/SD-VBS/benchmarks/texture_synthesis/src/matlab/edges-orig.c
new file mode 100755
index 0000000..1f6a98b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/edges-orig.c
@@ -0,0 +1,494 @@
+/* 
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;;  File: edges.c
+;;;  Author: Eero Simoncelli
+;;;  Description: Boundary handling routines for use with convolve.c
+;;;  Creation Date: Spring 1987.
+;;;  MODIFIED, 6/96, to operate on double float arrays.
+;;;  MODIFIED by dgp, 4/1/97, to support THINK C.
+;;;  ----------------------------------------------------------------
+;;;    Object-Based Vision and Image Understanding System (OBVIUS),
+;;;      Copyright 1988, Vision Science Group,  Media Laboratory,  
+;;;              Massachusetts Institute of Technology.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+*/
+
+/* 
+This file contains functions which determine how edges are to be
+handled when performing convolutions of images with linear filters.
+Any edge handling function which is local and linear may be defined,
+except (unfortunately) constants cannot be added.  So to treat the
+edges as if the image is surrounded by a gray field, you must paste it
+into a gray image, convolve, and crop it out...
+The main convolution function is called internal_filter and is defined
+in the file convolve.c.  The idea is that the convolution function
+calls the edge handling function which computes a new filter based on
+the old filter and the distance to the edge of the image.  For
+example, reflection is done by reflecting the filter through the
+appropriate axis and summing.  Currently defined functions are listed
+below.  
+*/
+
+/*
+#define DEBUG
+*/
+
+#include <stdio.h>
+#include <math.h>
+#include <string.h>
+#include "convolve.h"
+
+#define sgn(a)  ( ((a)>0)?1:(((a)<0)?-1:0) )
+#define clip(a,mn,mx)  ( ((a)<(mn))?(mn):(((a)>=(mx))?(mx-1):(a)) )
+
+int reflect1(), reflect2(), repeat(), zero(), Extend(), nocompute();
+int ereflect(), predict();
+
+/* Lookup table matching a descriptive string to the edge-handling function */
+#if !THINK_C
+        static EDGE_HANDLER edge_foos[] =
+          {
+            { "dont-compute", nocompute }, /* zero output for filter touching edge */
+            { "zero",     zero     },   /* zero outside of image */
+            { "repeat",   repeat   },   /* repeat edge pixel */
+            { "reflect1", reflect1 },   /* reflect about edge pixels  */
+            { "reflect2", reflect2 },   /* reflect image, including edge pixels  */
+            { "extend",   Extend   },   /* extend (reflect & invert) */
+            { "predict",  predict  },   /* predict based on portion covered by filt */
+            { "ereflect", ereflect },   /* orthogonal QMF reflection */
+          };
+#else
+        /*
+        This is really stupid, but THINK C won't allow initialization of static variables in
+        a code resource with string addresses. So we do it this way.
+        The 68K code for a MATLAB 4 MEX file can only be created by THINK C.
+        However, for MATLAB 5, we'll be able to use Metrowerks CodeWarrior for both 68K and PPC, so this
+        cludge can be dropped when we drop support for MATLAB 4.
+        Denis Pelli, 4/1/97. 
+        */
+        static EDGE_HANDLER edge_foos[8];
+
+        void InitializeTable(EDGE_HANDLER edge_foos[])
+        {
+                static int i=0;
+                
+                if(i>0) return;
+                edge_foos[i].name="dont-compute";
+                edge_foos[i++].func=nocompute;
+                edge_foos[i].name="zero";
+                edge_foos[i++].func=zero;
+                edge_foos[i].name="repeat";
+                edge_foos[i++].func=repeat;
+                edge_foos[i].name="reflect1";
+                edge_foos[i++].func=reflect1;
+                edge_foos[i].name="reflect2";
+                edge_foos[i++].func=reflect2;
+                edge_foos[i].name="extend";
+                edge_foos[i++].func=Extend;
+                edge_foos[i].name="predict";
+                edge_foos[i++].func=predict;
+                edge_foos[i].name="ereflect";
+                edge_foos[i++].func=ereflect;
+        }
+#endif
+
+/*
+Function looks up an edge handler id string in the structure above, and
+returns the associated function 
+*/
+fptr edge_function(char *edges)
+  {
+  int i;
+
+#if THINK_C
+  InitializeTable(edge_foos);
+#endif
+  for (i = 0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++)
+    if (strcmp(edges,edge_foos[i].name) == 0)
+      return(edge_foos[i].func);
+  printf("Error: '%s' is not the name of a valid edge-handler!\n",edges);
+  for (i=0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++)
+      {
+      if (i==0) printf("  Options are: ");
+      else printf(", ");
+      printf("%s",edge_foos[i].name);
+      }
+  printf("\n");
+  return(0);
+  }
+
+/* 
+---------------- EDGE HANDLER ARGUMENTS ------------------------
+filt - array of filter taps.
+x_dim, y_dim - x and y dimensions of filt.
+x_pos - position of filter relative to the horizontal image edges. Negative
+       values indicate left edge, positive indicate right edge.  Zero 
+       indicates that the filter is not touching either edge.  An absolute
+       value of 1 indicates that the edge tap of the filter is over the 
+       edge pixel of the image.
+y_pos - analogous to x_pos.
+result - array where the resulting filter will go.  The edge
+       of this filter will be aligned with the image for application...
+f_or_e - equal to one of the two constants EXPAND or FILTER.
+-------------------------------------------------------------------- 
+*/ 
+
+
+/* --------------------------------------------------------------------
+nocompute() - Return zero for values where filter hangs over the edge.
+*/
+
+int nocompute(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int i;
+  register int size = x_dim*y_dim;
+
+  if ( (x_pos>1) OR (x_pos<-1) OR (y_pos>1) OR (y_pos<-1) )
+    for (i=0; i<size; i++)  result[i] = 0.0;
+  else
+    for (i=0; i<size; i++)  result[i] = filt[i];
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+zero() - Zero outside of image.  Discontinuous, but adds zero energy. */
+
+int zero(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  int filt_sz = x_dim*y_dim;
+  int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_res=y_start;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    if ((y_res >= 0) AND (y_res < filt_sz))
+      for (x_filt=y_filt, x_res=x_start;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        if ((x_res >= 0) AND (x_res < x_dim))
+          result[y_res+x_res] = filt[x_filt];
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+repeat() - repeat edge pixel.  Continuous, but content is usually
+different from image.  
+*/
+
+int repeat(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  int filt_sz = x_dim*y_dim;
+  int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_res=y_start;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    for (x_filt=y_filt, x_res=x_start;
+         x_filt<y_filt+x_dim;
+         x_filt++, x_res++)
+      result[((y_res>=0)?((y_res<filt_sz)?y_res:(filt_sz-x_dim)):0) 
+             + ((x_res>=0)?((x_res<x_dim)?x_res:(x_dim-1)):0)]      
+        += filt[x_filt];
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+reflect2() - "Normal" image reflection.  The edge pixel is repeated,
+then the next pixel, etc.  Continuous, attempting to maintain
+"similar" content, but discontinuous first derivative.
+*/
+
+int reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int y_filt,x_filt, y_edge,x_edge;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; 
+  int filt_sz = x_dim*y_dim;
+  int x_edge_dist = (x_pos>0)?(x_pos-x_dim-1):(x_pos+1);
+  int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim-1):(y_pos+1));
+  int i;
+
+  #ifdef DEBUG
+    printf("(%d,%d)  ",y_pos,x_pos);
+    if (x_pos==0) printf("\n");
+  #endif
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_edge=y_edge_dist;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_edge+=x_dim)
+      {
+      if (y_edge IS 0) y_edge+=x_dim;
+      for (x_filt=y_filt, x_edge=x_edge_dist;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_edge++)
+          {
+          if (x_edge IS 0) x_edge++;
+          result[ABS(y_base-ABS(y_edge)+x_dim) + ABS(x_base-ABS(x_edge)+1)]
+            += filt[x_filt];
+          }
+      }
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+reflect1() - Reflection through the edge pixels.  This is the right thing
+to do if you are subsampling by 2, since it maintains parity (even 
+pixels positions remain even, odd ones remain odd). (note: procedure differs 
+depending on f_or_e parameter).  */      
+
+int reflect1(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  int filt_sz = x_dim*y_dim;
+  register int x_start = 0, y_start = 0, x_stop = x_dim, y_stop = filt_sz;
+  register int y_filt,x_filt, y_edge,x_edge;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; 
+  int x_edge_dist = (x_pos>0)?(x_pos-x_dim):((x_pos<0)?(x_pos+1):0);
+  int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim):((y_pos<0)?(y_pos+1):0));
+  int i;
+  int mx_pos = (x_dim/2)+1;
+  int my_pos = (y_dim/2)+1;
+
+  #ifdef DEBUG
+    printf("(%d,%d)  ",y_pos,x_pos);
+    if (x_pos==0) printf("\n");
+  #endif
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  /* if EXPAND and filter is centered on image edge, do not reflect */
+  if (f_or_e IS EXPAND)
+      {
+      if (x_pos IS mx_pos) x_stop = (x_dim+1)/2;
+      else if (x_pos IS -mx_pos) { x_start = x_dim/2; x_edge_dist = 0; }
+
+      if (y_pos IS my_pos) y_stop = x_dim*((y_dim+1)/2);
+      else if (y_pos IS -my_pos) { y_start = x_dim*(y_dim/2); y_edge_dist = 0;}
+      }
+
+  /* reflect at boundary of image */
+  for (y_filt=y_start, y_edge=y_edge_dist;
+       y_filt<y_stop;
+       y_filt+=x_dim, y_edge+=x_dim)
+    for (x_filt=y_filt+x_start, x_edge=x_edge_dist;
+         x_filt<y_filt+x_stop;
+         x_filt++, x_edge++)
+        result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))]
+          += filt[x_filt];
+
+  /* if EXPAND and filter is not centered on image edge, mult edge by 2 */
+    if (f_or_e IS EXPAND)
+      {
+      if ( (ABS(x_pos) ISNT mx_pos) AND (x_pos ISNT 0) )
+        for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim)
+          result[y_filt] += result[y_filt];
+      if ( (ABS(y_pos) ISNT my_pos) AND (y_pos ISNT 0) )
+        for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++)
+          result[x_filt] += result[x_filt];
+      }
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+Extend() - Extend image by reflecting and inverting about edge pixel
+value.  Maintains continuity in intensity AND first derivative (but
+not higher derivs).
+*/
+
+int Extend(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  int filt_sz = x_dim*y_dim;
+  register int x_start = 0, y_start = 0, x_stop = x_dim, y_stop = filt_sz;
+  register int y_filt,x_filt, y_edge,x_edge;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; 
+  int x_edge_dist = (x_pos>0)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0);
+  int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0));
+  int i;
+  int mx_pos = (x_dim/2)+1;
+  int my_pos = (y_dim/2)+1;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  /* if EXPAND and filter is centered on image edge, do not reflect */
+  if (f_or_e IS EXPAND)
+      {
+      if (x_pos IS mx_pos) x_stop = (x_dim+1)/2;
+      else if (x_pos IS -mx_pos) { x_start = x_dim/2; x_edge_dist = 0; }
+
+      if (y_pos IS my_pos) y_stop = x_dim*((y_dim+1)/2);
+      else if (y_pos IS -my_pos) { y_start = x_dim*(y_dim/2); y_edge_dist = 0;}
+      }
+
+  /* reflect at boundary of image */
+  for (y_filt=y_start, y_edge=y_edge_dist;
+       y_filt<y_stop;
+       y_filt+=x_dim, y_edge+=x_dim)
+    for (x_filt=y_filt+x_start, x_edge=x_edge_dist;
+         x_filt<y_filt+x_stop;
+         x_filt++, x_edge++)
+      if (((!y_base AND (sgn(y_edge) IS -1)) /* y overhanging */
+           OR
+           (y_base AND (sgn(y_edge) IS 1)))
+          ISNT                               /* XOR */
+          ((!x_base AND (sgn(x_edge) IS -1)) /* x overhanging */
+           OR
+           (x_base AND (sgn(x_edge) IS 1))))
+          {
+          result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))]
+            -= filt[x_filt];
+          result[clip(y_base+y_edge,0,y_dim) + clip(x_base+x_edge,0,x_dim)]
+            += filt[x_filt] + filt[x_filt];
+          }
+      else result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))]
+          += filt[x_filt];
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+predict() - Simple prediction.  Like zero, but multiplies the result
+by the reciprocal of the percentage of filter being used.  (i.e. if
+50% of the filter is hanging over the edge of the image, multiply the
+taps being used by 2).  */
+
+int predict(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  register double taps_used = 0.0; /* int *** */
+  register double fraction = 0.0;
+  int filt_sz = x_dim*y_dim;
+  int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_res=y_start;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    if ((y_res >= 0) AND (y_res < filt_sz))
+      for (x_filt=y_filt, x_res=x_start;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        if ((x_res >= 0) AND (x_res < x_dim))
+          {
+            result[y_res+x_res] = filt[x_filt];
+            taps_used += ABS(filt[x_filt]);
+          }
+  printf("TU: %f\n",taps_used);
+  if (f_or_e IS FILTER)
+      {
+      /* fraction = ( (double) filt_sz ) / ( (double) taps_used ); */
+      for (i=0; i<filt_sz; i++) fraction += ABS(filt[i]);
+      fraction = ( fraction / taps_used );
+      for (i=0; i<filt_sz; i++) result[i] *= fraction;
+      }
+  return(0);
+  }
+
+
+/* --------------------------------------------------------------------
+Reflect, multiplying tap of filter which is at the edge of the image
+by root 2.  This maintains orthogonality of odd-length linear-phase
+QMF filters, but it is not useful for most applications, since it
+alters the DC level.  */
+
+int ereflect(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int y_filt,x_filt, y_edge,x_edge;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ( (y_pos>0)?(y_dim-1):0 ); 
+  int filt_sz = x_dim*y_dim;
+  int x_edge_dist = (x_pos>1)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0);
+  int y_edge_dist = x_dim * ( (y_pos>1)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0) );
+  int i;
+  double norm,onorm;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  /* reflect at boundary */       
+  for (y_filt=0, y_edge=y_edge_dist;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_edge+=x_dim)
+    for (x_filt=y_filt, x_edge=x_edge_dist;
+         x_filt<y_filt+x_dim;
+         x_filt++, x_edge++)
+      result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))]
+        += filt[x_filt];
+
+  /* now multiply edge by root 2 */
+  if (x_pos ISNT 0) 
+    for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim)
+      result[y_filt] *= ROOT2;
+  if (y_pos ISNT 0) 
+    for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++)
+      result[x_filt] *= ROOT2;
+
+  /* now normalize to norm of original filter */
+  for (norm=0.0,i=0; i<filt_sz; i++)
+    norm += (result[i]*result[i]);
+  norm=sqrt(norm);
+
+  for (onorm=0.0,i=0; i<filt_sz; i++)
+    onorm += (filt[i]*filt[i]);
+  onorm = sqrt(onorm);
+
+  norm = norm/onorm;
+  for (i=0; i<filt_sz; i++)
+    result[i] /= norm;
+  return(0);
+  }
+
+
+/* ------- printout stuff for testing ------------------------------
+  printf("Xpos: %d, Ypos: %d", x_pos, y_pos);
+    for (y_filt=0; y_filt<y_dim; y_filt++)
+      {
+      printf("\n");
+      for (x_filt=0; x_filt<x_dim; x_filt++)
+        printf("%6.1f", result[y_filt*x_dim+x_filt]);
+      }
+  printf("\n");
+*/
+
+
+
+/* Local Variables: */
+/* buffer-read-only: t */
+/* End: */
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/einstein.pgm b/SD-VBS/benchmarks/texture_synthesis/src/matlab/einstein.pgm
new file mode 100755
index 0000000..99b974c
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/einstein.pgm
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/entropy2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/entropy2.m
new file mode 100755
index 0000000..68a2a9f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/entropy2.m
@@ -0,0 +1,31 @@
+% E = ENTROPY2(MTX,BINSIZE) 
+% 
+% Compute the first-order sample entropy of MTX.  Samples of VEC are
+% first discretized.  Optional argument BINSIZE controls the
+% discretization, and defaults to 256/(max(VEC)-min(VEC)).
+%
+% NOTE: This is a heavily  biased estimate of entropy when you
+% don't have much data.
+
+% Eero Simoncelli, 6/96.
+
+function res = entropy2(mtx,binsize)
+
+%% Ensure it's a vector, not a matrix.
+vec = mtx(:);
+[mn,mx] = range2(vec);
+
+if (exist('binsize') == 1)
+  nbins = max((mx-mn)/binsize, 1);
+else
+  nbins = 256;
+end
+  
+[bincount,bins] = histo(vec,nbins);
+
+%% Collect non-zero bins:
+H = bincount(find(bincount));
+H = H/sum(H);
+
+res = -sum(H .* log2(H));
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/expand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/expand.m
new file mode 100755
index 0000000..5f6e4d9
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/expand.m
@@ -0,0 +1,34 @@
+function te = expand(t,f)
+
+% Expand spatially an image t in a factor f 
+% in X and in Y.
+% t may be complex.
+% It fills in with zeros in the Fourier domain.
+%       te = expand(t, f)
+% See also: shrink.m
+% JPM, May 95, Instituto de Optica, CSIC, Madrid.
+
+[my mx]=size(t);
+my=f*my;
+mx=f*mx;
+Te=zeros(my,mx);
+T=f^2*fftshift(fft2(t));
+y1=my/2+2-my/(2*f);
+y2=my/2+my/(2*f);
+x1=mx/2+2-mx/(2*f);
+x2=mx/2+mx/(2*f);
+Te(y1:y2,x1:x2)=T(2:my/f,2:mx/f);
+Te(y1-1,x1:x2)=T(1,2:mx/f)/2;
+Te(y2+1,x1:x2)=((T(1,mx/f:-1:2)/2)').';
+Te(y1:y2,x1-1)=T(2:my/f,1)/2;
+Te(y1:y2,x2+1)=((T(my/f:-1:2,1)/2)').';
+esq=T(1,1)/4;
+Te(y1-1,x1-1)=esq;
+Te(y1-1,x2+1)=esq;
+Te(y2+1,x1-1)=esq;
+Te(y2+1,x2+1)=esq;
+Te=fftshift(Te);
+te=ifft2(Te);
+if all(imag(t)==0),
+        te = real(te);
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/factorial.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/factorial.m
new file mode 100755
index 0000000..9255f43
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/factorial.m
@@ -0,0 +1,16 @@
+%% RES = factorial(NUM)
+%
+% Factorial function that works on matrices (matlab's does not).
+
+% EPS, 11/02
+
+function res = factorial(num)
+
+res = ones(size(num));
+
+ind = find(num > 0);
+if ( ~isempty(ind) )
+  subNum = num(ind);
+  res(ind) = subNum .* factorial(subNum-1);
+end
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/feynman.pgm b/SD-VBS/benchmarks/texture_synthesis/src/matlab/feynman.pgm
new file mode 100755
index 0000000..7d14101
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/feynman.pgm
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/histo.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/histo.m
new file mode 100755
index 0000000..8da36e5
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/histo.m
@@ -0,0 +1,58 @@
+% [N,X] = histo(MTX, nbinsOrBinsize, binCenter);
+%
+% Compute a histogram of (all) elements of MTX.  N contains the histogram
+% counts, X is a vector containg the centers of the histogram bins.
+%
+% nbinsOrBinsize (optional, default = 101) specifies either
+% the number of histogram bins, or the negative of the binsize.
+%
+% binCenter (optional, default = mean2(MTX)) specifies a center position
+% for (any one of) the histogram bins.
+%
+% How does this differ from MatLab's HIST function?  This function:
+%   - allows uniformly spaced bins only.
+%   +/- operates on all elements of MTX, instead of columnwise.
+%   + is much faster (approximately a factor of 80 on my machine).
+%   + allows specification of number of bins OR binsize.  Default=101 bins.
+%   + allows (optional) specification of binCenter.
+
+% Eero Simoncelli, 3/97.
+
+function [N, X] = histo(mtx, nbins, binCtr)
+
+%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
+
+%fprintf(1,'WARNING: You should compile the MEX version of "histo.c",\n         found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path.  It is MUCH faster.\n');
+
+mtx = mtx(:);
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+[mn,mx] = range2(mtx);
+
+if (exist('binCtr') ~= 1) 
+  binCtr =  mean(mtx);
+end
+
+if (exist('nbins') == 1) 
+  if (nbins < 0)
+    binSize = -nbins;
+  else
+    binSize = ((mx-mn)/nbins);
+    tmpNbins = round((mx-binCtr)/binSize) - round((mn-binCtr)/binSize);
+    if (tmpNbins ~= nbins)
+      warning('Using %d bins instead of requested number (%d)',tmpNbins,nbins);
+    end
+  end
+else
+  binSize = ((mx-mn)/101);
+end
+
+firstBin = binCtr + binSize*round( (mn-binCtr)/binSize );
+
+tmpNbins = round((mx-binCtr)/binSize) - round((mn-binCtr)/binSize);
+
+bins = firstBin + binSize*[0:tmpNbins];
+
+[N, X] = hist(mtx, bins);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/histoMatch.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/histoMatch.m
new file mode 100755
index 0000000..ab82782
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/histoMatch.m
@@ -0,0 +1,35 @@
+% RES = histoMatch(MTX, N, X)
+%
+% Modify elements of MTX so that normalized histogram matches that
+% specified by vectors X and N, where N contains the histogram counts
+% and X the histogram bin positions (see histo).
+
+% Eero Simoncelli, 7/96.
+
+function res = histoMatch(mtx, N, X)
+
+if ( exist('histo') == 3 )
+  [oN, oX] = histo(mtx(:), size(X(:),1));
+else
+  [oN, oX] = hist(mtx(:), size(X(:),1));
+end
+
+oStep = oX(2) - oX(1);
+oC = [0, cumsum(oN)]/sum(oN);
+oX = [oX(1)-oStep/2, oX+oStep/2];
+
+N = N(:)';
+X = X(:)';
+N = N + mean(N)/(1e8);   %% HACK: no empty bins ensures nC strictly monotonic
+
+nStep = X(2) - X(1);
+nC = [0, cumsum(N)]/sum(N);
+nX = [X(1)-nStep/2, X+nStep/2];
+
+nnX = interp1(nC, nX, oC, 'linear');
+
+if ( exist('pointOp') == 3 )
+  res = pointOp(mtx, nnX, oX(1), oStep);
+else
+  res = reshape(interp1(oX, nnX, mtx(:)),size(mtx,1),size(mtx,2));
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/ifftshift.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/ifftshift.m
new file mode 100755
index 0000000..2ade297
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/ifftshift.m
@@ -0,0 +1,15 @@
+% [RES] = ifftshift (MTX)
+%
+% Inverse of MatLab's FFTSHIFT.  That is,
+%     ifftshift(fftshift(MTX)) = MTX
+%   for any size MTX.
+
+% Eero Simoncelli, 2/97.
+
+function [res]  = ifftshift(mtx)
+
+sz = size(mtx);
+DC = ceil((sz+1)./2);                   % location of DC term in a matlab fft.
+
+res = [mtx(DC(1):sz(1), DC(2):sz(2)) , mtx(DC(1):sz(1), 1:DC(2)-1); ...
+       mtx(1:DC(1)-1, DC(2):sz(2)) , mtx(1:DC(1)-1, 1:DC(2)-1)];
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/imGradient.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/imGradient.m
new file mode 100755
index 0000000..23187e3
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/imGradient.m
@@ -0,0 +1,48 @@
+% [dx, dy] = imGradient(im, edges) 
+%
+% Compute the gradient of the image using smooth derivative filters
+% optimized for accurate direction estimation.  Coordinate system
+% corresponds to standard pixel indexing: X axis points rightward.  Y
+% axis points downward.  EDGES specify boundary handling (see corrDn
+% for options).
+
+% EPS, 1997.
+% original filters from Int'l Conf Image Processing, 1994.
+% updated filters 10/2003.
+% Added to matlabPyrTools 10/2004.
+
+function [dx, dy] = imGradient(im, edges) 
+
+%% 1D smoothing and differentiation kernels.
+%% See Farid & Simoncelli, IEEE Trans Image Processing, 13(4):496-508, April 2004.
+
+if (exist('edges') ~= 1)
+    edges = 'dont-compute';
+end
+
+gp = [0.037659 0.249153 0.426375 0.249153 0.037659]';
+gd = [-0.109604 -0.276691 0.000000 0.276691 0.109604]';
+
+dx = corrDn(corrDn(im, gp, edges), gd', edges);
+dy = corrDn(corrDn(im, gd, edges), gp', edges);
+
+return 
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%%% TEST:
+
+%%Make a ramp with random slope and direction 
+dir = 2*pi*rand - pi;
+slope = 10*rand;
+
+sz = 32
+im = mkRamp(sz, dir, slope);
+[dx,dy] = imGradient(im);
+showIm(dx + sqrt(-1)*dy);
+
+ctr = (sz*sz/2)+sz/2;
+slopeEst = sqrt(dx(ctr).^2 + dy(ctr).^2);
+dirEst = atan2(dy(ctr), dx(ctr));
+
+[slope, slopeEst]
+[dir, dirEst]
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/imStats.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/imStats.m
new file mode 100755
index 0000000..3d79b4c
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/imStats.m
@@ -0,0 +1,41 @@
+% imStats(IM1,IM2)
+%
+% Report image (matrix) statistics.
+% When called on a single image IM1, report min, max, mean, stdev, 
+% and kurtosis.
+% When called on two images (IM1 and IM2), report min, max, mean, 
+% stdev of the difference, and also SNR (relative to IM1).
+
+% Eero Simoncelli, 6/96.
+
+function [] = imStats(im1,im2)
+
+if (~isreal(im1))
+  error('Args must be real-valued matrices');  
+end
+
+if (exist('im2') == 1)
+  difference = im1 - im2;
+  [mn,mx] = range2(difference);
+  mean = mean2(difference);
+  v = var2(difference,mean);
+  if (v < realmin) 
+    snr = Inf;
+  else
+    snr = 10 * log10(var2(im1)/v);
+  end
+  fprintf(1, 'Difference statistics:\n');
+  fprintf(1, '  Range: [%c, %c]\n',mn,mx);
+  fprintf(1, '  Mean: %f,  Stdev (rmse): %f,  SNR (dB): %f\n',...
+      mean,sqrt(v),snr);
+else
+  [mn,mx] = range2(im1);
+  mean = mean2(im1);
+  var = var2(im1);  
+  stdev = sqrt(real(var))+sqrt(imag(var));
+  kurt = kurt2(im1, mean, stdev^2);
+  fprintf(1, 'Image statistics:\n');
+  fprintf(1, '  Range: [%f, %f]\n',mn,mx);
+  fprintf(1, '  Mean: %f,  Stdev: %f,  Kurtosis: %f\n',mean,stdev,kurt);
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/innerProd.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/innerProd.m
new file mode 100755
index 0000000..9252c70
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/innerProd.m
@@ -0,0 +1,12 @@
+% RES = innerProd(MTX)
+%
+% Compute (MTX' * MTX) efficiently (i.e., without copying the matrix)
+
+function res = innerProd(mtx)
+
+%fprintf(1,['WARNING: You should compile the MEX version of' ...
+%          ' "innerProd.c",\n         found in the MEX subdirectory' ...
+%          ' of matlabPyrTools, and put it in your matlab path.' ...
+%          ' It is MUCH faster and requires less memory.\n']);
+
+res = mtx' * mtx;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/kurt2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/kurt2.m
new file mode 100755
index 0000000..8351eb4
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/kurt2.m
@@ -0,0 +1,24 @@
+% K = KURT2(MTX,MEAN,VAR)
+%
+% Sample kurtosis (fourth moment divided by squared variance) 
+% of a matrix.  Kurtosis of a Gaussian distribution is 3.
+%  MEAN (optional) and VAR (optional) make the computation faster.
+
+% Eero Simoncelli, 6/96.
+
+function res = kurt2(mtx, mn, v)
+
+if (exist('mn') ~= 1)
+        mn =  mean(mean(mtx));
+end
+
+if (exist('v') ~= 1)
+        v =  var2(mtx,mn);
+end
+
+if (isreal(mtx))
+  res = mean(mean(abs(mtx-mn).^4)) / (v^2);
+else
+  res = mean(mean(real(mtx-mn).^4)) / (real(v)^2) + ...
+      i*mean(mean(imag(mtx-mn).^4)) / (imag(v)^2);
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/lplot.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/lplot.m
new file mode 100755
index 0000000..3c67d8b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/lplot.m
@@ -0,0 +1,43 @@
+% lplot(VEC, XRANGE)
+%
+% Plot VEC, a vector, in  "lollipop" format.  
+% XRANGE (optional, default = [1,length(VEC)]), should be a 2-vector 
+% specifying the X positions (for labeling purposes) of the first and 
+% last sample of VEC.
+
+% Mark Liberman, Linguistics Dept, UPenn, 1994.
+
+function lplot(x,xrange)
+
+if (exist('xrange') ~= 1)
+  xrange = [1,length(x)];
+end
+
+msize = size(x);
+if ( msize(2) == 1)
+  x = x';
+elseif (msize(1) ~= 1)
+  error('First arg must be a vector');
+end
+
+if (~isreal(x))
+  fprintf(1,'Warning: Imaginary part of signal ignored\n');
+  x = abs(x);
+end
+
+N = length(x);
+index = xrange(1) + (xrange(2)-xrange(1))*[0:(N-1)]/(N-1)
+xinc = index(2)-index(1);
+
+xx = [zeros(1,N);x;zeros(1,N)];
+indexis = [index;index;index];
+xdiscrete = [0 xx(:)' 0];
+idiscrete = [index(1)-xinc indexis(:)' index(N)+xinc];
+
+[mn,mx] = range2(xdiscrete);
+ypad = (mx-mn)/12;                      % MAGIC NUMBER: graph padding
+
+plot(idiscrete, xdiscrete, index, x, 'o');
+axis([index(1)-xinc, index(N)+xinc, mn-ypad, mx+ypad]);
+
+return
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/lpyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/lpyrHt.m
new file mode 100755
index 0000000..d6834d7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/lpyrHt.m
@@ -0,0 +1,11 @@
+% [HEIGHT] = lpyrHt(INDICES)
+%
+% Compute height of Laplacian pyramid with given its INDICES matrix.
+% See buildLpyr.m
+
+% Eero Simoncelli, 6/96.
+
+function [ht] =  lpyrHt(pind)
+
+% Don't count lowpass residual band
+ht = size(pind,1)-1;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/maxPyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/maxPyrHt.m
new file mode 100755
index 0000000..84bcf29
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/maxPyrHt.m
@@ -0,0 +1,25 @@
+% HEIGHT = maxPyrHt(IMSIZE, FILTSIZE)
+%
+% Compute maximum pyramid height for given image and filter sizes.
+% Specifically: the number of corrDn operations that can be sequentially
+% performed when subsampling by a factor of 2.
+
+% Eero Simoncelli, 6/96.
+
+function height = maxPyrHt(imsz, filtsz)
+
+imsz = imsz(:);
+filtsz = filtsz(:);
+
+if any(imsz == 1) % 1D image
+  imsz = prod(imsz);
+  filtsz = prod(filtsz);
+elseif any(filtsz == 1)              % 2D image, 1D filter
+  filtsz = [filtsz(1); filtsz(1)];
+end
+
+if any(imsz < filtsz)
+  height = 0;
+else
+  height = 1 + maxPyrHt( floor(imsz/2), filtsz ); 
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mccExcludedFiles.log b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mccExcludedFiles.log
new file mode 100755
index 0000000..2c5359b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mccExcludedFiles.log
@@ -0,0 +1,11 @@
+This file contains the list of various toolbox functions that are not 
+included in the CTF file. An error will be thrown if any of these functions
+ are called at run-time. Some of these functions may be from toolboxes 
+that you are not using in your application. The reason for this is that 
+these toolboxes have overloaded some methods that are called by your code. 
+If you know which toolboxes are being used by your code, you can use the -p
+ flag with the -N flag to list these toolboxes explicitly. This will 
+cause MATLAB Compiler to only look for functions in the specified toolbox 
+directories in addition to the MATLAB directories. Refer to the MCC 
+documentation for more information on this.
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mean2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mean2.m
new file mode 100755
index 0000000..177f7ac
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mean2.m
@@ -0,0 +1,7 @@
+% M = MEAN2(MTX)
+%
+% Sample mean of a matrix.
+
+function res = mean2(mtx)
+
+res = mean(mean(mtx));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngle.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngle.m
new file mode 100755
index 0000000..bd54f8d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngle.m
@@ -0,0 +1,32 @@
+% IM = mkAngle(SIZE, PHASE, ORIGIN)
+%
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing samples of the polar angle (in radians, CW from the
+% X-axis, ranging from -pi to pi), relative to angle PHASE (default =
+% 0), about ORIGIN pixel (default = (size+1)/2).
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkAngle(sz, phase, origin)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+
+% -----------------------------------------------------------------
+% OPTIONAL args:
+
+if (exist('origin') ~= 1)
+  origin = (sz+1)/2;
+end
+
+% -----------------------------------------------------------------
+
+[xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) );
+
+res = atan2(yramp,xramp);
+
+if (exist('phase') == 1)
+  res = mod(res+(pi-phase),2*pi)-pi;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngularSine.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngularSine.m
new file mode 100755
index 0000000..f5238cc
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkAngularSine.m
@@ -0,0 +1,42 @@
+% IM = mkAngularSine(SIZE, HARMONIC, AMPL, PHASE, ORIGIN)
+%
+% Make an angular sinusoidal image:
+%     AMPL * sin( HARMONIC*theta + PHASE),
+% where theta is the angle about the origin.
+% SIZE specifies the matrix size, as for zeros().  
+% AMPL (default = 1) and PHASE (default = 0) are optional.
+
+% Eero Simoncelli, 2/97.
+
+function [res] = mkAngularSine(sz, harmonic, ampl, ph, origin)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+
+mxsz = max(sz(1),sz(2));
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('harmonic') ~= 1)
+  harmonic = 1;
+end
+
+if (exist('ampl') ~= 1)
+  ampl = 1;
+end
+
+if (exist('ph') ~= 1)
+  ph = 0;
+end
+
+if (exist('origin') ~= 1)
+  origin = (sz+1)/2;
+end
+
+%------------------------------------------------------------
+
+res = ampl * sin(harmonic*mkAngle(sz,ph,origin) + ph);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkDisc.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkDisc.m
new file mode 100755
index 0000000..33e7d6d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkDisc.m
@@ -0,0 +1,61 @@
+% IM = mkDisc(SIZE, RADIUS, ORIGIN, TWIDTH, VALS)
+%
+% Make a "disk" image.  SIZE specifies the matrix size, as for
+% zeros().  RADIUS (default = min(size)/4) specifies the radius of 
+% the disk.  ORIGIN (default = (size+1)/2) specifies the 
+% location of the disk center.  TWIDTH (in pixels, default = 2) 
+% specifies the width over which a soft threshold transition is made.
+% VALS (default = [0,1]) should be a 2-vector containing the
+% intensity value inside and outside the disk.  
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkDisc(sz, rad, origin, twidth, vals)
+
+if (nargin < 1)
+  error('Must pass at least a size argument');
+end
+  
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz sz];
+end
+ 
+%------------------------------------------------------------
+% OPTIONAL ARGS:
+
+if (exist('rad') ~= 1)
+  rad = min(sz(1),sz(2))/4;
+end
+
+if (exist('origin') ~= 1)
+  origin = (sz+1)./2;
+end
+
+if (exist('twidth') ~= 1)
+  twidth = 2;
+end
+
+if (exist('vals') ~= 1)
+  vals = [1,0];
+end
+
+%------------------------------------------------------------
+
+res = mkR(sz,1,origin);
+
+if (abs(twidth) < realmin)
+  res = vals(2) + (vals(1) - vals(2)) * (res <= rad);
+else
+  [Xtbl,Ytbl] = rcosFn(twidth, rad, [vals(1), vals(2)]);
+  res = pointOp(res, Ytbl, Xtbl(1), Xtbl(2)-Xtbl(1), 0);
+% 
+% OLD interp1 VERSION:
+%  res = res(:);
+%  Xtbl(1) = min(res);
+%  Xtbl(size(Xtbl,2)) = max(res);
+%  res = reshape(interp1(Xtbl,Ytbl,res), sz(1), sz(2));
+% 
+end
+  
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkFract.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkFract.m
new file mode 100755
index 0000000..af95cd5
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkFract.m
@@ -0,0 +1,36 @@
+% IM = mkFract(SIZE, FRACT_DIM)
+%
+% Make a matrix of dimensions SIZE (a [Y X] 2-vector, or a scalar)
+% containing fractal (pink) noise with power spectral density of the
+% form: 1/f^(5-2*FRACT_DIM).  Image variance is normalized to 1.0.
+% FRACT_DIM defaults to 1.0
+
+% Eero Simoncelli, 6/96.
+
+%% TODO: Verify that this  matches Mandelbrot defn of fractal dimension.
+%%       Make this more efficient!
+
+function res = mkFract(dims, fract_dim)
+
+if (exist('fract_dim') ~= 1)
+  fract_dim = 1.0;
+end
+
+res = randn(dims);
+fres = fft2(res);
+
+sz = size(res);
+ctr = ceil((sz+1)./2);
+
+shape = ifftshift(mkR(sz, -(2.5-fract_dim), ctr));
+shape(1,1) = 1;  %%DC term
+
+fres = shape .* fres;
+fres = ifft2(fres);
+
+if (max(max(abs(imag(fres)))) > 1e-10)
+  error('Symmetry error in creating fractal');
+else
+  res = real(fres);
+  res = res / sqrt(var2(res));
+end  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m
new file mode 100755
index 0000000..fa8a554
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m
@@ -0,0 +1,58 @@
+% IM = mkGaussian(SIZE, COVARIANCE, MEAN, AMPLITUDE)
+% 
+% Compute a matrix with dimensions SIZE (a [Y X] 2-vector, or a
+% scalar) containing a Gaussian function, centered at pixel position
+% specified by MEAN (default = (size+1)/2), with given COVARIANCE (can
+% be a scalar, 2-vector, or 2x2 matrix.  Default = (min(size)/6)^2),
+% and AMPLITUDE.  AMPLITUDE='norm' (default) will produce a
+% probability-normalized function.  All but the first argument are
+% optional.
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkGaussian(sz, cov, mn, ampl)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('cov') ~= 1)
+  cov = (min(sz(1),sz(2))/6)^2;
+end
+
+if (exist('mn') ~= 1)
+  mn = (sz+1)/2;
+end
+
+if (exist('ampl') ~= 1)
+  ampl = 'norm';
+end
+
+%------------------------------------------------------------
+
+[xramp,yramp] = meshgrid([1:sz(2)]-mn(2),[1:sz(1)]-mn(1));
+
+if (sum(size(cov)) == 2)  % scalar
+  if (strcmp(ampl,'norm'))  
+    ampl = 1/(2*pi*cov(1));
+  end
+  e = (xramp.^2 + yramp.^2)/(-2 * cov);
+elseif (sum(size(cov)) == 3) % a 2-vector
+  if (strcmp(ampl,'norm'))  
+    ampl = 1/(2*pi*sqrt(cov(1)*cov(2)));
+  end
+  e = xramp.^2/(-2 * cov(2)) + yramp.^2/(-2 * cov(1));
+else
+  if (strcmp(ampl,'norm'))  
+    ampl = 1/(2*pi*sqrt(det(cov)));
+  end
+  cov = -inv(cov)/2;
+  e = cov(2,2)*xramp.^2 + (cov(1,2)+cov(2,1))*(xramp.*yramp) ...
+      + cov(1,1)*yramp.^2;
+end
+  
+res = ampl .* exp(e);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkImpulse.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkImpulse.m
new file mode 100755
index 0000000..9844ee8
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkImpulse.m
@@ -0,0 +1,25 @@
+% IM = mkImpulse(SIZE, ORIGIN, AMPLITUDE)
+%
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing a single non-zero entry, at position ORIGIN (defaults to
+% ceil(size/2)), of value AMPLITUDE (defaults to 1).
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkImpulse(sz, origin, amplitude)
+
+sz = sz(:)';
+if (size(sz,2) == 1)
+  sz = [sz sz];
+end
+
+if (exist('origin') ~= 1)
+  origin = ceil(sz/2);
+end
+
+if (exist('amplitude') ~= 1)
+  amplitude = 1;
+end
+
+res = zeros(sz);
+res(origin(1),origin(2)) = amplitude;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkR.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkR.m
new file mode 100755
index 0000000..a1e8448
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkR.m
@@ -0,0 +1,32 @@
+% IM = mkR(SIZE, EXPT, ORIGIN)
+% 
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing samples of a radial ramp function, raised to power EXPT
+% (default = 1), with given ORIGIN (default = (size+1)/2, [1 1] =
+% upper left).  All but the first argument are optional.
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkR(sz, expt, origin)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+ 
+% -----------------------------------------------------------------
+% OPTIONAL args:
+
+if (exist('expt') ~= 1)
+  expt = 1;
+end
+
+if (exist('origin') ~= 1)
+  origin = (sz+1)/2;
+end
+
+% -----------------------------------------------------------------
+
+[xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) );
+
+res = (xramp.^2 + yramp.^2).^(expt/2);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkRamp.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkRamp.m
new file mode 100755
index 0000000..dd37164
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkRamp.m
@@ -0,0 +1,47 @@
+% IM = mkRamp(SIZE, DIRECTION, SLOPE, INTERCEPT, ORIGIN)
+%
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing samples of a ramp function, with given gradient DIRECTION
+% (radians, CW from X-axis, default = 0), SLOPE (per pixel, default =
+% 1), and a value of INTERCEPT (default = 0) at the ORIGIN (default =
+% (size+1)/2, [1 1] = upper left).  All but the first argument are
+% optional.
+
+% Eero Simoncelli, 6/96. 2/97: adjusted coordinate system.
+
+function [res] = mkRamp(sz, dir, slope, intercept, origin)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+
+% -----------------------------------------------------------------
+% OPTIONAL args:
+
+if (exist('dir') ~= 1)
+  dir = 0;
+end
+ 
+if (exist('slope') ~= 1)
+  slope = 1;
+end
+ 
+if (exist('intercept') ~= 1)
+  intercept = 0;
+end
+
+if (exist('origin') ~= 1)
+  origin = (sz+1)/2;
+end
+
+% -----------------------------------------------------------------
+
+xinc = slope*cos(dir);
+yinc = slope*sin(dir);
+
+[xramp,yramp] = meshgrid( xinc*([1:sz(2)]-origin(2)), ...
+    yinc*([1:sz(1)]-origin(1)) );
+ 
+res = intercept + xramp + yramp;
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSine.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSine.m
new file mode 100755
index 0000000..147eb01
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSine.m
@@ -0,0 +1,67 @@
+% IM = mkSine(SIZE, PERIOD, DIRECTION, AMPLITUDE, PHASE, ORIGIN)
+%      or
+% IM = mkSine(SIZE, FREQ, AMPLITUDE, PHASE, ORIGIN)
+% 
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing samples of a 2D sinusoid, with given PERIOD (in pixels),
+% DIRECTION (radians, CW from X-axis, default = 0), AMPLITUDE (default
+% = 1), and PHASE (radians, relative to ORIGIN, default = 0).  ORIGIN
+% defaults to the center of the image.
+% 
+% In the second form, FREQ is a 2-vector of frequencies (radians/pixel).
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkSine(sz, per_freq, dir_amp, amp_phase, phase_orig, orig)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (prod(size(per_freq)) == 2)
+  frequency = norm(per_freq);
+  direction = atan2(per_freq(1),per_freq(2));
+  if (exist('dir_amp') == 1)
+    amplitude = dir_amp;
+  else
+    amplitude = 1;
+  end
+  if (exist('amp_phase') == 1)
+    phase = amp_phase;
+  else
+    phase = 0;
+  end
+  if (exist('phase_orig') == 1)
+    origin = phase_orig;
+  end
+  if (exist('orig') == 1)
+    error('Too many arguments for (second form) of mkSine');
+  end
+else
+  frequency = 2*pi/per_freq;
+  if (exist('dir_amp') == 1)
+    direction = dir_amp;
+  else
+    direction = 0;
+  end
+  if (exist('amp_phase') == 1)
+    amplitude = amp_phase;
+  else
+    amplitude = 1;
+  end
+  if (exist('phase_orig') == 1)
+    phase = phase_orig;
+  else
+    phase = 0;
+  end
+  if (exist('orig') == 1)
+    origin = orig;
+  end
+end
+
+%------------------------------------------------------------
+ 
+if (exist('origin') == 1)
+  res = amplitude*sin(mkRamp(sz, direction, frequency, phase, origin));
+else
+ res = amplitude*sin(mkRamp(sz, direction, frequency, phase));
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSquare.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSquare.m
new file mode 100755
index 0000000..84ef466
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkSquare.m
@@ -0,0 +1,89 @@
+% IM = mkSquare(SIZE, PERIOD, DIRECTION, AMPLITUDE, PHASE, ORIGIN, TWIDTH)
+%      or
+% IM = mkSine(SIZE, FREQ, AMPLITUDE, PHASE, ORIGIN, TWIDTH)
+% 
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing samples of a 2D square wave, with given PERIOD (in
+% pixels), DIRECTION (radians, CW from X-axis, default = 0), AMPLITUDE
+% (default = 1), and PHASE (radians, relative to ORIGIN, default = 0).
+% ORIGIN defaults to the center of the image.  TWIDTH specifies width
+% of raised-cosine edges on the bars of the grating (default =
+% min(2,period/3)).
+% 
+% In the second form, FREQ is a 2-vector of frequencies (radians/pixel).
+
+% Eero Simoncelli, 6/96.
+
+% TODO: Add duty cycle.  
+
+function [res] = mkSquare(sz, per_freq, dir_amp, amp_phase, phase_orig, orig_twidth, twidth)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (prod(size(per_freq)) == 2)
+  frequency = norm(per_freq);
+  direction = atan2(per_freq(1),per_freq(2));
+  if (exist('dir_amp') == 1)
+    amplitude = dir_amp;
+  else
+    amplitude = 1;
+  end
+  if (exist('amp_phase') == 1)
+    phase = amp_phase;
+  else
+    phase = 0;
+  end
+  if (exist('phase_orig') == 1)
+    origin = phase_orig;
+  end
+  if (exist('orig_twidth') == 1)
+    transition = orig_twidth;
+  else
+    transition = min(2,2*pi/(3*frequency));
+  end
+  if (exist('twidth') == 1)
+    error('Too many arguments for (second form) of mkSine');
+  end
+else
+  frequency = 2*pi/per_freq;
+  if (exist('dir_amp') == 1)
+    direction = dir_amp;
+  else
+    direction = 0;
+  end
+  if (exist('amp_phase') == 1)
+    amplitude = amp_phase;
+  else
+    amplitude = 1;
+  end
+  if (exist('phase_orig') == 1)
+    phase = phase_orig;
+  else
+    phase = 0;
+  end
+  if (exist('orig_twidth') == 1)
+    origin = orig_twidth;
+  end
+  if (exist('twidth') == 1)
+    transition = twidth;
+  else
+    transition = min(2,2*pi/(3*frequency));
+  end
+
+end
+
+%------------------------------------------------------------
+  
+if (exist('origin') == 1)
+  res = mkRamp(sz, direction, frequency, phase, origin) - pi/2;
+else
+  res = mkRamp(sz, direction, frequency, phase) - pi/2;
+end
+
+[Xtbl,Ytbl] = rcosFn(transition*frequency,pi/2,[-amplitude amplitude]);
+
+res = pointOp(abs(mod(res+pi, 2*pi)-pi),Ytbl,Xtbl(1),Xtbl(2)-Xtbl(1),0);
+
+% OLD threshold version: 
+%res = amplitude * (mod(res,2*pi) < pi);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkZonePlate.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkZonePlate.m
new file mode 100755
index 0000000..2b6a4a5
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkZonePlate.m
@@ -0,0 +1,33 @@
+% IM = mkZonePlate(SIZE, AMPL, PHASE)
+%
+% Make a "zone plate" image:
+%     AMPL * cos( r^2 + PHASE)
+% SIZE specifies the matrix size, as for zeros().  
+% AMPL (default = 1) and PHASE (default = 0) are optional.
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkZonePlate(sz, ampl, ph)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+
+mxsz = max(sz(1),sz(2));
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('ampl') ~= 1)
+  ampl = 1;
+end
+
+if (exist('ph') ~= 1)
+  ph = 0;
+end
+
+%------------------------------------------------------------
+
+res = ampl * cos( (pi/mxsz) * mkR(sz,2) + ph );
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mod.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mod.m
new file mode 100755
index 0000000..21167e5
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mod.m
@@ -0,0 +1,14 @@
+% M = mod(A,B)
+% 
+% Modulus operator: returns A mod B.
+% Works on matrics, vectors or scalars.
+% 
+% NOTE: This function is a Matlab-5 builtin, but was missing from Matlab-4.
+
+% Eero Simoncelli, 7/96.
+
+function m = mod(a,n)
+
+m = a - n .* floor(a./n);
+return;
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modacor22.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modacor22.m
new file mode 100755
index 0000000..89c8d52
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modacor22.m
@@ -0,0 +1,127 @@
+function [Y,snrV,Chf]=modacor22(X,Cy,p);
+
+% It imposes the desired autocorrelation in the given (central) samples (Cy) to
+% an image X, convolving it with an even filter of size(Cy), in such a way
+% that the image containts change as less as possible, in a LSE sense.
+%       [Y,snr,Chf]=modacor22(X,Cy,p);
+%       Chf:    Fourier transform of the filter that forces the autocorrelation
+%       p [OPTIONAL]:   mixing proportion between Cx and Cy
+%                       it imposes (1-p)*Cx + p*Cy,
+%                       being Cx the actual autocorrelation.
+%                       DEFAULT: p = 1; 
+
+% JPM, 10/97, working with EPS, NYU
+
+Warn = 0;  % Set to 1 if you want to see warning messages
+if (exist('p') ~= 1)
+  p = 1;
+end
+
+% Compute the autocorrelation function of the original image
+
+[Ny,Nx]=size(X);
+Nc=size(Cy,1);  % Normally Nc<<Nx, only the low indices of the autocorrelation  
+if (2*Nc-1 > Nx) & Warn
+  warning('Autocorrelation neighborhood too large for image: reducing');
+  Nc = 2*floor(Nx/4)-1;
+  first = (size(Cy,1)-Nc)/2;
+  Cy = Cy(first+1:first+Nc, first+1:first+Nc);
+end
+
+Xf=fft2(X);
+Xf2=abs(Xf).^2;
+Cx=fftshift(real(ifft2(Xf2)))/(2-isreal(X));
+Cy=Cy*prod(size(X));    % Unnormalize the previously normalized correlation
+
+cy=Ny/2+1;
+cx=Nx/2+1;
+Lc=(Nc-1)/2;
+Cy0 = Cy;
+Cy = p*Cy + (1-p)*Cx(cy-Lc:cy+Lc,cx-Lc:cx+Lc);
+
+% Compare the actual correlation with the desired one
+%imStats(Cx(cy-Lc:cy+Lc,cx-Lc:cx+Lc),Cy)
+snrV=10*log10(sum(sum(Cy0.^2))/sum(sum((Cy0-Cx(cy-Lc:cy+Lc,cx-Lc:cx+Lc)).^2)));
+
+% Take just the part that has influence on the samples of Cy (Cy=conv(Cx,Ch))
+Cx=Cx(cy-2*Lc:cy+2*Lc,cx-2*Lc:cx+2*Lc);
+
+% Build the matrix that performs the convolution Cy1=Tcx*Ch1
+
+Ncx=4*Lc+1;
+M=(Nc^2+1)/2;
+Tcx=zeros(M);
+
+for i=Lc+1:2*Lc,
+        for j=Lc+1:3*Lc+1,
+                nm=(i-Lc-1)*(2*Lc+1)+j-Lc;
+                ccx=Cx(i-Lc:i+Lc,j-Lc:j+Lc);
+                ccxi=ccx(2*Lc+1:-1:1,2*Lc+1:-1:1);
+                ccx=ccx+ccxi;
+                ccx(Lc+1,Lc+1)=ccx(Lc+1,Lc+1)/2;
+                ccx=vector(ccx');
+                Tcx(nm,:)=ccx(1:M)';
+        end
+end
+i=2*Lc+1;
+for j=Lc+1:2*Lc+1,
+        nm=(i-Lc-1)*(2*Lc+1)+j-Lc;
+        ccx=Cx(i-Lc:i+Lc,j-Lc:j+Lc);
+        ccxi=ccx(2*Lc+1:-1:1,2*Lc+1:-1:1);
+        ccx=ccx+ccxi;
+        ccx(Lc+1,Lc+1)=ccx(Lc+1,Lc+1)/2;
+        ccx=vector(ccx');
+        Tcx(nm,:)=ccx(1:M)';
+end
+
+% Rearrange Cy indices and solve the equation
+
+Cy1=vector(Cy');
+Cy1=Cy1(1:M);
+
+Ch1=inv(Tcx)*Cy1;
+
+% Rearrange Ch1
+
+Ch1=[Ch1;Ch1(length(Cy1)-1:-1:1)];
+Ch=reshape(Ch1,Nc,Nc)';
+
+% Compute H from Ch (H is zero-phase) through the DFT
+
+%s=2^(ceil(log(Nc)/log(2))+1);
+%H=sqrt(abs(fft2(Ch,s,s)));
+%h=fftshift(real(ifft2(H)));
+%h=h(s/2+1-Lc:s/2+1+Lc,s/2+1-Lc:s/2+1+Lc);
+%%plot(Ch);drawnow
+%h=recphase(Ch);
+
+% Compute Y as conv(X,H) in the Fourier domain
+
+%%Y=real(ifft2(Xf.*H));
+%Y=real(ifft2(Xf.*sqrt(abs(fft2(Ch,Ny,Nx)))));
+aux=zeros(Ny,Nx);
+aux(cy-Lc:cy+Lc,cx-Lc:cx+Lc)=Ch;
+Ch=fftshift(aux);
+Chf=real(fft2(Ch));
+%Chf=fft2(Ch,Ny,Nx);
+%figure(7);plot(Chf);drawnow;
+Yf=Xf.*sqrt(abs(Chf));
+Y=ifft2(Yf);
+%Y=cconv2(X,h);
+
+% Checks the fidelity of the imposition
+
+%Cy2=fftshift(real(ifft2(Xf2.*abs(Chf))))/(2-isreal(X));
+%Cy2=Cy2(cy-Lc:cy+Lc,cx-Lc:cx+Lc);
+%imStats(Cy,Cy2)
+%imStats(X,Y)
+
+%Yf2=abs(Yf).^2;
+%Cy3=fftshift(real(ifft2(Yf2)))/2;
+
+%Cy3=Cy3(cy-Lc:cy+Lc,cx-Lc:cx+Lc);
+%snr(Cy,Cy-Cy3)
+%imStats(Cy,Cy3)
+
+
+                
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modkurt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modkurt.m
new file mode 100755
index 0000000..e144d32
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modkurt.m
@@ -0,0 +1,172 @@
+function [chm, snrk] = modkurt(ch,k,p);
+
+% Modify the kurtosis in one step, by moving in gradient direction until
+% reaching the desired kurtosis value. 
+% It does not affect the mean nor the variance, but it affects the skewness.
+% This operation is not an orthogonal projection, but the projection angle is
+% near pi/2 when k is close to the original kurtosis, which is a realistic assumption
+% when doing iterative projections in a pyramid, for example (small corrections
+% to the channels' statistics). 
+%
+% [chm, snrk] = modkurt(ch,k,p);
+%       ch: channel
+%       k: desired kurtosis (k=M4/M2^2) 
+%       p [OPTIONAL]:   mixing proportion between k0 and k
+%                       it imposes (1-p)*k0 + p*k,
+%                       being k0 the current kurtosis.
+%                       DEFAULT: p = 1;
+
+
+% Javier Portilla,  Oct.12/97, NYU
+
+Warn = 0;  % Set to 1 if you want to see warning messages
+if ~exist('p'),
+  p = 1;
+end
+
+me=mean2(ch);
+ch=ch-me;
+
+% Compute the moments
+
+m=zeros(12,1);
+for n=2:12,
+        m(n)=mean2(ch.^n);
+end
+
+% The original kurtosis
+
+k0=m(4)/m(2)^2;
+snrk = snr(k, k-k0);
+if snrk > 60,
+        chm = ch+me;
+        return
+end
+k = k0*(1-p) + k*p;
+
+% Some auxiliar variables
+
+a=m(4)/m(2);
+
+% Coeficients of the numerator (A*lam^4+B*lam^3+C*lam^2+D*lam+E)
+
+A=m(12)-4*a*m(10)-4*m(3)*m(9)+6*a^2*m(8)+12*a*m(3)*m(7)+6*m(3)^2*m(6)-...
+        4*a^3*m(6)-12*a^2*m(3)*m(5)+a^4*m(4)-12*a*m(3)^2*m(4)+...
+        4*a^3*m(3)^2+6*a^2*m(3)^2*m(2)-3*m(3)^4;
+B=4*(m(10)-3*a*m(8)-3*m(3)*m(7)+3*a^2*m(6)+6*a*m(3)*m(5)+3*m(3)^2*m(4)-...
+        a^3*m(4)-3*a^2*m(3)^2-3*m(4)*m(3)^2);
+C=6*(m(8)-2*a*m(6)-2*m(3)*m(5)+a^2*m(4)+2*a*m(3)^2+m(3)^2*m(2));
+D=4*(m(6)-a^2*m(2)-m(3)^2);
+E=m(4);
+
+% Define the coefficients of the denominator (F*lam^2+G)^2
+
+F=D/4;
+G=m(2);
+
+% test
+test = 0;
+
+if test,
+
+        grd = ch.^3 - a*ch - m(3);
+        lam = -0.001:0.00001:0.001;
+        k = (A*lam.^4+B*lam.^3+C*lam.^2+D*lam+E)./...
+                (F*lam.^2 + G).^2;
+        for lam = -0.001:0.00001:0.001,
+                n = lam*100000+101;
+                chp = ch + lam*grd;
+                k2(n) = mean2(chp.^4)/mean2(chp.^2)^2;
+                %k2(n) = mean2(chp.^4);
+        end
+        lam = -0.001:0.00001:0.001;
+        snr(k2, k-k2)
+
+end % test
+
+% Now I compute its derivative with respect to lambda
+% (only the roots of derivative = 0 )
+
+d(1) = B*F;
+d(2) = 2*C*F - 4*A*G;
+d(3) = 4*F*D -3*B*G - D*F;
+d(4) = 4*F*E - 2*C*G;
+d(5) = -D*G;
+
+mMlambda = roots(d);
+
+tg = imag(mMlambda)./real(mMlambda);
+mMlambda = mMlambda(find(abs(tg)<1e-6));
+lNeg = mMlambda(find(mMlambda<0));
+if length(lNeg)==0,
+        lNeg = -1/eps;
+end
+lPos = mMlambda(find(mMlambda>=0));
+if length(lPos)==0,
+        lPos = 1/eps;
+end
+lmi = max(lNeg);
+lma = min(lPos);
+
+lam = [lmi lma];
+mMnewKt = polyval([A B C D E],lam)./(polyval([F 0 G],lam)).^2;
+kmin = min(mMnewKt);
+kmax = max(mMnewKt);
+
+% Given a desired kurtosis, solves for lambda
+
+if k<=kmin & Warn,
+        lam = lmi;
+        warning('Saturating (down) kurtosis!');
+        kmin
+elseif k>=kmax & Warn,
+        lam = lma;
+        warning('Saturating (up) kurtosis!');
+        kmax
+else
+
+% Coeficients of the algebraic equation
+
+c0 = E - k*G^2;
+c1 = D;
+c2 = C - 2*k*F*G;
+c3 = B;
+c4 = A - k*F^2;
+
+% Solves the equation
+
+r=roots([c4 c3 c2 c1 c0]);
+
+% Chose the real solution with minimum absolute value with the rigth sign
+
+tg = imag(r)./real(r);
+%lambda = real(r(find(abs(tg)<1e-6)));
+lambda = real(r(find(abs(tg)==0)));
+if length(lambda)>0,
+        lam = lambda(find(abs(lambda)==min(abs(lambda))));
+        lam = lam(1);
+else
+        lam = 0;
+end
+
+end % if ... else
+
+
+% Modify the channel
+
+chm=ch+lam*(ch.^3-a*ch-m(3));   % adjust the kurtosis
+chm=chm*sqrt(m(2)/mean2(chm.^2));       % adjust the variance
+chm=chm+me;                             % adjust the mean
+
+% Check the result
+%k2=mean2((chm-me).^4)/(mean2((chm-me).^2))^2;
+%SNR=snr(k,k-k2)
+
+
+
+
+
+
+
+
+ 
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modskew.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modskew.m
new file mode 100755
index 0000000..3de0e3c
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modskew.m
@@ -0,0 +1,183 @@
+function [chm, snrk] = modskew(ch,sk,p);
+
+% Adjust the sample skewness of a vector/matrix, using gradient projection,
+% without affecting its sample mean and variance.
+%
+% This operation is not an orthogonal projection, but the projection angle is
+% near pi/2 when sk is close to the original skewness, which is a realistic
+% assumption when doing iterative projections in a pyramid, for example
+% (small corrections to the channels' statistics).
+%
+%       [xm, snrk] = modskew(x,sk,p);
+%               sk: new skweness
+%               p [OPTIONAL]:   mixing proportion between sk0 and sk 
+%                               it imposes (1-p)*sk0 + p*sk,
+%                               being sk0 the current skewness.
+%                               DEFAULT: p = 1;
+
+%
+% JPM. 2/98, IODV, CSIC
+% 4/00, CNS, NYU
+
+Warn = 0;  % Set to 1 if you want to see warning messages
+if ~exist('p'), 
+  p = 1;
+end
+
+N=prod(size(ch));       % number of samples
+me=mean2(ch);
+ch=ch-me;
+
+for n=2:6,
+        m(n)=mean2(ch.^n);
+end
+
+sd=sqrt(m(2));  % standard deviation
+s=m(3)/sd^3;    % original skewness
+snrk = snr(sk, sk-s); 
+sk = s*(1-p) + sk*p;
+
+% Define the coefficients of the numerator (A*lam^3+B*lam^2+C*lam+D)
+
+A=m(6)-3*sd*s*m(5)+3*sd^2*(s^2-1)*m(4)+sd^6*(2+3*s^2-s^4);
+B=3*(m(5)-2*sd*s*m(4)+sd^5*s^3);
+C=3*(m(4)-sd^4*(1+s^2));
+D=s*sd^3;
+
+a(7)=A^2;
+a(6)=2*A*B;
+a(5)=B^2+2*A*C;
+a(4)=2*(A*D+B*C);
+a(3)=C^2+2*B*D;
+a(2)=2*C*D;
+a(1)=D^2;
+
+% Define the coefficients of the denominator (A2+B2*lam^2)
+
+A2=sd^2;
+B2=m(4)-(1+s^2)*sd^4;
+
+b=zeros(1,7);
+b(7)=B2^3;
+b(5)=3*A2*B2^2;
+b(3)=3*A2^2*B2;
+b(1)=A2^3;
+
+
+if 0, % test
+
+        lam = -2:0.02:2;
+        S = (A*lam.^3+B*lam.^2+C*lam+D)./...
+                sqrt(b(7)*lam.^6 + b(5)*lam.^4 + b(3)*lam.^2 + b(1));
+%       grd = ch.^2 - m(2) - sd * s * ch;
+%       for lam = -1:0.01:1,
+%               n = lam*100+101;
+%               chp = ch + lam*grd;
+%               S2(n) = mean2(chp.^3)/abs(mean2(chp.^2))^(1.5);
+%       end
+        lam = -2:0.02:2;
+figure(1);plot(lam,S);grid;drawnow
+%       snr(S2, S-S2)
+
+end % test
+
+% Now I compute its derivative with respect to lambda
+
+d(8) = B*b(7);
+d(7) = 2*C*b(7) - A*b(5);
+d(6) = 3*D*b(7);
+d(5) = C*b(5) - 2*A*b(3);
+d(4) = 2*D*b(5) - B*b(3);
+d(3) = -3*A*b(1);
+d(2) = D*b(3) - 2*B*b(1);
+d(1) = -C*b(1);
+
+d = d(8:-1:1);
+mMlambda = roots(d);
+
+tg = imag(mMlambda)./real(mMlambda);
+mMlambda = real(mMlambda(find(abs(tg)<1e-6)));
+lNeg = mMlambda(find(mMlambda<0));
+if length(lNeg)==0,
+        lNeg = -1/eps;
+end
+lPos = mMlambda(find(mMlambda>=0));
+if length(lPos)==0,
+        lPos = 1/eps;
+end
+lmi = max(lNeg);
+lma = min(lPos);
+
+lam = [lmi lma];
+mMnewSt = polyval([A B C D],lam)./(polyval(b(7:-1:1),lam)).^0.5;
+skmin = min(mMnewSt);
+skmax = max(mMnewSt);
+
+
+% Given a desired skewness, solves for lambda
+
+if sk<=skmin & Warn,
+        lam = lmi;
+        warning('Saturating (down) skewness!');
+        skmin
+elseif sk>=skmax & Warn,
+        lam = lma;
+        warning('Saturating (up) skewness!');
+        skmax
+else
+
+
+% The equation is sum(c.*lam.^(0:6))=0
+
+c=a-b*sk^2;
+
+c=c(7:-1:1);
+
+r=roots(c);
+
+% Chose the real solution with minimum absolute value with the rigth sign
+lam=-Inf;
+co=0;
+for n=1:6,
+        tg = imag(r(n))/real(r(n));
+        if (abs(tg)<1e-6)&(sign(real(r(n)))==sign(sk-s)),
+                co=co+1;
+                lam(co)=real(r(n));
+        end
+end
+if min(abs(lam))==Inf & Warn,
+        display('Warning: Skew adjustment skipped!');
+        lam=0;
+end
+
+p=[A B C D];
+
+if length(lam)>1,
+        foo=sign(polyval(p,lam));
+        if any(foo==0),
+                lam = lam(find(foo==0));
+        else
+                lam = lam(find(foo==sign(sk)));         % rejects the symmetric solution
+        end
+        if length(lam)>0,
+                lam=lam(find(abs(lam)==min(abs(lam)))); % the smallest that fix the skew
+                lam=lam(1);
+        else
+                lam = 0;
+        end
+end
+end % if else
+
+% Modify the channel
+chm=ch+lam*(ch.^2-sd^2-sd*s*ch);        % adjust the skewness
+chm=chm*sqrt(m(2)/mean2(chm.^2));               % adjust the variance
+chm=chm+me;                             % adjust the mean
+                                        % (These don't affect the skewness)
+% Check the result
+%mem=mean2(chm);
+%sk2=mean2((chm-mem).^3)/mean2((chm-mem).^2).^(3/2);
+%sk - sk2
+%SNR=snr(sk,sk-sk2)
+
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/modulateFlip.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modulateFlip.m
new file mode 100755
index 0000000..eb27303
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/modulateFlip.m
@@ -0,0 +1,19 @@
+% [HFILT] = modulateFlipShift(LFILT)
+%
+% QMF/Wavelet highpass filter construction: modulate by (-1)^n,
+% reverse order (and shift by one, which is handled by the convolution
+% routines).  This is an extension of the original definition of QMF's
+% (e.g., see Simoncelli90).
+
+% Eero Simoncelli, 7/96.
+
+function [hfilt] = modulateFlipShift(lfilt)
+
+lfilt = lfilt(:);
+
+sz = size(lfilt,1);
+sz2 = ceil(sz/2);
+
+ind = [sz:-1:1]';
+
+hfilt = lfilt(ind) .* (-1).^(ind-sz2);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/namedFilter.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/namedFilter.m
new file mode 100755
index 0000000..0689dbc
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/namedFilter.m
@@ -0,0 +1,71 @@
+% KERNEL = NAMED_FILTER(NAME)
+%
+% Some standard 1D filter kernels.  These are scaled such that
+% their L2-norm is 1.0.
+%
+%  binomN             - binomial coefficient filter of order N-1
+%  haar:              - Haar wavelet.
+%  qmf8, qmf12, qmf16 - Symmetric Quadrature Mirror Filters [Johnston80]
+%  daub2,daub3,daub4  - Daubechies wavelet [Daubechies88].
+%  qmf5, qmf9, qmf13: - Symmetric Quadrature Mirror Filters [Simoncelli88,Simoncelli90]
+%
+%  See bottom of file for full citations.
+
+% Eero Simoncelli, 6/96.
+
+function [kernel] = named_filter(name)
+
+if strcmp(name(1:min(5,size(name,2))), 'binom')
+  kernel = sqrt(2) * binomialFilter(str2num(name(6:size(name,2))));
+elseif strcmp(name,'qmf5')
+  kernel = [-0.076103 0.3535534 0.8593118 0.3535534 -0.076103]';
+elseif strcmp(name,'qmf9')
+  kernel = [0.02807382 -0.060944743 -0.073386624 0.41472545 0.7973934 ...
+      0.41472545 -0.073386624 -0.060944743 0.02807382]';
+elseif strcmp(name,'qmf13')
+  kernel = [-0.014556438 0.021651438 0.039045125 -0.09800052 ...
+          -0.057827797 0.42995453 0.7737113 0.42995453 -0.057827797 ...
+          -0.09800052 0.039045125 0.021651438 -0.014556438]';
+elseif strcmp(name,'qmf8')
+  kernel = sqrt(2) * [0.00938715 -0.07065183 0.06942827 0.4899808 ...
+    0.4899808 0.06942827 -0.07065183 0.00938715 ]';
+elseif strcmp(name,'qmf12')
+  kernel = sqrt(2) * [-0.003809699 0.01885659 -0.002710326 -0.08469594 ...
+        0.08846992 0.4843894 0.4843894 0.08846992 -0.08469594 -0.002710326 ...
+        0.01885659 -0.003809699 ]';
+elseif strcmp(name,'qmf16')
+  kernel = sqrt(2) * [0.001050167 -0.005054526 -0.002589756 0.0276414 -0.009666376 ...
+        -0.09039223 0.09779817 0.4810284 0.4810284 0.09779817 -0.09039223 -0.009666376 ...
+        0.0276414 -0.002589756 -0.005054526 0.001050167 ]';
+elseif strcmp(name,'haar')
+  kernel = [1 1]' / sqrt(2);
+elseif strcmp(name,'daub2')
+  kernel = [0.482962913145 0.836516303738 0.224143868042 -0.129409522551]';
+elseif strcmp(name,'daub3')
+  kernel = [0.332670552950 0.806891509311 0.459877502118 -0.135011020010 ...
+        -0.085441273882  0.035226291882]';
+elseif strcmp(name,'daub4')
+  kernel = [0.230377813309 0.714846570553 0.630880767930 -0.027983769417 ...
+        -0.187034811719 0.030841381836 0.032883011667 -0.010597401785]';
+elseif strcmp(name,'gauss5')  % for backward-compatibility
+  kernel = sqrt(2) * [0.0625 0.25 0.375 0.25 0.0625]';
+elseif strcmp(name,'gauss3')  % for backward-compatibility
+  kernel = sqrt(2) * [0.25 0.5 0.25]';
+else
+  error(sprintf('Bad filter name: %s\n',name));
+end
+  
+% [Johnston80] - J D Johnston, "A filter family designed for use in quadrature 
+%    mirror filter banks", Proc. ICASSP, pp 291-294, 1980.
+%
+% [Daubechies88] - I Daubechies, "Orthonormal bases of compactly supported wavelets",
+%    Commun. Pure Appl. Math, vol. 42, pp 909-996, 1988.
+%
+% [Simoncelli88] - E P Simoncelli,  "Orthogonal sub-band image transforms",
+%     PhD Thesis, MIT Dept. of Elec. Eng. and Comp. Sci. May 1988.
+%     Also available as: MIT Media Laboratory Vision and Modeling Technical 
+%     Report #100.
+%
+% [Simoncelli90] -  E P Simoncelli and E H Adelson, "Subband image coding",
+%    Subband Transforms, chapter 4, ed. John W Woods, Kluwer Academic 
+%    Publishers,  Norwell, MA, 1990, pp 143--192.
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/nextFig.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/nextFig.m
new file mode 100755
index 0000000..e0ac73f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/nextFig.m
@@ -0,0 +1,19 @@
+% nextFig (MAXFIGS, SKIP)
+% 
+% Make figure number mod((GCF+SKIP), MAXFIGS) the current figure.
+% MAXFIGS is optional, and defaults to 2.
+% SKIP is optional, and defaults to 1.
+
+% Eero Simoncelli, 2/97.
+
+function nextFig(maxfigs, skip)
+
+if (exist('maxfigs') ~= 1)
+  maxfigs = 2;
+end
+  
+if (exist('skip') ~= 1)
+  skip = 1;
+end
+  
+figure(1+mod(gcf-1+skip,maxfigs));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmRead.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmRead.m
new file mode 100755
index 0000000..86c3b62
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmRead.m
@@ -0,0 +1,59 @@
+% IM = pgmRead( FILENAME )
+%
+% Load a pgm image into a MatLab matrix.  
+%   This format is accessible from the XV image browsing utility.
+%   Only works for 8bit gray images (raw or ascii)
+
+% Hany Farid, Spring '96.  Modified by Eero Simoncelli, 6/96.
+
+function im = pgmRead( fname );
+
+[fid,msg] = fopen( fname, 'r' );
+
+if (fid == -1)
+  error(msg);
+end
+
+%%% First line contains ID string:
+%%% "P1" = ascii bitmap, "P2" = ascii greymap,
+%%% "P3" = ascii pixmap, "P4" = raw bitmap, 
+%%% "P5" = raw greymap, "P6" = raw pixmap
+TheLine = fgetl(fid);
+format  = TheLine;              
+
+if ~((format(1:2) == 'P2') | (format(1:2) == 'P5'))
+  error('PGM file must be of type P2 or P5');
+end
+
+%%% Any number of comment lines
+TheLine  = fgetl(fid);
+while TheLine(1) == '#' 
+        TheLine = fgetl(fid);
+end
+
+%%% dimensions
+sz = sscanf(TheLine,'%d',2);
+xdim = sz(1);
+ydim = sz(2);
+sz = xdim * ydim;
+
+%%% Maximum pixel value
+TheLine  = fgetl(fid);
+maxval = sscanf(TheLine, '%d',1);
+
+%%im  = zeros(dim,1);
+if (format(2) == '2')
+  [im,count]  = fscanf(fid,'%d',sz);
+else
+  [im,count]  = fread(fid,sz,'uchar');
+end
+
+fclose(fid);
+
+if (count == sz)
+  im = reshape( im, xdim, ydim )';
+else
+  fprintf(1,'Warning: File ended early!');
+  im = reshape( [im ; zeros(sz-count,1)], xdim, ydim)';
+end
+          
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmWrite.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmWrite.m
new file mode 100755
index 0000000..09c14c9
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pgmWrite.m
@@ -0,0 +1,120 @@
+% RANGE = pgmWrite(MTX, FILENAME, RANGE, TYPE, COMMENT)
+%
+% Write a MatLab matrix to a pgm (graylevel image) file.
+% This format is accessible from the XV image browsing utility.
+%
+% RANGE (optional) is a 2-vector specifying the values that map to
+% black and white, respectively.  Passing a value of 'auto' (default)
+% sets RANGE=[min,max] (as in MatLab's imagesc).  'auto2' sets
+% RANGE=[mean-2*stdev, mean+2*stdev].  'auto3' sets
+% RANGE=[p1-(p2-p1)/8, p2+(p2-p1)/8], where p1 is the 10th percentile
+% value of the sorted MATRIX samples, and p2 is the 90th percentile
+% value.
+%
+% TYPE (optional) should be 'raw' or 'ascii'.  Defaults to 'raw'.
+
+% Hany Farid,  Spring '96.  Modified by Eero Simoncelli, 6/96.
+
+function range = pgmWrite(mtx, fname, range, type, comment );
+
+[fid,msg] = fopen( fname, 'w' );
+
+if (fid == -1)
+  error(msg);
+end
+
+%------------------------------------------------------------
+%% optional ARGS:
+
+if (exist('range') ~= 1)
+  range = 'auto';
+end
+
+if (exist('type') ~= 1)
+  type = 'raw';
+end
+%------------------------------------------------------------
+
+%% Automatic range calculation: 
+if (strcmp(range,'auto1') | strcmp(range,'auto'))
+  [mn,mx] = range2(mtx);
+  range = [mn,mx];
+
+elseif strcmp(range,'auto2')
+  stdev = sqrt(var2(mtx));
+  av = mean2(mtx);
+  range = [av-2*stdev,av+2*stdev];      % MAGIC NUMBER: 2 stdevs
+
+elseif strcmp(range, 'auto3')
+  percentile = 0.1;                     % MAGIC NUMBER: 0<p<0.5
+  [N,X] = histo(mtx);
+  binsz = X(2)-X(1);
+  N = N+1e-10;  % Ensure cumsum will be monotonic for call to interp1
+  cumN = [0, cumsum(N)]/sum(N);
+  cumX = [X(1)-binsz, X] + (binsz/2);
+  ctrRange = interp1(cumN,cumX, [percentile, 1-percentile]);
+  range = mean(ctrRange) + (ctrRange-mean(ctrRange))/(1-2*percentile);
+
+elseif isstr(range)
+  error(sprintf('Bad RANGE argument: %s',range))
+
+end
+
+if ((range(2) - range(1)) <= eps)
+  range(1) = range(1) - 0.5;
+  range(2) = range(2) + 0.5;
+end
+
+
+%%% First line contains ID string:
+%%% "P1" = ascii bitmap, "P2" = ascii greymap,
+%%% "P3" = ascii pixmap, "P4" = raw bitmap, 
+%%% "P5" = raw greymap, "P6" = raw pixmap
+if strcmp(type,'raw')
+  fprintf(fid,'P5\n');
+  format = 5;
+elseif strcmp(type,'ascii')
+  fprintf(fid,'P2\n');
+  format = 2;
+else
+  error(sprintf('PGMWRITE: Bad type argument: %s',type));
+end
+
+fprintf(fid,'# MatLab PGMWRITE file, saved %s\n',date);
+
+if (exist('comment') == 1)
+  fprintf(fid,'# %s\n', comment);
+end
+
+%%% dimensions
+fprintf(fid,'%d %d\n',size(mtx,2),size(mtx,1));
+
+%%% Maximum pixel value
+fprintf(fid,'255\n');
+
+
+%% MatLab's "fprintf" floors when writing floats, so we compute
+%% (mtx-r1)*255/(r2-r1)+0.5
+mult = (255 / (range(2)-range(1)));
+mtx = (mult * mtx) + (0.5 - mult * range(1));
+
+mtx = max(-0.5+eps,min(255.5-eps,mtx));
+
+if (format == 2)
+  count  = fprintf(fid,'%d ',mtx');
+elseif (format == 5)
+  count  = fwrite(fid,mtx','uchar');
+end
+
+fclose(fid);
+
+if (count ~= size(mtx,1)*size(mtx,2))
+  fprintf(1,'Warning: File output terminated early!');
+end
+          
+%%% TEST:
+% foo = 257*rand(100)-1;
+% pgmWrite(foo,'foo.pgm',[0 255]);
+% foo2=pgmRead('foo.pgm');
+% size(find((foo2-round(foo))~=0))
+% foo(find((foo2-round(foo))~=0))
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pixelAxes.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pixelAxes.m
new file mode 100755
index 0000000..f88210d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pixelAxes.m
@@ -0,0 +1,70 @@
+% [ZOOM] = pixelAxes(DIMS, ZOOM)
+%
+% Set the axes of the current plot to cover a multiple of DIMS pixels,
+% thereby eliminating screen aliasing artifacts when displaying an
+% image of size DIMS.  
+% 
+% ZOOM (optional, default='same') expresses the desired number of
+% samples displayed per screen pixel.  It should be a scalar, which
+% will be rounded to the nearest integer, or 1 over an integer.  It
+% may also be the string 'same' or 'auto', in which case the value is chosen so
+% as to produce an image closest in size to the currently displayed
+% image.  It may also be the string 'full', in which case the image is
+% made as large as possible while still fitting in the window.
+
+% Eero Simoncelli, 2/97.
+
+function [zoom] = pixelAxes(dims, zoom)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('zoom') ~= 1)
+  zoom = 'same';
+end
+
+%% Reverse  dimension order, since Figure Positions reported as (x,y).
+dims = dims(2:-1:1);
+
+%% Use MatLab's axis function to force square pixels, etc:
+axis('image');
+ax = gca;
+
+oldunits = get(ax,'Units');
+
+if strcmp(zoom,'full');
+  set(ax,'Units','normalized');
+  set(ax,'Position',[0 0 1 1]);
+  zoom = 'same';
+end
+
+set(ax,'Units','pixels');
+pos = get(ax,'Position');
+ctr = pos(1:2)+pos(3:4)/2;
+
+if (strcmp(zoom,'same') | strcmp(zoom,'auto'))
+  %% HACK: enlarge slightly so that floor doesn't round down 
+  zoom = min( pos(3:4) ./ (dims - 1) );
+elseif isstr(zoom)
+  error(sprintf('Bad ZOOM argument: %s',zoom));
+end
+
+%% Force zoom value to be an integer, or inverse integer.
+if (zoom < 0.75)
+  zoom = 1/ceil(1/zoom);
+  %% Round upward, subtracting 0.5 to avoid floating point errors.
+  newsz = ceil(zoom*(dims-0.5));
+else
+  zoom = floor(zoom + 0.001);           % Avoid floating pt errors
+  if (zoom < 1.5)                       % zoom=1
+    zoom = 1;
+    newsz = dims + 0.5;
+  else
+    newsz = zoom*(dims-1) + mod(zoom,2);
+  end
+end 
+
+set(ax,'Position', [floor(ctr-newsz/2)+0.5, newsz] )
+
+% Restore units
+set(ax,'Units',oldunits);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pointOp.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pointOp.m
new file mode 100755
index 0000000..feb7750
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pointOp.m
@@ -0,0 +1,28 @@
+% RES = pointOp(IM, LUT, ORIGIN, INCREMENT, WARNINGS)
+%
+% Apply a point operation, specified by lookup table LUT, to image IM.
+% LUT must be a row or column vector, and is assumed to contain
+% (equi-spaced) samples of the function.  ORIGIN specifies the
+% abscissa associated with the first sample, and INCREMENT specifies the
+% spacing between samples.  Between-sample values are estimated via
+% linear interpolation.  If WARNINGS is non-zero, the function prints
+% a warning whenever the lookup table is extrapolated.
+%
+% This function is much faster than MatLab's interp1, and allows
+% extrapolation beyond the lookup table domain.  The drawbacks are
+% that the lookup table must be equi-spaced, and the interpolation is
+% linear.
+
+% Eero Simoncelli, 8/96.
+
+function res = pointOp(im, lut, origin, increment, warnings)
+
+%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
+
+%fprintf(1,'WARNING: You should compile the MEX version of "pointOp.c",\n         found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path.  It is MUCH faster.\n');
+
+X = origin + increment*[0:size(lut(:),1)-1];
+Y = lut(:);
+
+res = reshape(interp1(X, Y, im(:), 'linear', 'extrap'),size(im));
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pwd2path.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pwd2path.m
new file mode 100755
index 0000000..15aecf0
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pwd2path.m
@@ -0,0 +1,6 @@
+% PWD2PATH()
+%
+% add current working directory (pwd) to path.
+
+P = path;
+path(pwd,P);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBand.m
new file mode 100755
index 0000000..1fb6461
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBand.m
@@ -0,0 +1,11 @@
+% RES = pyrBand(PYR, INDICES, BAND_NUM)
+%
+% Access a subband from a pyramid (gaussian, laplacian, QMF/wavelet, 
+% or steerable).  Subbands are numbered consecutively, from finest
+% (highest spatial frequency) to coarsest (lowest spatial frequency).
+
+% Eero Simoncelli, 6/96.
+
+function res =  pyrBand(pyr, pind, band)
+
+res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) );
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBandIndices.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBandIndices.m
new file mode 100755
index 0000000..f94c217
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrBandIndices.m
@@ -0,0 +1,24 @@
+% RES = pyrBandIndices(INDICES, BAND_NUM)
+%
+% Return indices for accessing a subband from a pyramid 
+% (gaussian, laplacian, QMF/wavelet, steerable).
+
+% Eero Simoncelli, 6/96.
+
+function indices =  pyrBandIndices(pind,band)
+
+if ((band > size(pind,1)) | (band < 1))
+  error(sprintf('BAND_NUM must be between 1 and number of pyramid bands (%d).', ...
+      size(pind,1)));
+end
+
+if (size(pind,2) ~= 2)
+  error('INDICES must be an Nx2 matrix indicating the size of the pyramid subbands');
+end
+
+ind = 1;
+for l=1:band-1
+  ind = ind + prod(pind(l,:));
+end
+
+indices = ind:ind+prod(pind(band,:))-1;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrLow.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrLow.m
new file mode 100755
index 0000000..290e806
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/pyrLow.m
@@ -0,0 +1,12 @@
+% RES = pyrLow(PYR, INDICES)
+%
+% Access the lowpass subband from a pyramid 
+%   (gaussian, laplacian, QMF/wavelet, steerable).
+
+% Eero Simoncelli, 6/96.
+
+function res =  pyrLow(pyr,pind)
+
+band = size(pind,1);
+
+res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) );
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/range2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/range2.m
new file mode 100755
index 0000000..082bbe1
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/range2.m
@@ -0,0 +1,18 @@
+% [MIN, MAX] = range2(MTX)
+%
+% Compute minimum and maximum values of MTX, returning them as a 2-vector.
+
+% Eero Simoncelli, 3/97.
+
+function [mn, mx] = range2(mtx)
+
+%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
+
+%fprintf(1,'WARNING: You should compile the MEX version of "range2.c",\n         found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path.  It is MUCH faster.\n');
+
+if (~isreal(mtx))
+  error('MTX must be real-valued');  
+end
+
+mn = min(min(mtx));
+mx = max(max(mtx));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/rconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/rconv2.m
new file mode 100755
index 0000000..0c12490
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/rconv2.m
@@ -0,0 +1,50 @@
+% RES = RCONV2(MTX1, MTX2, CTR)
+%
+% Convolution of two matrices, with boundaries handled via reflection
+% about the edge pixels.  Result will be of size of LARGER matrix.
+% 
+% The origin of the smaller matrix is assumed to be its center.
+% For even dimensions, the origin is determined by the CTR (optional) 
+% argument:
+%      CTR   origin
+%       0     DIM/2      (default)
+%       1     (DIM/2)+1  
+
+% Eero Simoncelli, 6/96.
+
+function c = rconv2(a,b,ctr)
+
+if (exist('ctr') ~= 1)
+  ctr = 0;
+end
+
+if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
+    large = a; small = b;
+elseif  (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
+    large = b; small = a;
+else
+  error('one arg must be larger than the other in both dimensions!');
+end
+
+ly = size(large,1);
+lx = size(large,2);
+sy = size(small,1);
+sx = size(small,2);
+
+%% These values are one less than the index of the small mtx that falls on 
+%% the border pixel of the large matrix when computing the first 
+%% convolution response sample:
+sy2 = floor((sy+ctr-1)/2);
+sx2 = floor((sx+ctr-1)/2);
+
+% pad with reflected copies
+clarge = [ 
+    large(sy-sy2:-1:2,sx-sx2:-1:2), large(sy-sy2:-1:2,:), ...
+        large(sy-sy2:-1:2,lx-1:-1:lx-sx2); ...
+    large(:,sx-sx2:-1:2),    large,   large(:,lx-1:-1:lx-sx2); ...
+    large(ly-1:-1:ly-sy2,sx-sx2:-1:2), ...
+      large(ly-1:-1:ly-sy2,:), ...
+      large(ly-1:-1:ly-sy2,lx-1:-1:lx-sx2) ];
+
+c = conv2(clarge,small,'valid');
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/rcosFn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/rcosFn.m
new file mode 100755
index 0000000..5dac344
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/rcosFn.m
@@ -0,0 +1,45 @@
+% [X, Y] = rcosFn(WIDTH, POSITION, VALUES)
+%
+% Return a lookup table (suitable for use by INTERP1) 
+% containing a "raised cosine" soft threshold function:
+% 
+%    Y =  VALUES(1) + (VALUES(2)-VALUES(1)) *
+%              cos^2( PI/2 * (X - POSITION + WIDTH)/WIDTH )
+%
+% WIDTH is the width of the region over which the transition occurs
+% (default = 1). POSITION is the location of the center of the
+% threshold (default = 0).  VALUES (default = [0,1]) specifies the
+% values to the left and right of the transition.
+
+% Eero Simoncelli, 7/96.
+
+function [X, Y] = rcosFn(width,position,values)
+
+%------------------------------------------------------------
+% OPTIONAL ARGS:
+
+if (exist('width') ~= 1)
+  width = 1;
+end
+
+if (exist('position') ~= 1)
+  position = 0;
+end
+
+if (exist('values') ~= 1)
+  values = [0,1];
+end
+
+%------------------------------------------------------------
+
+sz = 256;  %% arbitrary!
+
+X    = pi * [-sz-1:1] / (2*sz);
+
+Y = values(1) + (values(2)-values(1)) * cos(X).^2;
+
+%    Make sure end values are repeated, for extrapolation...
+Y(1) = Y(2);
+Y(sz+3) = Y(sz+2);
+
+X = position + (2*width/pi) * (X + pi/4);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconLpyr.m
new file mode 100755
index 0000000..cddcc12
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconLpyr.m
@@ -0,0 +1,83 @@
+% RES = reconLpyr(PYR, INDICES, LEVS, FILT2, EDGES)
+%
+% Reconstruct image from Laplacian pyramid, as created by buildLpyr.
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+%
+% LEVS (optional) should be a list of levels to include, or the string
+% 'all' (default).  The finest scale is number 1.  The lowpass band
+% corresponds to lpyrHt(INDICES)+1.
+%
+% FILT2 (optional) can be a string naming a standard filter (see
+% namedFilter), or a vector which will be used for (separable)
+% convolution.  Default = 'binom5'.  EDGES specifies edge-handling,
+% and defaults to 'reflect1' (see corrDn).
+
+% Eero Simoncelli, 6/96
+
+function res = reconLpyr(pyr, ind, levs, filt2, edges)
+
+if (nargin < 2)
+  error('First two arguments (PYR, INDICES) are required');
+end
+  
+%%------------------------------------------------------------
+%% DEFAULTS:
+
+if (exist('levs') ~= 1)
+  levs = 'all';
+end
+
+if (exist('filt2') ~= 1)
+  filt2 = 'binom5';
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+%%------------------------------------------------------------
+
+maxLev =  1+lpyrHt(ind);
+if strcmp(levs,'all')
+  levs = [1:maxLev]';
+else
+  if (any(levs > maxLev))
+    error(sprintf('Level numbers must be in the range [1, %d].', maxLev));
+  end
+  levs = levs(:);
+end
+
+if isstr(filt2)
+  filt2 = namedFilter(filt2);
+end
+
+filt2 = filt2(:);
+res_sz = ind(1,:);
+
+if any(levs > 1)
+
+  int_sz = [ind(1,1), ind(2,2)];
+  
+  nres = reconLpyr( pyr(prod(res_sz)+1:size(pyr,1)), ...
+      ind(2:size(ind,1),:), levs-1, filt2, edges);
+  
+  if (res_sz(1) == 1)
+    res = upConv(nres, filt2', edges, [1 2], [1 1], res_sz);
+  elseif (res_sz(2) == 1)
+    res = upConv(nres, filt2, edges, [2 1], [1 1], res_sz);
+  else
+    hi = upConv(nres, filt2, edges, [2 1], [1 1], int_sz);
+    res = upConv(hi, filt2', edges, [1 2], [1 1], res_sz);
+  end
+
+else
+  
+  res = zeros(res_sz);
+
+end
+
+if any(levs == 1)
+  res = res + pyrBand(pyr,ind,1);
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSCFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSCFpyr.m
new file mode 100755
index 0000000..a86f03d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSCFpyr.m
@@ -0,0 +1,87 @@
+% RES = reconSCFpyr(PYR, INDICES, LEVS, BANDS, TWIDTH)
+%
+% The inverse of buildSCFpyr: Reconstruct image from its complex steerable pyramid representation,
+% in the Fourier domain.
+%
+% The image is reconstructed by forcing the complex subbands to be analytic
+% (zero on half of the 2D Fourier plane, as they are supossed to be unless
+% they have being modified), and reconstructing from the real part of those
+% analytic subbands. That is equivalent to compute the Hilbert transforms of
+% the imaginary parts of the subbands, average them with their real
+% counterparts, and then reconstructing from the resulting real subbands.
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+%
+% LEVS (optional) should be a list of levels to include, or the string
+% 'all' (default).  0 corresonds to the residual highpass subband.
+% 1 corresponds to the finest oriented scale.  The lowpass band
+% corresponds to number spyrHt(INDICES)+1.
+%
+% BANDS (optional) should be a list of bands to include, or the string
+% 'all' (default).  1 = vertical, rest proceeding anti-clockwise.
+%
+% TWIDTH is the width of the transition region of the radial lowpass
+% function, in octaves (default = 1, which gives a raised cosine for
+% the bandpass filters).
+                                                                                                                        
+% Javier Portilla, 7/04, basing on Eero Simoncelli's Matlab Pyrtools code
+% and our common code on texture synthesis (textureSynthesis.m).
+                                                                                                                        
+function res = reconSCFpyr(pyr, indices, levs, bands, twidth)
+                                                                                                                        
+%%------------------------------------------------------------
+%% DEFAULTS:
+                                                                                                                        
+if ~exist('levs'),
+  levs = 'all';
+end
+                                                                                                                        
+if ~exist('bands')
+  bands = 'all';
+end
+                                                                                                                        
+if ~exist('twidth'),
+  twidth = 1;
+elseif (twidth <= 0)
+  fprintf(1,'Warning: TWIDTH must be positive.  Setting to 1.\n');
+  twidth = 1;
+end
+                                                                                                                        
+%%------------------------------------------------------------
+                                                                                                                        
+                                                                                                                        
+pind = indices;
+Nsc = log2(pind(1,1)/pind(end,1));
+Nor = (size(pind,1)-2)/Nsc;
+                                                                                                                        
+for nsc = 1:Nsc,
+    firstBnum = (nsc-1)*Nor+2;
+                                                                                                                        
+%% Re-create analytic subbands
+    dims = pind(firstBnum,:);
+    ctr = ceil((dims+0.5)/2);
+    ang = mkAngle(dims, 0, ctr);
+    ang(ctr(1),ctr(2)) = -pi/2;
+    for nor = 1:Nor,
+      nband = (nsc-1)*Nor+nor+1;
+      ind = pyrBandIndices(pind,nband);
+      ch = pyrBand(pyr, pind, nband);
+      ang0 = pi*(nor-1)/Nor;
+      xang = mod(ang-ang0+pi, 2*pi) - pi;
+      amask = 2*(abs(xang) < pi/2) + (abs(xang) == pi/2);
+      amask(ctr(1),ctr(2)) = 1;
+      amask(:,1) = 1;
+      amask(1,:) = 1;
+      amask = fftshift(amask);
+      ch = ifft2(amask.*fft2(ch));    % "Analytic" version
+      %f = 1.000008;  % With this factor the reconstruction SNR goes up around 6 dB!
+      f = 1;
+      ch = f*0.5*real(ch); % real part
+      pyr(ind) = ch;
+    end     % nor
+end         % nsc
+                                                                                                                        
+res = reconSFpyr(pyr, indices, levs, bands, twidth);
+                                                                                                                        
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyr.m
new file mode 100755
index 0000000..0e3109e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyr.m
@@ -0,0 +1,108 @@
+% RES = reconSFpyr(PYR, INDICES, LEVS, BANDS, TWIDTH)
+%
+% Reconstruct image from its steerable pyramid representation, in the Fourier
+% domain, as created by buildSFpyr.
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+%
+% LEVS (optional) should be a list of levels to include, or the string
+% 'all' (default).  0 corresonds to the residual highpass subband.  
+% 1 corresponds to the finest oriented scale.  The lowpass band
+% corresponds to number spyrHt(INDICES)+1.
+%
+% BANDS (optional) should be a list of bands to include, or the string
+% 'all' (default).  1 = vertical, rest proceeding anti-clockwise.
+%
+% TWIDTH is the width of the transition region of the radial lowpass
+% function, in octaves (default = 1, which gives a raised cosine for
+% the bandpass filters).
+
+%%% MODIFIED VERSION, 7/04, uses different lookup table for radial frequency!
+
+% Eero Simoncelli, 5/97.
+
+function res = reconSFpyr(pyr, pind, levs, bands, twidth)
+
+%%------------------------------------------------------------
+%% DEFAULTS:
+
+if (exist('levs') ~= 1)
+  levs = 'all';
+end
+
+if (exist('bands') ~= 1)
+  bands = 'all';
+end
+
+if (exist('twidth') ~= 1)
+  twidth = 1;
+elseif (twidth <= 0)
+  fprintf(1,'Warning: TWIDTH must be positive.  Setting to 1.\n');
+  twidth = 1;
+end
+
+%%------------------------------------------------------------
+
+nbands = spyrNumBands(pind);
+
+maxLev =  1+spyrHt(pind);
+if strcmp(levs,'all')
+  levs = [0:maxLev]';
+else
+  if (any(levs > maxLev) | any(levs < 0))
+    error(sprintf('Level numbers must be in the range [0, %d].', maxLev));
+  end
+  levs = levs(:);
+end
+
+if strcmp(bands,'all')
+  bands = [1:nbands]';
+else
+  if (any(bands < 1) | any(bands > nbands))
+    error(sprintf('Band numbers must be in the range [1,3].', nbands));
+  end
+  bands = bands(:);
+end
+
+%----------------------------------------------------------------------
+
+dims = pind(1,:);
+ctr = ceil((dims+0.5)/2);
+
+[xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ...
+    ([1:dims(1)]-ctr(1))./(dims(1)/2) );
+angle = atan2(yramp,xramp);
+log_rad = sqrt(xramp.^2 + yramp.^2);
+log_rad(ctr(1),ctr(2)) =  log_rad(ctr(1),ctr(2)-1);
+log_rad  = log2(log_rad);
+
+%% Radial transition function (a raised cosine in log-frequency):
+[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
+Yrcos = sqrt(Yrcos);
+YIrcos = sqrt(abs(1.0 - Yrcos.^2));
+
+if (size(pind,1) == 2)
+  if (any(levs==1))
+    resdft = fftshift(fft2(pyrBand(pyr,pind,2)));
+  else
+    resdft = zeros(pind(2,:));
+  end
+else
+  resdft = reconSFpyrLevs(pyr(1+prod(pind(1,:)):size(pyr,1)), ...
+      pind(2:size(pind,1),:), ...
+      log_rad, Xrcos, Yrcos, angle, nbands, levs, bands);
+end
+
+lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+resdft = resdft .* lo0mask;
+
+%% residual highpass subband
+if any(levs == 0)
+  hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+  hidft = fftshift(fft2(subMtx(pyr, pind(1,:))));
+  resdft = resdft + hidft .* hi0mask;
+end
+ 
+res = real(ifft2(ifftshift(resdft)));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyrLevs.m
new file mode 100755
index 0000000..420f278
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSFpyrLevs.m
@@ -0,0 +1,69 @@
+% RESDFT = reconSFpyrLevs(PYR,INDICES,LOGRAD,XRCOS,YRCOS,ANGLE,NBANDS,LEVS,BANDS)
+%
+% Recursive function for reconstructing levels of a steerable pyramid
+% representation.  This is called by reconSFpyr, and is not usually
+% called directly.
+
+% Eero Simoncelli, 5/97.
+
+function resdft = reconSFpyrLevs(pyr,pind,log_rad,Xrcos,Yrcos,angle,nbands,levs,bands);
+
+lo_ind = nbands+1;
+dims = pind(1,:);
+ctr = ceil((dims+0.5)/2);
+
+%  log_rad = log_rad + 1;
+Xrcos = Xrcos - log2(2);  % shift origin of lut by 1 octave.
+
+if any(levs > 1)
+
+  lodims = ceil((dims-0.5)/2);
+  loctr = ceil((lodims+0.5)/2);
+  lostart = ctr-loctr+1;
+  loend = lostart+lodims-1;
+  nlog_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2));
+  nangle = angle(lostart(1):loend(1),lostart(2):loend(2));
+
+  if  (size(pind,1) > lo_ind)
+    nresdft = reconSFpyrLevs( pyr(1+sum(prod(pind(1:lo_ind-1,:)')):size(pyr,1)),...
+        pind(lo_ind:size(pind,1),:), ...
+        nlog_rad, Xrcos, Yrcos, nangle, nbands,levs-1, bands);
+  else
+    nresdft = fftshift(fft2(pyrBand(pyr,pind,lo_ind)));
+  end
+
+  YIrcos = sqrt(abs(1.0 - Yrcos.^2));
+  lomask = pointOp(nlog_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+
+  resdft = zeros(dims);
+  resdft(lostart(1):loend(1),lostart(2):loend(2)) = nresdft .* lomask;
+
+else
+
+  resdft = zeros(dims);
+
+end
+
+        
+if any(levs == 1)
+
+  lutsize = 1024;
+  Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize;  % [-2*pi:pi]
+  order = nbands-1;
+  %% divide by sqrt(sum_(n=0)^(N-1)  cos(pi*n/N)^(2(N-1)) )
+  const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order));
+  Ycosn = sqrt(const) * (cos(Xcosn)).^order;
+  himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1),0);
+
+  ind = 1;
+  for b = 1:nbands
+    if any(bands == b)
+      anglemask = pointOp(angle,Ycosn,Xcosn(1)+pi*(b-1)/nbands,Xcosn(2)-Xcosn(1));
+      band = reshape(pyr(ind:ind+prod(dims)-1), dims(1), dims(2));
+      banddft = fftshift(fft2(band));
+      resdft = resdft + (sqrt(-1))^(nbands-1) * banddft.*anglemask.*himask;
+    end
+    ind = ind + prod(dims);
+  end
+end
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyr.m
new file mode 100755
index 0000000..270009d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyr.m
@@ -0,0 +1,96 @@
+% RES = reconSpyr(PYR, INDICES, FILTFILE, EDGES, LEVS, BANDS)
+%
+% Reconstruct image from its steerable pyramid representation, as created
+% by buildSpyr.
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+%
+% FILTFILE (optional) should be a string referring to an m-file that returns
+% the rfilters.  examples: sp0Filters, sp1Filters, sp3Filters 
+% (default = 'sp1Filters'). 
+% EDGES specifies edge-handling, and defaults to 'reflect1' (see
+% corrDn).
+% 
+% LEVS (optional) should be a list of levels to include, or the string
+% 'all' (default).  0 corresonds to the residual highpass subband.  
+% 1 corresponds to the finest oriented scale.  The lowpass band
+% corresponds to number spyrHt(INDICES)+1.
+%
+% BANDS (optional) should be a list of bands to include, or the string
+% 'all' (default).  1 = vertical, rest proceeding anti-clockwise.
+
+% Eero Simoncelli, 6/96.
+
+function res = reconSpyr(pyr, pind, filtfile, edges, levs, bands)
+
+%%------------------------------------------------------------
+%% DEFAULTS:
+
+if (exist('filtfile') ~= 1)
+  filtfile = 'sp1Filters';
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+if (exist('levs') ~= 1)
+  levs = 'all';
+end
+
+if (exist('bands') ~= 1)
+  bands = 'all';
+end
+
+%%------------------------------------------------------------
+
+if (isstr(filtfile) & (exist(filtfile) == 2))
+   [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filtfile);
+   nbands = spyrNumBands(pind);
+   if ((nbands > 0) & (size(bfilts,2) ~= nbands))
+     error('Number of pyramid bands is inconsistent with filter file');
+   end
+else
+  error('filtfile argument must be the name of an M-file containing SPYR filters.');
+end
+
+maxLev =  1+spyrHt(pind);
+if strcmp(levs,'all')
+  levs = [0:maxLev]';
+else
+  if (any(levs > maxLev) | any(levs < 0))
+    error(sprintf('Level numbers must be in the range [0, %d].', maxLev));
+  end
+  levs = levs(:);
+end
+
+if strcmp(bands,'all')
+  bands = [1:nbands]';
+else
+  if (any(bands < 1) | any(bands > nbands))
+    error(sprintf('Band numbers must be in the range [1,3].', nbands));
+  end
+  bands = bands(:);
+end
+
+if (spyrHt(pind) == 0)
+  if (any(levs==1))
+    res1 = pyrBand(pyr,pind,2);
+  else
+    res1 = zeros(pind(2,:));
+  end
+else
+  res1 = reconSpyrLevs(pyr(1+prod(pind(1,:)):size(pyr,1)), ...
+      pind(2:size(pind,1),:), ...
+      lofilt, bfilts, edges, levs, bands);
+end
+
+res = upConv(res1, lo0filt, edges);
+
+%% residual highpass subband
+if any(levs == 0)
+   upConv( subMtx(pyr, pind(1,:)), hi0filt, edges, [1 1], [1 1], size(res), res);
+end
+ 
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyrLevs.m
new file mode 100755
index 0000000..f8e456c
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconSpyrLevs.m
@@ -0,0 +1,46 @@
+% RES = reconSpyrLevs(PYR,INDICES,LOFILT,BFILTS,EDGES,LEVS,BANDS)
+%
+% Recursive function for reconstructing levels of a steerable pyramid
+% representation.  This is called by reconSpyr, and is not usually
+% called directly.
+
+% Eero Simoncelli, 6/96.
+
+function res = reconSpyrLevs(pyr,pind,lofilt,bfilts,edges,levs,bands);
+
+nbands = size(bfilts,2);
+lo_ind = nbands+1;
+res_sz = pind(1,:);
+
+% Assume square filters:
+bfiltsz =  round(sqrt(size(bfilts,1)));
+
+if any(levs > 1)
+
+  if  (size(pind,1) > lo_ind)
+    nres = reconSpyrLevs( pyr(1+sum(prod(pind(1:lo_ind-1,:)')):size(pyr,1)),  ...
+        pind(lo_ind:size(pind,1),:), ...
+        lofilt, bfilts, edges, levs-1, bands);
+  else
+    nres = pyrBand(pyr,pind,lo_ind);    % lowpass subband
+  end
+
+  res = upConv(nres, lofilt, edges, [2 2], [1 1], res_sz);
+
+else
+
+  res = zeros(res_sz);
+
+end
+        
+if any(levs == 1)
+  ind = 1;
+  for b = 1:nbands
+    if any(bands == b)
+      bfilt = reshape(bfilts(:,b), bfiltsz, bfiltsz);
+      upConv(reshape(pyr(ind:ind+prod(res_sz)-1), res_sz(1), res_sz(2)), ...
+                  bfilt, edges, [1 1], [1 1], res_sz, res);
+    end
+    ind = ind + prod(res_sz);
+  end
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconWpyr.m
new file mode 100755
index 0000000..fc31226
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/reconWpyr.m
@@ -0,0 +1,148 @@
+% RES = reconWpyr(PYR, INDICES, FILT, EDGES, LEVS, BANDS)
+%
+% Reconstruct image from its separable orthonormal QMF/wavelet pyramid
+% representation, as created by buildWpyr.
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+%
+% FILT (optional) can be a string naming a standard filter (see
+% namedFilter), or a vector which will be used for (separable)
+% convolution.  Default = 'qmf9'.  EDGES specifies edge-handling,
+% and defaults to 'reflect1' (see corrDn).
+%
+% LEVS (optional) should be a vector of levels to include, or the string
+% 'all' (default).  1 corresponds to the finest scale.  The lowpass band
+% corresponds to wpyrHt(INDICES)+1.
+%
+% BANDS (optional) should be a vector of bands to include, or the string
+% 'all' (default).   1=horizontal, 2=vertical, 3=diagonal.  This is only used
+% for pyramids of 2D images.
+
+% Eero Simoncelli, 6/96.
+
+function res = reconWpyr(pyr, ind, filt, edges, levs, bands)
+
+if (nargin < 2)
+  error('First two arguments (PYR INDICES) are required');
+end
+
+%%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('filt') ~= 1)
+  filt = 'qmf9';
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+if (exist('levs') ~= 1)
+  levs = 'all';
+end
+
+if (exist('bands') ~= 1)
+  bands = 'all';
+end
+
+%%------------------------------------------------------------
+
+maxLev = 1+wpyrHt(ind);
+if strcmp(levs,'all')
+  levs = [1:maxLev]';
+else
+  if (any(levs > maxLev))
+    error(sprintf('Level numbers must be in the range [1, %d].', maxLev));
+  end
+  levs = levs(:);
+end
+
+if strcmp(bands,'all')
+  bands = [1:3]';
+else
+  if (any(bands < 1) | any(bands > 3))
+    error('Band numbers must be in the range [1,3].');
+  end
+  bands = bands(:);
+end
+
+if isstr(filt)
+  filt = namedFilter(filt);
+end
+
+filt = filt(:);
+hfilt = modulateFlip(filt);
+
+%% For odd-length filters, stagger the sampling lattices:
+if (mod(size(filt,1),2) == 0)
+        stag = 2;
+else
+        stag = 1;
+end
+
+%% Compute size of result image: assumes critical sampling (boundaries correct)
+res_sz = ind(1,:);
+if (res_sz(1) == 1)
+  loind = 2;
+  res_sz(2) = sum(ind(:,2));
+elseif (res_sz(2) == 1) 
+  loind = 2;
+  res_sz(1) = sum(ind(:,1));
+else
+  loind = 4;
+  res_sz = ind(1,:) + ind(2,:);  %%horizontal + vertical bands.
+  hres_sz = [ind(1,1), res_sz(2)];
+  lres_sz = [ind(2,1), res_sz(2)];
+end
+        
+
+%% First, recursively collapse coarser scales:
+if any(levs > 1)  
+
+  if (size(ind,1) > loind)
+    nres = reconWpyr( pyr(1+sum(prod(ind(1:loind-1,:)')):size(pyr,1)), ...
+        ind(loind:size(ind,1),:), filt, edges, levs-1, bands);
+  else
+    nres = pyrBand(pyr, ind, loind);    % lowpass subband
+  end
+
+  if (res_sz(1) == 1)
+    res = upConv(nres, filt', edges, [1 2], [1 stag], res_sz);
+  elseif (res_sz(2) == 1)
+    res = upConv(nres, filt, edges, [2 1], [stag 1], res_sz);
+  else
+    ires = upConv(nres, filt', edges, [1 2], [1 stag], lres_sz); 
+    res = upConv(ires, filt, edges, [2 1], [stag 1], res_sz);
+  end
+  
+else
+
+  res = zeros(res_sz);
+
+end
+
+        
+%% Add  in reconstructed bands from this level:
+if any(levs == 1)
+  if (res_sz(1) == 1)
+    upConv(pyrBand(pyr,ind,1), hfilt', edges, [1 2], [1 2], res_sz, res);
+  elseif (res_sz(2) == 1)
+    upConv(pyrBand(pyr,ind,1), hfilt, edges, [2 1], [2 1], res_sz, res);
+  else
+    if any(bands == 1) % horizontal
+      ires = upConv(pyrBand(pyr,ind,1),filt',edges,[1 2],[1 stag],hres_sz);
+      upConv(ires,hfilt,edges,[2 1],[2 1],res_sz,res);  %destructively modify res
+    end
+    if any(bands == 2) % vertical
+      ires = upConv(pyrBand(pyr,ind,2),hfilt',edges,[1 2],[1 2],lres_sz);
+      upConv(ires,filt,edges,[2 1],[stag 1],res_sz,res);  %destructively modify res
+    end
+    if any(bands == 3) % diagonal
+      ires =  upConv(pyrBand(pyr,ind,3),hfilt',edges,[1 2],[1 2],hres_sz);
+      upConv(ires,hfilt,edges,[2 1],[2 1],res_sz,res);  %destructively modify res
+    end
+  end
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile.m
new file mode 100755
index 0000000..133ca50
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile.m
@@ -0,0 +1,142 @@
+% Example 2:  Seamless blending of real and synthetic texture in an
+% image, using Portilla-Simoncelli texture analysis/synthesis code,
+% based on alternate projections onto statistical constraints in a
+% complex overcomplete wavelet representation.
+%
+% See Readme.txt, and headers of textureAnalysis.m and
+% textureSynthesis.m for more details.
+%
+% Javier Portilla (javier@decsai.ugr.es).  March, 2001
+
+function script_run_profile(dataDir, resultDir, type, common,toolDir)
+
+path(path, common);
+Files = dir([dataDir,'/1.bmp']);
+inputFile = fullfile(dataDir,Files(1).name);
+
+close all
+
+Nsc = 4; % Number of scales
+Nor = 4; % Number of orientations
+Na = 5;  % Spatial neighborhood is Na x Na coefficients
+                        % It must be an odd number!
+Niter = 25;     % Number of iterations of synthesis loop
+Nsx = 192;      % Size of synthetic image is Nsy x Nsx
+Nsy = 192;      % Warning: both dimensions must be multiple of 2^(Nsc+2)
+
+if(strcmp(type,'qcif'))
+Nsc = 4;
+Nor = 4;
+Na = 5;
+Niter = 5;
+elseif(strcmp(type,'sqcif'))
+Nsc = 2;
+Nor = 2;
+Na = 3;
+Niter = 5;
+elseif(strcmp(type, 'test'))
+Nsc = 2; % Number of scales
+Nor = 2; % Number of orientations
+Na = 1;  % Spatial neighborhood is Na x Na coefficients
+                        % It must be an odd number!
+Niter = 1;      % Number of iterations of synthesis loop
+Nsx = 16;       % Size of synthetic image is Nsy x Nsx
+Nsy = 16;       % Warning: both dimensions must be multiple of 2^(Nsc+2)
+
+elseif(strcmp(type, 'sim_fast'))
+Nsc = 2; % Number of scales
+Nor = 2; % Number of orientations
+Na = 3;  % Spatial neighborhood is Na x Na coefficients
+                        % It must be an odd number!
+Niter = 2;      % Number of iterations of synthesis loop
+Nsx = 16;       % Size of synthetic image is Nsy x Nsx
+Nsy = 16;       % Warning: both dimensions must be multiple of 2^(Nsc+2)
+
+elseif(strcmp(type, 'sim'))
+Nsc = 2; % Number of scales
+Nor = 2; % Number of orientations
+Na = 3;  % Spatial neighborhood is Na x Na coefficients
+                        % It must be an odd number!
+Niter = 1;      % Number of iterations of synthesis loop
+Nsx = 32;       % Size of synthetic image is Nsy x Nsx
+Nsy = 32;       % Warning: both dimensions must be multiple of 2^(Nsc+2)
+
+elseif(strcmp(type, 'vga'))
+Nsc = 2; % Number of scales
+Nor = 2; % Number of orientations
+Na = 3;  % Spatial neighborhood is Na x Na coefficients
+                        % It must be an odd number!
+Niter = 1;      % Number of iterations of synthesis loop
+Nsx = 640;      % Size of synthetic image is Nsy x Nsx
+Nsy = 480;      % Warning: both dimensions must be multiple of 2^(Nsc+2)
+
+elseif(strcmp(type, 'real'))
+Nsc = 2; % Number of scales
+Nor = 2; % Number of orientations
+Na = 3;  % Spatial neighborhood is Na x Na coefficients
+                        % It must be an odd number!
+Niter = 1;      % Number of iterations of synthesis loop
+Nsx = 1920;     % Size of synthetic image is Nsy x Nsx
+Nsy = 1200;     % Warning: both dimensions must be multiple of 2^(Nsc+2)
+
+end
+
+im0 = readImage(inputFile);     % Warning: im0 is a double float matrix!
+rows = size(im0,1);
+cols = size(im0,2);
+fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
+
+%% Self check params
+tol = 0.1;
+elapsed = zeros(1,2);
+
+%% Timing
+start = photonStartTiming;
+
+params = textureAnalysis(im0, Nsc, Nor, Na);
+
+%% Timing
+stop = photonEndTiming;
+
+temp = photonReportTiming(start, stop);
+elapsed(1) = elapsed(1) + temp(1);
+elapsed(2) = elapsed(2) + temp(2);
+
+% Use a mask and the original image to synthesize an image with the
+% left side synthetic and the right side real data.
+% The effective mask is M = (mask>0), its smoothness is for avoiding
+% border effects.
+ramp = meshgrid(1:Nsx/4,1:Nsy)*4/Nsy;
+mask = [zeros(Nsy,Nsx/2) ramp ramp(:,Nsx/4:-1:1)];
+mask =  1/2*(1-cos(pi*mask));
+
+imKeep = zeros(Nsx*Nsy,2);
+imKeep(:,1) = reshape(mask, [Nsy*Nsx,1]);
+imKeep(:,2) = reshape(im0(1:Nsy,1:Nsx), [Nsy*Nsx,1]);   % Original
+
+%% Timing
+start = photonStartTiming;
+
+res = textureSynthesis(params, [Nsy Nsx], Niter,[],imKeep);
+
+%% Timing
+stop = photonEndTiming;
+
+temp = photonReportTiming(start, stop);
+elapsed(1) = elapsed(1) + temp(1);
+elapsed(2) = elapsed(2) + temp(2);
+
+%% Self checking
+fWriteMatrix(res, dataDir);
+
+rows = Nsy;
+cols = Nsx;
+
+%% Timing
+photonPrintTiming(elapsed);
+
+%close all
+%figure(1);showIm(mask>0, 'auto', 'auto', 'Mask');
+%figure(2);showIm(im0, 'auto', 'auto', 'Original Texture');
+%figure(3);showIm(res, 'auto', 'auto', 'Blended Original and Synthetic Texture');
+%pause;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile1.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile1.m
new file mode 100755
index 0000000..2a7a0dc
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/script_run_profile1.m
@@ -0,0 +1,34 @@
+% Example 1: Synthesis of a "text" texture image, using
+% Portilla-Simoncelli texture analysis/synthesis code, based on
+% alternate projections onto statistical constraints in a complex
+% overcomplete wavelet representation.
+%
+% See Readme.txt, and headers of textureAnalysis.m and
+% textureSynthesis.m for more details.
+%
+% Javier Portilla (javier@decsai.ugr.es).  March, 2001
+
+close all
+
+im0 = imread('/u/kvs/VisionBenchmark/texture_synthesis/result/text.pgm');       % im0 is a double float matrix!
+
+Nsc = 4; % Number of scales
+Nor = 4; % Number of orientations
+Na = 9;  % Spatial neighborhood is Na x Na coefficients
+         % It must be an odd number!
+
+params = textureAnalysis(im0, Nsc, Nor, Na);
+
+Niter = 25;     % Number of iterations of synthesis loop
+Nsx = 192;      % Size of synthetic image is Nsy x Nsx
+Nsy = 128;      % WARNING: Both dimensions must be multiple of 2^(Nsc+2)
+
+res = textureSynthesis(params, [Nsy Nsx], Niter);
+
+close all
+figure(1)
+showIm(im0, 'auto', 1, 'Original texture');
+figure(2)
+showIm(res, 'auto', 1, 'Synthesized texture');
+
+% Can you read the NEW text? ;-)
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/setPyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/setPyrBand.m
new file mode 100755
index 0000000..baa9f77
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/setPyrBand.m
@@ -0,0 +1,32 @@
+% NEWPYR = setPyrBand(PYR, INDICES, BAND, BAND_NUM)
+%
+% Insert an image (BAND) into a pyramid (gaussian, laplacian, QMF/wavelet, 
+% or steerable).  Subbands are numbered consecutively, from finest
+% (highest spatial frequency) to coarsest (lowest spatial frequency).
+
+% Eero Simoncelli, 1/03.
+
+function pyr =  pyrBand(pyr, pind, band, bandNum)
+
+%% Check: PIND a valid index matrix?
+if ( ~(ndims(pind) == 2) | ~(size(pind,2) == 2) | ~all(pind==round(pind)) )
+  pind
+  error('pyrTools:badArg',...
+      'PIND argument is not an Nbands X 2 matrix of integers');
+end
+
+%% Check: PIND consistent with size of PYR?
+if ( length(pyr) ~= sum(prod(pind,2)) )
+  error('pyrTools:badPyr',...
+      'Pyramid data vector length is inconsistent with index matrix PIND');
+end
+
+%% Check: size of BAND  consistent with desired BANDNUM?
+if (~all(size(band) == pind(bandNum,:)))
+  size(band)
+  pind(bandNum,:)
+  error('pyrTools:badArg',...
+      'size of BAND to be inserted is inconsistent with BAND_NUM');
+end
+
+pyr(pyrBandIndices(pind,bandNum)) = vectify(band); 
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/shift.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/shift.m
new file mode 100755
index 0000000..497297e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/shift.m
@@ -0,0 +1,15 @@
+% [RES] = shift(MTX, OFFSET)
+% 
+% Circular shift 2D matrix samples by OFFSET (a [Y,X] 2-vector),
+% such that  RES(POS) = MTX(POS-OFFSET).
+
+function res = shift(mtx, offset)
+
+dims = size(mtx);
+
+offset = mod(-offset,dims);
+
+res = [ mtx(offset(1)+1:dims(1), offset(2)+1:dims(2)),  ...
+          mtx(offset(1)+1:dims(1), 1:offset(2));        ...
+        mtx(1:offset(1), offset(2)+1:dims(2)),          ...
+          mtx(1:offset(1), 1:offset(2)) ];
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showIm.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showIm.m
new file mode 100755
index 0000000..a9e2bd1
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showIm.m
@@ -0,0 +1,221 @@
+% RANGE = showIm (MATRIX, RANGE, ZOOM, LABEL, NSHADES )
+% 
+% Display a MatLab MATRIX as a grayscale image in the current figure,
+% inside the current axes.  If MATRIX is complex, the real and imaginary 
+% parts are shown side-by-side, with the same grayscale mapping.
+% 
+% If MATRIX is a string, it should be the name of a variable bound to a 
+% MATRIX in the base (global) environment.  This matrix is displayed as an 
+% image, with the title set to the string.
+% 
+% RANGE (optional) is a 2-vector specifying the values that map to
+% black and white, respectively.  Passing a value of 'auto' (default)
+% sets RANGE=[min,max] (as in MatLab's imagesc).  'auto2' sets
+% RANGE=[mean-2*stdev, mean+2*stdev].  'auto3' sets
+% RANGE=[p1-(p2-p1)/8, p2+(p2-p1)/8], where p1 is the 10th percentile
+% value of the sorted MATRIX samples, and p2 is the 90th percentile
+% value.
+% 
+% ZOOM specifies the number of matrix samples per screen pixel.  It
+% will be rounded to an integer, or 1 divided by an integer.  A value
+% of 'same' or 'auto' (default) causes the zoom value to be chosen
+% automatically to fit the image into the current axes.  A value of
+% 'full' fills the axis region (leaving no room for labels).  See
+% pixelAxes.m.
+% 
+% If LABEL (optional, default = 1, unless zoom='full') is non-zero, the range 
+% of values that are mapped into the gray colormap and the dimensions 
+% (size) of the matrix and zoom factor are printed below the image.  If label 
+% is a string, it is used as a title.
+% 
+% NSHADES (optional) specifies the number of gray shades, and defaults
+% to the size of the current colormap.
+
+% Eero Simoncelli, 6/96.
+
+%%TODO: should use "newplot"
+
+function range = showIm( im, range, zoom, label, nshades );
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (nargin < 1)
+  error('Requires at least one input argument.'); 
+end
+
+MLv = version;
+
+if isstr(im)
+  if (strcmp(MLv(1),'4'))
+    error('Cannot pass string arg for MATRIX in MatLab version 4.x');
+  end
+  label = im;
+  im = evalin('base',im);
+end
+
+if (exist('range') ~= 1)
+  range = 'auto1';
+end
+
+if (exist('nshades') ~= 1)
+  nshades = size(colormap,1);
+end
+nshades = max( nshades, 2 );
+
+if (exist('zoom') ~= 1)
+  zoom = 'auto';
+end
+
+if (exist('label') ~= 1)
+  if strcmp(zoom,'full')
+    label = 0;                          % no labeling
+  else                                  
+    label = 1;                          % just print grayrange & dims
+  end
+end
+
+%------------------------------------------------------------
+
+%% Automatic range calculation: 
+if (strcmp(range,'auto1') | strcmp(range,'auto'))
+  if isreal(im)
+    [mn,mx] = range2(im);
+  else
+    [mn1,mx1] = range2(real(im));
+    [mn2,mx2] =  range2(imag(im));
+    mn = min(mn1,mn2);
+    mx = max(mx1,mx2);
+  end
+  if any(size(im)==1)
+    pad = (mx-mn)/12;                   % MAGIC NUMBER: graph padding
+    range = [mn-pad, mx+pad];
+  else
+    range = [mn,mx];
+  end
+
+elseif strcmp(range,'auto2')
+  if isreal(im)
+    stdev = sqrt(var2(im));
+    av = mean2(im);
+  else
+    stdev = sqrt((var2(real(im)) + var2(imag(im)))/2);
+    av = (mean2(real(im)) + mean2(imag(im)))/2;
+  end
+  range = [av-2*stdev,av+2*stdev];      % MAGIC NUMBER: 2 stdevs
+
+elseif strcmp(range, 'auto3')
+  percentile = 0.1;                     % MAGIC NUMBER: 0<p<0.5
+  [N,X] = histo(im);
+  binsz = X(2)-X(1);
+  N = N+1e-10;  % Ensure cumsum will be monotonic for call to interp1
+  cumN = [0, cumsum(N)]/sum(N);
+  cumX = [X(1)-binsz, X] + (binsz/2);
+  ctrRange = interp1(cumN,cumX, [percentile, 1-percentile]);
+  range = mean(ctrRange) + (ctrRange-mean(ctrRange))/(1-2*percentile);
+
+elseif isstr(range)
+  error(sprintf('Bad RANGE argument: %s',range))
+
+end
+
+if ((range(2) - range(1)) <= eps)
+  range(1) = range(1) - 0.5;
+  range(2) = range(2) + 0.5;
+end
+
+
+if isreal(im)
+  factor=1;
+else
+  factor = 1+sqrt(-1);
+end
+
+xlbl_offset = 0; % default value
+
+if (~any(size(im)==1))
+  %% MatLab's "image" rounds when mapping to the colormap, so we compute
+  %%      (im-r1)*(nshades-1)/(r2-r1) + 1.5 
+  mult = ((nshades-1) / (range(2)-range(1)));
+  d_im = (mult * im) + factor*(1.5 - range(1)*mult);
+end
+
+if isreal(im)
+  if (any(size(im)==1))
+    hh = plot( im);
+    axis([1, prod(size(im)), range]);
+  else
+    hh = image( d_im );
+    axis('off');
+    zoom = pixelAxes(size(d_im),zoom);
+  end
+else
+  if (any(size(im)==1))
+    subplot(2,1,1);
+    hh = plot(real(im));
+    axis([1, prod(size(im)), range]);
+    subplot(2,1,2);
+    hh = plot(imag(im));
+    axis([1, prod(size(im)), range]);
+  else
+    subplot(1,2,1);
+    hh = image(real(d_im));
+    axis('off'); zoom = pixelAxes(size(d_im),zoom);
+    ax = gca; orig_units = get(ax,'Units');
+    set(ax,'Units','points');
+    pos1 = get(ax,'Position');
+    set(ax,'Units',orig_units);
+    subplot(1,2,2);
+    hh = image(imag(d_im));
+    axis('off'); zoom = pixelAxes(size(d_im),zoom);
+    ax = gca; orig_units = get(ax,'Units');
+    set(ax,'Units','points');
+    pos2 = get(ax,'Position');
+    set(ax,'Units',orig_units);
+    xlbl_offset = (pos1(1)-pos2(1))/2;
+  end
+end  
+
+if ~any(size(im)==1)
+  colormap(gray(nshades));
+end
+
+if ((label ~= 0))
+  if isstr(label)
+    title(label);
+    h = get(gca,'Title');
+    orig_units = get(h,'Units');
+    set(h,'Units','points');
+    pos = get(h,'Position');
+    pos(1:2) = pos(1:2) + [xlbl_offset, -3]; % MAGIC NUMBER: y pixel offset
+    set(h,'Position',pos);
+    set(h,'Units',orig_units);
+  end
+
+  if (~any(size(im)==1))
+    if (zoom > 1)
+      zformat = sprintf('* %d',round(zoom));
+    else
+      zformat = sprintf('/ %d',round(1/zoom));
+    end
+    if isreal(im) 
+      format=[' Range: [%.3g, %.3g] \n Dims: [%d, %d] ', zformat];
+        else
+      format=['Range: [%.3g, %.3g]  ----  Dims: [%d, %d]', zformat];
+    end
+    xlabel(sprintf(format, range(1), range(2), size(im,1), size(im,2)));
+    h = get(gca,'Xlabel');
+    set(h,'FontSize', 9);               % MAGIC NUMBER: font size!!!
+
+    orig_units = get(h,'Units');
+    set(h,'Units','points');  
+    pos = get(h,'Position');
+    pos(1:2) = pos(1:2) + [xlbl_offset, 10]; % MAGIC NUMBER: y offset in points
+    set(h,'Position',pos);
+    set(h,'Units',orig_units);
+
+    set(h,'Visible','on');              % axis('image') turned the  xlabel  off...
+  end
+end
+
+return;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showLpyr.m
new file mode 100755
index 0000000..0d85f9d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showLpyr.m
@@ -0,0 +1,202 @@
+% RANGE = showLpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR)
+% 
+% Display a Laplacian (or Gaussian) pyramid, specified by PYR and
+% INDICES (see buildLpyr), in the current figure.
+% 
+% RANGE is a 2-vector specifying the values that map to black and
+% white, respectively.  These values are scaled by
+% LEVEL_SCALE_FACTOR^(lev-1) for bands at each level.  Passing a value
+% of 'auto1' sets RANGE to the min and max values of MATRIX.  'auto2'
+% sets RANGE to 3 standard deviations below and above 0.0.  In both of
+% these cases, the lowpass band is independently scaled.  A value of
+% 'indep1' sets the range of each subband independently, as in a call
+% to showIm(subband,'auto1').  Similarly, 'indep2' causes each subband
+% to be scaled independently as if by showIm(subband,'indep2').
+% The default value for RANGE is 'auto1' for 1D images, and 'auto2' for
+% 2D images.
+% 
+% GAP (optional, default=1) specifies the gap in pixels to leave
+% between subbands (2D images only).  
+% 
+% LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid
+% levels.  This should be set to the sum of the kernel taps of the
+% lowpass filter used to construct the pyramid (default assumes
+% L2-normalalized filters, using a value of 2 for 2D images, sqrt(2) for
+% 1D images).
+
+% Eero Simoncelli, 2/97.
+
+function [range] = showLpyr(pyr, pind, range, gap, scale);
+
+% Determine 1D or 2D pyramid:
+if ((pind(1,1) == 1) | (pind(1,2) ==1))
+  oned = 1;
+else
+  oned = 0;
+end
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('range') ~= 1)  
+  if (oned==1)
+    range = 'auto1';
+  else
+    range = 'auto2';
+  end
+end
+                
+if (exist('gap') ~= 1)
+  gap = 1;
+end
+
+if (exist('scale') ~= 1)
+  if (oned == 1)
+    scale = sqrt(2);
+  else
+    scale = 2;
+  end
+end
+
+%------------------------------------------------------------
+
+nind = size(pind,1);
+
+%% Auto range calculations:
+if strcmp(range,'auto1')
+  range = zeros(nind,1);
+  mn = 0.0; mx = 0.0;
+  for bnum = 1:(nind-1)
+    band = pyrBand(pyr,pind,bnum)/(scale^(bnum-1));
+    range(bnum) = scale^(bnum-1);
+    [bmn,bmx] = range2(band);
+    mn = min(mn, bmn);  mx = max(mx, bmx);
+  end    
+  if (oned == 1)
+    pad = (mx-mn)/12;                   % *** MAGIC NUMBER!!
+    mn = mn-pad;  mx = mx+pad;
+  end
+  range = range * [mn mx];              % outer product
+  band = pyrLow(pyr,pind);
+  [mn,mx] = range2(band);
+  if (oned == 1)
+    pad = (mx-mn)/12;                   % *** MAGIC NUMBER!!
+    mn = mn-pad;  mx = mx+pad;
+  end
+  range(nind,:) = [mn, mx];
+
+elseif strcmp(range,'indep1')
+  range = zeros(nind,2);
+  for bnum = 1:nind
+    band = pyrBand(pyr,pind,bnum);
+    [mn,mx] = range2(band);
+    if (oned == 1)
+      pad = (mx-mn)/12;                 % *** MAGIC NUMBER!!
+      mn = mn-pad;  mx = mx+pad;
+    end
+    range(bnum,:) =  [mn mx];
+  end
+
+elseif strcmp(range,'auto2')
+  range = zeros(nind,1);
+  sqsum = 0;  numpixels = 0;
+  for bnum = 1:(nind-1)
+    band = pyrBand(pyr,pind,bnum)/(scale^(bnum-1));
+    sqsum = sqsum + sum(sum(band.^2));
+    numpixels = numpixels + prod(size(band));
+    range(bnum) = scale^(bnum-1);
+  end    
+  stdev = sqrt(sqsum/(numpixels-1));
+  range = range * [ -3*stdev 3*stdev ]; % outer product
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+
+elseif strcmp(range,'indep2')
+  range = zeros(nind,2);
+  for bnum = 1:(nind-1)
+    band = pyrBand(pyr,pind,bnum);
+    stdev = sqrt(var2(band));
+    range(bnum,:) =  [ -3*stdev 3*stdev ];
+  end
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+  
+elseif isstr(range)
+  error(sprintf('Bad RANGE argument: %s',range))
+
+elseif ((size(range,1) == 1) & (size(range,2) == 2))
+  scales = scale.^[0:nind-1];
+  range = scales(:) * range;            % outer product
+  band = pyrLow(pyr,pind);
+  range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:));
+
+end
+
+%% Clear Figure
+clf;
+
+if (oned == 1)
+
+  %%%%%  1D signal:
+  for bnum=1:nind
+    band = pyrBand(pyr,pind,bnum);
+    subplot(nind,1,nind-bnum+1);
+    plot(band);
+    axis([1, prod(size(band)), range(bnum,:)]);
+  end
+
+else  
+
+  %%%%% 2D signal:
+  colormap(gray);
+  cmap = get(gcf,'Colormap');
+  nshades = size(cmap,1);
+
+  %  Find background color index:
+  clr = get(gcf,'Color');
+  bg = 1;
+  dist = norm(cmap(bg,:)-clr);
+  for n = 1:nshades
+    ndist = norm(cmap(n,:)-clr);
+    if (ndist < dist)
+      dist = ndist;
+      bg = n;
+    end
+  end  
+
+  %% Compute positions of subbands:
+  llpos = ones(nind,2);
+  dir = [-1 -1];
+  ctr = [pind(1,1)+1+gap 1];
+  sz = [0 0];
+  for bnum = 1:nind
+    prevsz = sz;
+    sz = pind(bnum,:);
+
+    % Determine center position of new band:
+    ctr = ctr + gap*dir/2 + dir.* floor((prevsz+(dir>0))/2);
+    dir = dir * [0 -1; 1 0];  % ccw rotation
+    ctr = ctr + gap*dir/2 + dir.* floor((sz+(dir<0))/2);
+    llpos(bnum,:) = ctr - floor(sz./2);
+  end
+   
+  %% Make position list positive, and allocate appropriate image:
+  llpos = llpos - ones(nind,1)*min(llpos) + 1;
+  urpos = llpos + pind - 1;
+  d_im = bg + zeros(max(urpos));
+
+  %% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 
+  for bnum=1:nind
+    mult = (nshades-1) / (range(bnum,2)-range(bnum,1));
+    d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ...
+        mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1));
+  end
+    
+  hh = image(d_im);
+  axis('off');
+  pixelAxes(size(d_im),'full');
+  set(hh,'UserData',range);
+
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showSpyr.m
new file mode 100755
index 0000000..da85715
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showSpyr.m
@@ -0,0 +1,188 @@
+% RANGE = showSpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR)
+% 
+% Display a steerable pyramid, specified by PYR and INDICES
+% (see buildSpyr), in the current figure.  The highpass band is not shown.
+% 
+% RANGE is a 2-vector specifying the values that map to black and
+% white, respectively.  These values are scaled by
+% LEVEL_SCALE_FACTOR^(lev-1) for bands at each level.  Passing a value
+% of 'auto1' sets RANGE to the min and max values of MATRIX.  'auto2'
+% sets RANGE to 3 standard deviations below and above 0.0.  In both of
+% these cases, the lowpass band is independently scaled.  A value of
+% 'indep1' sets the range of each subband independently, as in a call
+% to showIm(subband,'auto1').  Similarly, 'indep2' causes each subband
+% to be scaled independently as if by showIm(subband,'indep2').
+% The default value for RANGE is 'auto2'.
+% 
+% GAP (optional, default=1) specifies the gap in pixels to leave
+% between subbands.  
+% 
+% LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid
+% levels.  This should be set to the sum of the kernel taps of the
+% lowpass filter used to construct the pyramid (default is 2, which is 
+% correct for L2-normalized filters.
+
+% Eero Simoncelli, 2/97.
+
+function [range] = showSpyr(pyr, pind, range, gap, scale);
+
+nbands = spyrNumBands(pind);
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('range') ~= 1)  
+  range = 'auto2';
+end
+                
+if (exist('gap') ~= 1)
+  gap = 1;
+end
+
+if (exist('scale') ~= 1)
+  scale = 2;
+end
+
+%------------------------------------------------------------
+
+ht = spyrHt(pind);
+nind = size(pind,1);
+
+%% Auto range calculations:
+if strcmp(range,'auto1')
+  range = ones(nind,1);
+  band = spyrHigh(pyr,pind);
+  [mn,mx] = range2(band);
+  for lnum = 1:ht
+    for bnum = 1:nbands
+      band = spyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1));
+      range((lnum-1)*nbands+bnum+1) = scale^(lnum-1);
+      [bmn,bmx] = range2(band);
+      mn = min(mn, bmn);
+      mx = max(mx, bmx);
+    end    
+  end
+  range = range * [mn mx];              % outer product
+  band = pyrLow(pyr,pind);
+  [mn,mx] = range2(band);
+  range(nind,:) = [mn, mx];
+
+elseif strcmp(range,'indep1')
+  range = zeros(nind,2);
+  for bnum = 1:nind
+    band = pyrBand(pyr,pind,bnum);
+    [mn,mx] = range2(band);
+    range(bnum,:) =  [mn mx];
+  end
+
+elseif strcmp(range,'auto2')
+  range = ones(nind,1);
+  band = spyrHigh(pyr,pind);
+  sqsum = sum(sum(band.^2));  numpixels = prod(size(band));
+  for lnum = 1:ht
+    for bnum = 1:nbands
+      band = spyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1));
+      sqsum = sqsum + sum(sum(band.^2));
+      numpixels = numpixels + prod(size(band));
+      range((lnum-1)*nbands+bnum+1) = scale^(lnum-1);
+    end    
+  end
+  stdev = sqrt(sqsum/(numpixels-1));
+  range = range * [ -3*stdev 3*stdev ]; % outer product
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+
+elseif strcmp(range,'indep2')
+  range = zeros(nind,2);
+  for bnum = 1:(nind-1)
+    band = pyrBand(pyr,pind,bnum);
+    stdev = sqrt(var2(band));
+    range(bnum,:) =  [ -3*stdev 3*stdev ];
+  end
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+  
+elseif isstr(range)
+  error(sprintf('Bad RANGE argument: %s',range))
+  
+elseif ((size(range,1) == 1) & (size(range,2) == 2))
+  scales = scale.^[0:(ht-1)];
+  scales = ones(nbands,1) * scales;   %outer product
+  scales = [1; scales(:); scale^ht];  %tack on highpass and lowpass
+  range = scales * range;               % outer product
+  band = pyrLow(pyr,pind);
+  range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:));
+
+end
+
+% CLEAR FIGURE:
+clf;
+
+colormap(gray);
+cmap = get(gcf,'Colormap');
+nshades = size(cmap,1);
+
+%  Find background color index:
+clr = get(gcf,'Color');
+bg = 1;
+dist = norm(cmap(bg,:)-clr);
+for n = 1:nshades
+  ndist = norm(cmap(n,:)-clr);
+  if (ndist < dist)
+    dist = ndist;
+    bg = n;
+  end
+end  
+
+%% Compute positions of subbands:
+llpos = ones(nind,2);
+
+if (nbands == 2)
+  ncols = 1;  nrows = 2;
+else
+  ncols = ceil((nbands+1)/2);   nrows = ceil(nbands/2);
+end
+relpos = [ (1-nrows):0, zeros(1,(ncols-1)); ...
+           zeros(1,nrows), -1:-1:(1-ncols) ]';
+if (nbands > 1)
+  mvpos = [-1 -1];
+else
+  mvpos = [0 -1];
+end
+basepos = [0 0];
+
+for lnum = 1:ht
+  ind1 = (lnum-1)*nbands + 2;
+  sz = pind(ind1,:)+gap;
+  basepos = basepos + mvpos .* sz;
+  if (nbands < 5)                       % to align edges...
+    sz = sz + gap*(ht-lnum+1);
+  end
+  llpos(ind1:ind1+nbands-1,:) = relpos * diag(sz) + ones(nbands,1)*basepos;
+end
+
+% lowpass band
+sz = pind(nind-1,:)+gap;
+basepos = basepos + mvpos .* sz;
+llpos(nind,:) = basepos;
+
+%% Make position list positive, and allocate appropriate image:
+llpos = llpos - ones(nind,1)*min(llpos) + 1;
+llpos(1,:) = [1 1];
+urpos = llpos + pind - 1;
+d_im = bg + zeros(max(urpos));
+
+%% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 
+for bnum=2:nind
+  mult = (nshades-1) / (range(bnum,2)-range(bnum,1));
+  d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ...
+      mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1));
+end
+  
+hh = image(d_im);
+axis('off');
+pixelAxes(size(d_im),'full');
+set(hh,'UserData',range);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/showWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showWpyr.m
new file mode 100755
index 0000000..510e395
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/showWpyr.m
@@ -0,0 +1,204 @@
+% RANGE = showWpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR)
+% 
+% Display a separable QMF/wavelet pyramid, specified by PYR and INDICES
+% (see buildWpyr), in the current figure.
+% 
+% RANGE is a 2-vector specifying the values that map to black and
+% white, respectively.  These values are scaled by
+% LEVEL_SCALE_FACTOR^(lev-1) for bands at each level.  Passing a value
+% of 'auto1' sets RANGE to the min and max values of MATRIX.  'auto2'
+% sets RANGE to 3 standard deviations below and above 0.0.  In both of
+% these cases, the lowpass band is independently scaled.  A value of
+% 'indep1' sets the range of each subband independently, as in a call
+% to showIm(subband,'auto1').  Similarly, 'indep2' causes each subband
+% to be scaled independently as if by showIm(subband,'indep2').
+% The default value for RANGE is 'auto1' for 1D images, and 'auto2' for
+% 2D images.
+% 
+% GAP (optional, default=1) specifies the gap in pixels to leave
+% between subbands (2D images only).  
+% 
+% LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid
+% levels.  This should be set to the sum of the kernel taps of the
+% lowpass filter used to construct the pyramid (default assumes
+% L2-normalized filters, using a value of 2 for 2D images, sqrt(2) for
+% 1D images).
+
+% Eero Simoncelli, 2/97.
+
+function [range] = showWpyr(pyr, pind, range, gap, scale);
+
+% Determine 1D or 2D pyramid:
+if ((pind(1,1) == 1) | (pind(1,2) ==1))
+  nbands = 1;
+else
+  nbands = 3;
+end
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('range') ~= 1)  
+  if (nbands==1)
+    range = 'auto1';
+  else
+    range = 'auto2';
+  end
+end
+                
+if (exist('gap') ~= 1)
+  gap = 1;
+end
+
+if (exist('scale') ~= 1)
+  if (nbands == 1)
+    scale = sqrt(2);
+  else
+    scale = 2;
+  end
+end
+
+%------------------------------------------------------------
+
+ht = wpyrHt(pind);
+nind = size(pind,1);
+
+%% Auto range calculations:
+if strcmp(range,'auto1')
+  range = zeros(nind,1);
+  mn = 0.0; mx = 0.0;
+  for lnum = 1:ht
+    for bnum = 1:nbands
+      band = wpyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1));
+      range((lnum-1)*nbands+bnum) = scale^(lnum-1);
+      [bmn,bmx] = range2(band);
+      mn = min(mn, bmn);  mx = max(mx, bmx);
+    end    
+  end
+  if (nbands == 1)
+    pad = (mx-mn)/12;                   % *** MAGIC NUMBER!!
+    mn = mn-pad;  mx = mx+pad;
+  end
+  range = range * [mn mx];              % outer product
+  band = pyrLow(pyr,pind);
+  [mn,mx] = range2(band);
+  if (nbands == 1)
+    pad = (mx-mn)/12;                   % *** MAGIC NUMBER!!
+    mn = mn-pad;  mx = mx+pad;
+  end
+  range(nind,:) = [mn, mx];
+
+elseif strcmp(range,'indep1')
+  range = zeros(nind,2);
+  for bnum = 1:nind
+    band = pyrBand(pyr,pind,bnum);
+    [mn,mx] = range2(band);
+    if (nbands == 1)
+      pad = (mx-mn)/12;                 % *** MAGIC NUMBER!!
+      mn = mn-pad;  mx = mx+pad;
+    end
+    range(bnum,:) =  [mn mx];
+  end
+
+elseif strcmp(range,'auto2')
+  range = zeros(nind,1);
+  sqsum = 0;  numpixels = 0;
+  for lnum = 1:ht
+    for bnum = 1:nbands
+      band = wpyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1));
+      sqsum = sqsum + sum(sum(band.^2));
+      numpixels = numpixels + prod(size(band));
+      range((lnum-1)*nbands+bnum) = scale^(lnum-1);
+    end    
+  end
+  stdev = sqrt(sqsum/(numpixels-1));
+  range = range * [ -3*stdev 3*stdev ]; % outer product
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+
+elseif strcmp(range,'indep2')
+  range = zeros(nind,2);
+  for bnum = 1:(nind-1)
+    band = pyrBand(pyr,pind,bnum);
+    stdev = sqrt(var2(band));
+    range(bnum,:) =  [ -3*stdev 3*stdev ];
+  end
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+  
+elseif isstr(range)
+  error(sprintf('Bad RANGE argument: %s',range))
+  
+elseif ((size(range,1) == 1) & (size(range,2) == 2))
+  scales = scale.^[0:ht];
+  if (nbands ~= 1)
+    scales = [scales; scales; scales];
+  end
+  range = scales(:) * range;            % outer product
+  band = pyrLow(pyr,pind);
+  range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:));
+
+end
+
+% CLEAR FIGURE:
+clf;
+
+if (nbands == 1)
+
+  %%%%%  1D signal:
+  for bnum=1:nind
+    band = pyrBand(pyr,pind,bnum);
+    subplot(nind,1,nind-bnum+1);
+    plot(band);
+    axis([1, prod(size(band)), range(bnum,:)]);
+  end
+
+else  
+
+  %%%%% 2D signal:
+  colormap(gray);
+  cmap = get(gcf,'Colormap');
+  nshades = size(cmap,1);
+
+  %  Find background color index:
+  clr = get(gcf,'Color');
+  bg = 1;
+  dist = norm(cmap(bg,:)-clr);
+  for n = 1:nshades
+    ndist = norm(cmap(n,:)-clr);
+    if (ndist < dist)
+      dist = ndist;
+      bg = n;
+    end
+  end  
+
+  %% Compute positions of subbands:
+  llpos = ones(nind,2);
+  for lnum = 1:ht
+    ind1 = nbands*(lnum-1) + 1;
+    xpos = pind(ind1,2) + 1 + gap*(ht-lnum+1);
+    ypos = pind(ind1+1,1) + 1 + gap*(ht-lnum+1);
+    llpos(ind1:ind1+2,:) = [ypos 1; 1 xpos; ypos xpos];
+  end
+  llpos(nind,:) = [1 1];  %lowpass
+
+  %% Make position list positive, and allocate appropriate image:
+  llpos = llpos - ones(nind,1)*min(llpos) + 1;
+  urpos = llpos + pind - 1;
+  d_im = bg + zeros(max(urpos));
+
+  %% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 
+  for bnum=1:nind
+    mult = (nshades-1) / (range(bnum,2)-range(bnum,1));
+    d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ...
+        mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1));
+  end
+    
+  hh = image(d_im);
+  axis('off');
+  pixelAxes(size(d_im),'full');
+  set(hh,'UserData',range);
+
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/shrink.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/shrink.m
new file mode 100755
index 0000000..7af0151
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/shrink.m
@@ -0,0 +1,25 @@
+function ts=shrink(t,f)
+
+% It shrinks an image in a factor f
+% in each dimension. 
+%       ts = shrink(t,f)
+% ts may also be complex.
+% See also: expand.m, blurDn.m
+% JPM, April 95, Instituto de Optica, CSIC, Madrid.
+
+[my,mx]=size(t);
+T=fftshift(fft2(t))/f^2;
+Ts=zeros(my/f,mx/f);
+y1=my/2+2-my/(2*f);
+y2=my/2+my/(2*f);
+x1=mx/2+2-mx/(2*f);
+x2=mx/2+mx/(2*f);
+Ts(2:my/f,2:mx/f)=T(y1:y2,x1:x2);
+Ts(1,2:mx/f)=(T(y1-1,x1:x2)+T(y2+1,x1:x2))/2;
+Ts(2:my/f,1)=(T(y1:y2,x1-1)+T(y1:y2,x2+1))/2;
+Ts(1,1)=(T(y1-1,x1-1)+T(y1-1,x2+1)+T(y2+1,x1-1)+T(y2+1,x2+1))/4;
+Ts=fftshift(Ts);
+ts=ifft2(Ts);
+if all(imag(t)==0),
+        ts = real(ts);
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/skew2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/skew2.m
new file mode 100755
index 0000000..623d6ca
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/skew2.m
@@ -0,0 +1,21 @@
+% S = SKEW2(MTX,MEAN,VAR)
+%
+% Sample skew (third moment divided by variance^3/2) of a matrix.
+%  MEAN (optional) and VAR (optional) make the computation faster.
+
+function res = skew2(mtx, mn, v)
+
+if (exist('mn') ~= 1)
+  mn =  mean2(mtx);
+end
+
+if (exist('v') ~= 1)
+  v =  var2(mtx,mn);
+end
+
+if (isreal(mtx))
+  res = mean(mean((mtx-mn).^3)) / (v^(3/2));
+else
+  res = mean(mean(real(mtx-mn).^3)) / (real(v)^(3/2)) + ...
+      i * mean(mean(imag(mtx-mn).^3)) / (imag(v)^(3/2));
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/snr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/snr.m
new file mode 100755
index 0000000..3945d90
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/snr.m
@@ -0,0 +1,10 @@
+function X=SNR(s,n);
+
+% Compute the signal-to-noise ratio in dB
+%       X=SNR(signal,noise);
+% (it does not subtract the means).
+
+es=sum(sum(abs(s).^2))+0.0000001;
+en=sum(sum(abs(n).^2))+0.0000001;
+X=10*log10(es/en);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp0Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp0Filters.m
new file mode 100755
index 0000000..6b25e36
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp0Filters.m
@@ -0,0 +1,72 @@
+% Steerable pyramid filters.  Transform described  in:
+%
+% @INPROCEEDINGS{Simoncelli95b,
+%       TITLE = "The Steerable Pyramid: A Flexible Architecture for
+%                Multi-Scale Derivative Computation",
+%       AUTHOR = "E P Simoncelli and W T Freeman",
+%       BOOKTITLE = "Second Int'l Conf on Image Processing",
+%       ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 }
+%
+% Filter kernel design described in:
+%
+%@INPROCEEDINGS{Karasaridis96,
+%       TITLE = "A Filter Design Technique for 
+%               Steerable Pyramid Image Transforms",
+%       AUTHOR = "A Karasaridis and E P Simoncelli",
+%       BOOKTITLE = "ICASSP",   ADDRESS = "Atlanta, GA",
+%       MONTH = "May",  YEAR = 1996 }
+
+% Eero Simoncelli, 6/96.
+
+function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp0Filters();
+
+harmonics = [ 0 ];
+
+lo0filt = [ ...
+-4.514000e-04 -1.137100e-04 -3.725800e-04 -3.743860e-03 -3.725800e-04 -1.137100e-04 -4.514000e-04
+-1.137100e-04 -6.119520e-03 -1.344160e-02 -7.563200e-03 -1.344160e-02 -6.119520e-03 -1.137100e-04
+-3.725800e-04 -1.344160e-02 6.441488e-02 1.524935e-01 6.441488e-02 -1.344160e-02 -3.725800e-04 
+-3.743860e-03 -7.563200e-03 1.524935e-01 3.153017e-01 1.524935e-01 -7.563200e-03 -3.743860e-03 
+-3.725800e-04 -1.344160e-02 6.441488e-02 1.524935e-01 6.441488e-02 -1.344160e-02 -3.725800e-04 
+-1.137100e-04 -6.119520e-03 -1.344160e-02 -7.563200e-03 -1.344160e-02 -6.119520e-03 -1.137100e-04 
+-4.514000e-04 -1.137100e-04 -3.725800e-04 -3.743860e-03 -3.725800e-04 -1.137100e-04 -4.514000e-04];
+
+lofilt = [ ...
+-2.257000e-04 -8.064400e-04 -5.686000e-05 8.741400e-04 -1.862800e-04 -1.031640e-03 -1.871920e-03 -1.031640e-03 -1.862800e-04 8.741400e-04 -5.686000e-05 -8.064400e-04 -2.257000e-04 
+-8.064400e-04 1.417620e-03 -1.903800e-04 -2.449060e-03 -4.596420e-03 -7.006740e-03 -6.948900e-03 -7.006740e-03 -4.596420e-03 -2.449060e-03 -1.903800e-04 1.417620e-03 -8.064400e-04 
+-5.686000e-05 -1.903800e-04 -3.059760e-03 -6.401000e-03 -6.720800e-03 -5.236180e-03 -3.781600e-03 -5.236180e-03 -6.720800e-03 -6.401000e-03 -3.059760e-03 -1.903800e-04 -5.686000e-05 
+8.741400e-04 -2.449060e-03 -6.401000e-03 -5.260020e-03 3.938620e-03 1.722078e-02 2.449600e-02 1.722078e-02 3.938620e-03 -5.260020e-03 -6.401000e-03 -2.449060e-03 8.741400e-04 
+-1.862800e-04 -4.596420e-03 -6.720800e-03 3.938620e-03 3.220744e-02 6.306262e-02 7.624674e-02 6.306262e-02 3.220744e-02 3.938620e-03 -6.720800e-03 -4.596420e-03 -1.862800e-04 
+-1.031640e-03 -7.006740e-03 -5.236180e-03 1.722078e-02 6.306262e-02 1.116388e-01 1.348999e-01 1.116388e-01 6.306262e-02 1.722078e-02 -5.236180e-03 -7.006740e-03 -1.031640e-03 
+-1.871920e-03 -6.948900e-03 -3.781600e-03 2.449600e-02 7.624674e-02 1.348999e-01 1.576508e-01 1.348999e-01 7.624674e-02 2.449600e-02 -3.781600e-03 -6.948900e-03 -1.871920e-03 
+-1.031640e-03 -7.006740e-03 -5.236180e-03 1.722078e-02 6.306262e-02 1.116388e-01 1.348999e-01 1.116388e-01 6.306262e-02 1.722078e-02 -5.236180e-03 -7.006740e-03 -1.031640e-03 
+-1.862800e-04 -4.596420e-03 -6.720800e-03 3.938620e-03 3.220744e-02 6.306262e-02 7.624674e-02 6.306262e-02 3.220744e-02 3.938620e-03 -6.720800e-03 -4.596420e-03 -1.862800e-04
+8.741400e-04 -2.449060e-03 -6.401000e-03 -5.260020e-03 3.938620e-03 1.722078e-02 2.449600e-02 1.722078e-02 3.938620e-03 -5.260020e-03 -6.401000e-03 -2.449060e-03 8.741400e-04 
+-5.686000e-05 -1.903800e-04 -3.059760e-03 -6.401000e-03 -6.720800e-03 -5.236180e-03 -3.781600e-03 -5.236180e-03 -6.720800e-03 -6.401000e-03 -3.059760e-03 -1.903800e-04 -5.686000e-05 
+-8.064400e-04 1.417620e-03 -1.903800e-04 -2.449060e-03 -4.596420e-03 -7.006740e-03 -6.948900e-03 -7.006740e-03 -4.596420e-03 -2.449060e-03 -1.903800e-04 1.417620e-03 -8.064400e-04 
+-2.257000e-04 -8.064400e-04 -5.686000e-05 8.741400e-04 -1.862800e-04 -1.031640e-03 -1.871920e-03 -1.031640e-03 -1.862800e-04 8.741400e-04 -5.686000e-05 -8.064400e-04 -2.257000e-04]; 
+
+mtx = [ 1.000000 ];
+
+hi0filt = [...
+5.997200e-04 -6.068000e-05 -3.324900e-04 -3.325600e-04 -2.406600e-04 -3.325600e-04 -3.324900e-04 -6.068000e-05 5.997200e-04
+-6.068000e-05 1.263100e-04 4.927100e-04 1.459700e-04 -3.732100e-04 1.459700e-04 4.927100e-04 1.263100e-04 -6.068000e-05 
+-3.324900e-04 4.927100e-04 -1.616650e-03 -1.437358e-02 -2.420138e-02 -1.437358e-02 -1.616650e-03 4.927100e-04 -3.324900e-04 
+-3.325600e-04 1.459700e-04 -1.437358e-02 -6.300923e-02 -9.623594e-02 -6.300923e-02 -1.437358e-02 1.459700e-04 -3.325600e-04 
+-2.406600e-04 -3.732100e-04 -2.420138e-02 -9.623594e-02 8.554893e-01 -9.623594e-02 -2.420138e-02 -3.732100e-04 -2.406600e-04 
+-3.325600e-04 1.459700e-04 -1.437358e-02 -6.300923e-02 -9.623594e-02 -6.300923e-02 -1.437358e-02 1.459700e-04 -3.325600e-04 
+-3.324900e-04 4.927100e-04 -1.616650e-03 -1.437358e-02 -2.420138e-02 -1.437358e-02 -1.616650e-03 4.927100e-04 -3.324900e-04 
+-6.068000e-05 1.263100e-04 4.927100e-04 1.459700e-04 -3.732100e-04 1.459700e-04 4.927100e-04 1.263100e-04 -6.068000e-05 
+5.997200e-04 -6.068000e-05 -3.324900e-04 -3.325600e-04 -2.406600e-04 -3.325600e-04 -3.324900e-04 -6.068000e-05 5.997200e-04 ];
+
+bfilts = [ ...
+-9.066000e-05 -1.738640e-03 -4.942500e-03 -7.889390e-03 -1.009473e-02 -7.889390e-03 -4.942500e-03 -1.738640e-03 -9.066000e-05 ...
+-1.738640e-03 -4.625150e-03 -7.272540e-03 -7.623410e-03 -9.091950e-03 -7.623410e-03 -7.272540e-03 -4.625150e-03 -1.738640e-03 ...
+-4.942500e-03 -7.272540e-03 -2.129540e-02 -2.435662e-02 -3.487008e-02 -2.435662e-02 -2.129540e-02 -7.272540e-03 -4.942500e-03  ...
+-7.889390e-03 -7.623410e-03 -2.435662e-02 -1.730466e-02 -3.158605e-02 -1.730466e-02 -2.435662e-02 -7.623410e-03 -7.889390e-03  ...
+-1.009473e-02 -9.091950e-03 -3.487008e-02 -3.158605e-02 9.464195e-01 -3.158605e-02 -3.487008e-02 -9.091950e-03 -1.009473e-02  ...
+-7.889390e-03 -7.623410e-03 -2.435662e-02 -1.730466e-02 -3.158605e-02 -1.730466e-02 -2.435662e-02 -7.623410e-03 -7.889390e-03 ...
+-4.942500e-03 -7.272540e-03 -2.129540e-02 -2.435662e-02 -3.487008e-02 -2.435662e-02 -2.129540e-02 -7.272540e-03 -4.942500e-03  ...
+-1.738640e-03 -4.625150e-03 -7.272540e-03 -7.623410e-03 -9.091950e-03 -7.623410e-03 -7.272540e-03 -4.625150e-03 -1.738640e-03  ...
+-9.066000e-05 -1.738640e-03 -4.942500e-03 -7.889390e-03 -1.009473e-02 -7.889390e-03 -4.942500e-03 -1.738640e-03 -9.066000e-05 ]';
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp1Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp1Filters.m
new file mode 100755
index 0000000..215e651
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp1Filters.m
@@ -0,0 +1,91 @@
+% Steerable pyramid filters.  Transform described  in:
+%
+% @INPROCEEDINGS{Simoncelli95b,
+%       TITLE = "The Steerable Pyramid: A Flexible Architecture for
+%                Multi-Scale Derivative Computation",
+%       AUTHOR = "E P Simoncelli and W T Freeman",
+%       BOOKTITLE = "Second Int'l Conf on Image Processing",
+%       ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 }
+%
+% Filter kernel design described in:
+%
+%@INPROCEEDINGS{Karasaridis96,
+%       TITLE = "A Filter Design Technique for 
+%               Steerable Pyramid Image Transforms",
+%       AUTHOR = "A Karasaridis and E P Simoncelli",
+%       BOOKTITLE = "ICASSP",   ADDRESS = "Atlanta, GA",
+%       MONTH = "May",  YEAR = 1996 }
+
+% Eero Simoncelli, 6/96.
+
+function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp1Filters();
+
+harmonics = [ 1 ];
+
+%% filters only contain first harmonic.
+mtx = eye(2);
+
+lo0filt = [ ...
+-8.701000e-05 -1.354280e-03 -1.601260e-03 -5.033700e-04 2.524010e-03 -5.033700e-04 -1.601260e-03 -1.354280e-03 -8.701000e-05
+-1.354280e-03 2.921580e-03 7.522720e-03 8.224420e-03 1.107620e-03 8.224420e-03 7.522720e-03 2.921580e-03 -1.354280e-03 
+-1.601260e-03 7.522720e-03 -7.061290e-03 -3.769487e-02 -3.297137e-02 -3.769487e-02 -7.061290e-03 7.522720e-03 -1.601260e-03  
+-5.033700e-04 8.224420e-03 -3.769487e-02 4.381320e-02 1.811603e-01 4.381320e-02 -3.769487e-02 8.224420e-03 -5.033700e-04 
+2.524010e-03 1.107620e-03 -3.297137e-02 1.811603e-01 4.376250e-01 1.811603e-01 -3.297137e-02 1.107620e-03 2.524010e-03  
+-5.033700e-04 8.224420e-03 -3.769487e-02 4.381320e-02 1.811603e-01 4.381320e-02 -3.769487e-02 8.224420e-03 -5.033700e-04  
+-1.601260e-03 7.522720e-03 -7.061290e-03 -3.769487e-02 -3.297137e-02 -3.769487e-02 -7.061290e-03 7.522720e-03 -1.601260e-03  
+-1.354280e-03 2.921580e-03 7.522720e-03 8.224420e-03 1.107620e-03 8.224420e-03 7.522720e-03 2.921580e-03 -1.354280e-03  
+-8.701000e-05 -1.354280e-03 -1.601260e-03 -5.033700e-04 2.524010e-03 -5.033700e-04 -1.601260e-03 -1.354280e-03 -8.701000e-05 
+];
+
+lofilt = [ ...
+-4.350000e-05 1.207800e-04 -6.771400e-04 -1.243400e-04 -8.006400e-04 -1.597040e-03 -2.516800e-04 -4.202000e-04 1.262000e-03 -4.202000e-04 -2.516800e-04 -1.597040e-03 -8.006400e-04 -1.243400e-04 -6.771400e-04 1.207800e-04 -4.350000e-05  ; ...
+1.207800e-04 4.460600e-04 -5.814600e-04 5.621600e-04 -1.368800e-04 2.325540e-03 2.889860e-03 4.287280e-03 5.589400e-03 4.287280e-03 2.889860e-03 2.325540e-03 -1.368800e-04 5.621600e-04 -5.814600e-04 4.460600e-04 1.207800e-04  ; ...
+-6.771400e-04 -5.814600e-04 1.460780e-03 2.160540e-03 3.761360e-03 3.080980e-03 4.112200e-03 2.221220e-03 5.538200e-04 2.221220e-03 4.112200e-03 3.080980e-03 3.761360e-03 2.160540e-03 1.460780e-03 -5.814600e-04 -6.771400e-04  ; ...
+-1.243400e-04 5.621600e-04 2.160540e-03 3.175780e-03 3.184680e-03 -1.777480e-03 -7.431700e-03 -9.056920e-03 -9.637220e-03 -9.056920e-03 -7.431700e-03 -1.777480e-03 3.184680e-03 3.175780e-03 2.160540e-03 5.621600e-04 -1.243400e-04  ; ...
+-8.006400e-04 -1.368800e-04 3.761360e-03 3.184680e-03 -3.530640e-03 -1.260420e-02 -1.884744e-02 -1.750818e-02 -1.648568e-02 -1.750818e-02 -1.884744e-02 -1.260420e-02 -3.530640e-03 3.184680e-03 3.761360e-03 -1.368800e-04 -8.006400e-04  ; ...
+-1.597040e-03 2.325540e-03 3.080980e-03 -1.777480e-03 -1.260420e-02 -2.022938e-02 -1.109170e-02 3.955660e-03 1.438512e-02 3.955660e-03 -1.109170e-02 -2.022938e-02 -1.260420e-02 -1.777480e-03 3.080980e-03 2.325540e-03 -1.597040e-03  ; ...
+-2.516800e-04 2.889860e-03 4.112200e-03 -7.431700e-03 -1.884744e-02 -1.109170e-02 2.190660e-02 6.806584e-02 9.058014e-02 6.806584e-02 2.190660e-02 -1.109170e-02 -1.884744e-02 -7.431700e-03 4.112200e-03 2.889860e-03 -2.516800e-04  ; ...
+-4.202000e-04 4.287280e-03 2.221220e-03 -9.056920e-03 -1.750818e-02 3.955660e-03 6.806584e-02 1.445500e-01 1.773651e-01 1.445500e-01 6.806584e-02 3.955660e-03 -1.750818e-02 -9.056920e-03 2.221220e-03 4.287280e-03 -4.202000e-04  ; ...
+1.262000e-03 5.589400e-03 5.538200e-04 -9.637220e-03 -1.648568e-02 1.438512e-02 9.058014e-02 1.773651e-01 2.120374e-01 1.773651e-01 9.058014e-02 1.438512e-02 -1.648568e-02 -9.637220e-03 5.538200e-04 5.589400e-03 1.262000e-03  ; ...
+-4.202000e-04 4.287280e-03 2.221220e-03 -9.056920e-03 -1.750818e-02 3.955660e-03 6.806584e-02 1.445500e-01 1.773651e-01 1.445500e-01 6.806584e-02 3.955660e-03 -1.750818e-02 -9.056920e-03 2.221220e-03 4.287280e-03 -4.202000e-04  ; ...
+-2.516800e-04 2.889860e-03 4.112200e-03 -7.431700e-03 -1.884744e-02 -1.109170e-02 2.190660e-02 6.806584e-02 9.058014e-02 6.806584e-02 2.190660e-02 -1.109170e-02 -1.884744e-02 -7.431700e-03 4.112200e-03 2.889860e-03 -2.516800e-04  ; ...
+-1.597040e-03 2.325540e-03 3.080980e-03 -1.777480e-03 -1.260420e-02 -2.022938e-02 -1.109170e-02 3.955660e-03 1.438512e-02 3.955660e-03 -1.109170e-02 -2.022938e-02 -1.260420e-02 -1.777480e-03 3.080980e-03 2.325540e-03 -1.597040e-03  ; ...
+-8.006400e-04 -1.368800e-04 3.761360e-03 3.184680e-03 -3.530640e-03 -1.260420e-02 -1.884744e-02 -1.750818e-02 -1.648568e-02 -1.750818e-02 -1.884744e-02 -1.260420e-02 -3.530640e-03 3.184680e-03 3.761360e-03 -1.368800e-04 -8.006400e-04  ; ...
+-1.243400e-04 5.621600e-04 2.160540e-03 3.175780e-03 3.184680e-03 -1.777480e-03 -7.431700e-03 -9.056920e-03 -9.637220e-03 -9.056920e-03 -7.431700e-03 -1.777480e-03 3.184680e-03 3.175780e-03 2.160540e-03 5.621600e-04 -1.243400e-04  ; ...
+-6.771400e-04 -5.814600e-04 1.460780e-03 2.160540e-03 3.761360e-03 3.080980e-03 4.112200e-03 2.221220e-03 5.538200e-04 2.221220e-03 4.112200e-03 3.080980e-03 3.761360e-03 2.160540e-03 1.460780e-03 -5.814600e-04 -6.771400e-04  ; ...
+1.207800e-04 4.460600e-04 -5.814600e-04 5.621600e-04 -1.368800e-04 2.325540e-03 2.889860e-03 4.287280e-03 5.589400e-03 4.287280e-03 2.889860e-03 2.325540e-03 -1.368800e-04 5.621600e-04 -5.814600e-04 4.460600e-04 1.207800e-04  ; ...
+-4.350000e-05 1.207800e-04 -6.771400e-04 -1.243400e-04 -8.006400e-04 -1.597040e-03 -2.516800e-04 -4.202000e-04 1.262000e-03 -4.202000e-04 -2.516800e-04 -1.597040e-03 -8.006400e-04 -1.243400e-04 -6.771400e-04 1.207800e-04 -4.350000e-05 ];
+
+hi0filt = [...
+-9.570000e-04 -2.424100e-04 -1.424720e-03 -8.742600e-04 -1.166810e-03 -8.742600e-04 -1.424720e-03 -2.424100e-04 -9.570000e-04 ; ...
+-2.424100e-04 -4.317530e-03 8.998600e-04 9.156420e-03 1.098012e-02 9.156420e-03 8.998600e-04 -4.317530e-03 -2.424100e-04  ; ...
+-1.424720e-03 8.998600e-04 1.706347e-02 1.094866e-02 -5.897780e-03 1.094866e-02 1.706347e-02 8.998600e-04 -1.424720e-03  ; ...
+-8.742600e-04 9.156420e-03 1.094866e-02 -7.841370e-02 -1.562827e-01 -7.841370e-02 1.094866e-02 9.156420e-03 -8.742600e-04  ; ...
+-1.166810e-03 1.098012e-02 -5.897780e-03 -1.562827e-01 7.282593e-01 -1.562827e-01 -5.897780e-03 1.098012e-02 -1.166810e-03  ; ...
+-8.742600e-04 9.156420e-03 1.094866e-02 -7.841370e-02 -1.562827e-01 -7.841370e-02 1.094866e-02 9.156420e-03 -8.742600e-04  ; ...
+-1.424720e-03 8.998600e-04 1.706347e-02 1.094866e-02 -5.897780e-03 1.094866e-02 1.706347e-02 8.998600e-04 -1.424720e-03  ; ...
+-2.424100e-04 -4.317530e-03 8.998600e-04 9.156420e-03 1.098012e-02 9.156420e-03 8.998600e-04 -4.317530e-03 -2.424100e-04  ; ...
+-9.570000e-04 -2.424100e-04 -1.424720e-03 -8.742600e-04 -1.166810e-03 -8.742600e-04 -1.424720e-03 -2.424100e-04 -9.570000e-04 ];
+
+bfilts = -[ ...
+6.125880e-03 -8.052600e-03 -2.103714e-02 -1.536890e-02 -1.851466e-02 -1.536890e-02 -2.103714e-02 -8.052600e-03 6.125880e-03  ...
+-1.287416e-02 -9.611520e-03 1.023569e-02 6.009450e-03 1.872620e-03 6.009450e-03 1.023569e-02 -9.611520e-03 -1.287416e-02  ...
+-5.641530e-03 4.168400e-03 -2.382180e-02 -5.375324e-02 -2.076086e-02 -5.375324e-02 -2.382180e-02 4.168400e-03 -5.641530e-03  ...
+-8.957260e-03 -1.751170e-03 -1.836909e-02 1.265655e-01 2.996168e-01 1.265655e-01 -1.836909e-02 -1.751170e-03 -8.957260e-03  ...
+0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00  ...
+8.957260e-03 1.751170e-03 1.836909e-02 -1.265655e-01 -2.996168e-01 -1.265655e-01 1.836909e-02 1.751170e-03 8.957260e-03  ...
+5.641530e-03 -4.168400e-03 2.382180e-02 5.375324e-02 2.076086e-02 5.375324e-02 2.382180e-02 -4.168400e-03 5.641530e-03  ...
+1.287416e-02 9.611520e-03 -1.023569e-02 -6.009450e-03 -1.872620e-03 -6.009450e-03 -1.023569e-02 9.611520e-03 1.287416e-02  ...
+-6.125880e-03 8.052600e-03 2.103714e-02 1.536890e-02 1.851466e-02 1.536890e-02 2.103714e-02 8.052600e-03 -6.125880e-03; ...
+...
+-6.125880e-03 1.287416e-02 5.641530e-03 8.957260e-03 0.000000e+00 -8.957260e-03 -5.641530e-03 -1.287416e-02 6.125880e-03  ...
+8.052600e-03 9.611520e-03 -4.168400e-03 1.751170e-03 0.000000e+00 -1.751170e-03 4.168400e-03 -9.611520e-03 -8.052600e-03  ...
+2.103714e-02 -1.023569e-02 2.382180e-02 1.836909e-02 0.000000e+00 -1.836909e-02 -2.382180e-02 1.023569e-02 -2.103714e-02  ...
+1.536890e-02 -6.009450e-03 5.375324e-02 -1.265655e-01 0.000000e+00 1.265655e-01 -5.375324e-02 6.009450e-03 -1.536890e-02  ...
+1.851466e-02 -1.872620e-03 2.076086e-02 -2.996168e-01 0.000000e+00 2.996168e-01 -2.076086e-02 1.872620e-03 -1.851466e-02  ...
+1.536890e-02 -6.009450e-03 5.375324e-02 -1.265655e-01 0.000000e+00 1.265655e-01 -5.375324e-02 6.009450e-03 -1.536890e-02  ...
+2.103714e-02 -1.023569e-02 2.382180e-02 1.836909e-02 0.000000e+00 -1.836909e-02 -2.382180e-02 1.023569e-02 -2.103714e-02  ...
+8.052600e-03 9.611520e-03 -4.168400e-03 1.751170e-03 0.000000e+00 -1.751170e-03 4.168400e-03 -9.611520e-03 -8.052600e-03  ...
+-6.125880e-03 1.287416e-02 5.641530e-03 8.957260e-03 0.000000e+00 -8.957260e-03 -5.641530e-03 -1.287416e-02 6.125880e-03 ...
+]';
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp3Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp3Filters.m
new file mode 100755
index 0000000..c9cfaaf
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp3Filters.m
@@ -0,0 +1,121 @@
+% Steerable pyramid filters.  Transform described  in:
+%
+% @INPROCEEDINGS{Simoncelli95b,
+%       TITLE = "The Steerable Pyramid: A Flexible Architecture for
+%                Multi-Scale Derivative Computation",
+%       AUTHOR = "E P Simoncelli and W T Freeman",
+%       BOOKTITLE = "Second Int'l Conf on Image Processing",
+%       ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 }
+%
+% Filter kernel design described in:
+%
+%@INPROCEEDINGS{Karasaridis96,
+%       TITLE = "A Filter Design Technique for 
+%               Steerable Pyramid Image Transforms",
+%       AUTHOR = "A Karasaridis and E P Simoncelli",
+%       BOOKTITLE = "ICASSP",   ADDRESS = "Atlanta, GA",
+%       MONTH = "May",  YEAR = 1996 }
+
+% Eero Simoncelli, 6/96.
+
+function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp3Filters();
+
+harmonics = [1 3];
+
+mtx = [ ...
+    0.5000    0.3536         0   -0.3536
+   -0.0000    0.3536    0.5000    0.3536
+    0.5000   -0.3536         0    0.3536
+   -0.0000    0.3536   -0.5000    0.3536];
+
+hi0filt = [ 
+-4.0483998600E-4  -6.2596000498E-4  -3.7829999201E-5  8.8387000142E-4  1.5450799838E-3  1.9235999789E-3  2.0687500946E-3  2.0898699295E-3  2.0687500946E-3  1.9235999789E-3  1.5450799838E-3  8.8387000142E-4  -3.7829999201E-5  -6.2596000498E-4  -4.0483998600E-4
+-6.2596000498E-4  -3.2734998967E-4  7.7435001731E-4  1.5874400269E-3  2.1750701126E-3  2.5626500137E-3  2.2892199922E-3  1.9755100366E-3  2.2892199922E-3  2.5626500137E-3  2.1750701126E-3  1.5874400269E-3  7.7435001731E-4  -3.2734998967E-4  -6.2596000498E-4
+-3.7829999201E-5  7.7435001731E-4  1.1793200392E-3  1.4050999889E-3  2.2253401112E-3  2.1145299543E-3  3.3578000148E-4  -8.3368999185E-4  3.3578000148E-4  2.1145299543E-3  2.2253401112E-3  1.4050999889E-3  1.1793200392E-3  7.7435001731E-4  -3.7829999201E-5
+8.8387000142E-4  1.5874400269E-3  1.4050999889E-3  1.2960999738E-3  -4.9274001503E-4  -3.1295299996E-3  -4.5751798898E-3  -5.1014497876E-3  -4.5751798898E-3  -3.1295299996E-3  -4.9274001503E-4  1.2960999738E-3  1.4050999889E-3  1.5874400269E-3  8.8387000142E-4
+1.5450799838E-3  2.1750701126E-3  2.2253401112E-3  -4.9274001503E-4  -6.3222697936E-3  -2.7556000277E-3  5.3632198833E-3  7.3032598011E-3  5.3632198833E-3  -2.7556000277E-3  -6.3222697936E-3  -4.9274001503E-4  2.2253401112E-3  2.1750701126E-3  1.5450799838E-3
+1.9235999789E-3  2.5626500137E-3  2.1145299543E-3  -3.1295299996E-3  -2.7556000277E-3  1.3962360099E-2  7.8046298586E-3  -9.3812197447E-3  7.8046298586E-3  1.3962360099E-2  -2.7556000277E-3  -3.1295299996E-3  2.1145299543E-3  2.5626500137E-3  1.9235999789E-3
+2.0687500946E-3  2.2892199922E-3  3.3578000148E-4  -4.5751798898E-3  5.3632198833E-3  7.8046298586E-3  -7.9501636326E-2  -0.1554141641      -7.9501636326E-2  7.8046298586E-3  5.3632198833E-3  -4.5751798898E-3  3.3578000148E-4  2.2892199922E-3  2.0687500946E-3
+2.0898699295E-3  1.9755100366E-3  -8.3368999185E-4  -5.1014497876E-3  7.3032598011E-3  -9.3812197447E-3  -0.1554141641      0.7303866148      -0.1554141641      -9.3812197447E-3  7.3032598011E-3  -5.1014497876E-3  -8.3368999185E-4  1.9755100366E-3  2.0898699295E-3
+2.0687500946E-3  2.2892199922E-3  3.3578000148E-4  -4.5751798898E-3  5.3632198833E-3  7.8046298586E-3  -7.9501636326E-2  -0.1554141641      -7.9501636326E-2  7.8046298586E-3  5.3632198833E-3  -4.5751798898E-3  3.3578000148E-4  2.2892199922E-3  2.0687500946E-3
+1.9235999789E-3  2.5626500137E-3  2.1145299543E-3  -3.1295299996E-3  -2.7556000277E-3  1.3962360099E-2  7.8046298586E-3  -9.3812197447E-3  7.8046298586E-3  1.3962360099E-2  -2.7556000277E-3  -3.1295299996E-3  2.1145299543E-3  2.5626500137E-3  1.9235999789E-3
+1.5450799838E-3  2.1750701126E-3  2.2253401112E-3  -4.9274001503E-4  -6.3222697936E-3  -2.7556000277E-3  5.3632198833E-3  7.3032598011E-3  5.3632198833E-3  -2.7556000277E-3  -6.3222697936E-3  -4.9274001503E-4  2.2253401112E-3  2.1750701126E-3  1.5450799838E-3
+8.8387000142E-4  1.5874400269E-3  1.4050999889E-3  1.2960999738E-3  -4.9274001503E-4  -3.1295299996E-3  -4.5751798898E-3  -5.1014497876E-3  -4.5751798898E-3  -3.1295299996E-3  -4.9274001503E-4  1.2960999738E-3  1.4050999889E-3  1.5874400269E-3  8.8387000142E-4
+-3.7829999201E-5  7.7435001731E-4  1.1793200392E-3  1.4050999889E-3  2.2253401112E-3  2.1145299543E-3  3.3578000148E-4  -8.3368999185E-4  3.3578000148E-4  2.1145299543E-3  2.2253401112E-3  1.4050999889E-3  1.1793200392E-3  7.7435001731E-4  -3.7829999201E-5
+-6.2596000498E-4  -3.2734998967E-4  7.7435001731E-4  1.5874400269E-3  2.1750701126E-3  2.5626500137E-3  2.2892199922E-3  1.9755100366E-3  2.2892199922E-3  2.5626500137E-3  2.1750701126E-3  1.5874400269E-3  7.7435001731E-4  -3.2734998967E-4  -6.2596000498E-4
+-4.0483998600E-4  -6.2596000498E-4  -3.7829999201E-5  8.8387000142E-4  1.5450799838E-3  1.9235999789E-3  2.0687500946E-3  2.0898699295E-3  2.0687500946E-3  1.9235999789E-3  1.5450799838E-3  8.8387000142E-4  -3.7829999201E-5  -6.2596000498E-4  -4.0483998600E-4
+];
+
+lo0filt = [
+-8.7009997515E-5  -1.3542800443E-3  -1.6012600390E-3  -5.0337001448E-4  2.5240099058E-3  -5.0337001448E-4  -1.6012600390E-3  -1.3542800443E-3  -8.7009997515E-5
+-1.3542800443E-3  2.9215801042E-3  7.5227199122E-3  8.2244202495E-3  1.1076199589E-3  8.2244202495E-3  7.5227199122E-3  2.9215801042E-3  -1.3542800443E-3
+-1.6012600390E-3  7.5227199122E-3  -7.0612900890E-3  -3.7694871426E-2  -3.2971370965E-2  -3.7694871426E-2  -7.0612900890E-3  7.5227199122E-3  -1.6012600390E-3
+-5.0337001448E-4  8.2244202495E-3  -3.7694871426E-2  4.3813198805E-2  0.1811603010      4.3813198805E-2  -3.7694871426E-2  8.2244202495E-3  -5.0337001448E-4
+2.5240099058E-3  1.1076199589E-3  -3.2971370965E-2  0.1811603010      0.4376249909      0.1811603010      -3.2971370965E-2  1.1076199589E-3  2.5240099058E-3
+-5.0337001448E-4  8.2244202495E-3  -3.7694871426E-2  4.3813198805E-2  0.1811603010      4.3813198805E-2  -3.7694871426E-2  8.2244202495E-3  -5.0337001448E-4
+-1.6012600390E-3  7.5227199122E-3  -7.0612900890E-3  -3.7694871426E-2  -3.2971370965E-2  -3.7694871426E-2  -7.0612900890E-3  7.5227199122E-3  -1.6012600390E-3
+-1.3542800443E-3  2.9215801042E-3  7.5227199122E-3  8.2244202495E-3  1.1076199589E-3  8.2244202495E-3  7.5227199122E-3  2.9215801042E-3  -1.3542800443E-3
+-8.7009997515E-5  -1.3542800443E-3  -1.6012600390E-3  -5.0337001448E-4  2.5240099058E-3  -5.0337001448E-4  -1.6012600390E-3  -1.3542800443E-3  -8.7009997515E-5
+];
+
+lofilt = [
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+1.2078000145E-4  4.4606000301E-4  -5.8146001538E-4  5.6215998484E-4  -1.3688000035E-4  2.3255399428E-3  2.8898599558E-3  4.2872801423E-3  5.5893999524E-3  4.2872801423E-3  2.8898599558E-3  2.3255399428E-3  -1.3688000035E-4  5.6215998484E-4  -5.8146001538E-4  4.4606000301E-4  1.2078000145E-4
+-6.7714002216E-4  -5.8146001538E-4  1.4607800404E-3  2.1605400834E-3  3.7613599561E-3  3.0809799209E-3  4.1121998802E-3  2.2212199401E-3  5.5381999118E-4  2.2212199401E-3  4.1121998802E-3  3.0809799209E-3  3.7613599561E-3  2.1605400834E-3  1.4607800404E-3  -5.8146001538E-4  -6.7714002216E-4
+-1.2434000382E-4  5.6215998484E-4  2.1605400834E-3  3.1757799443E-3  3.1846798956E-3  -1.7774800071E-3  -7.4316998944E-3  -9.0569201857E-3  -9.6372198313E-3  -9.0569201857E-3  -7.4316998944E-3  -1.7774800071E-3  3.1846798956E-3  3.1757799443E-3  2.1605400834E-3  5.6215998484E-4  -1.2434000382E-4
+-8.0063997302E-4  -1.3688000035E-4  3.7613599561E-3  3.1846798956E-3  -3.5306399222E-3  -1.2604200281E-2  -1.8847439438E-2  -1.7508180812E-2  -1.6485679895E-2  -1.7508180812E-2  -1.8847439438E-2  -1.2604200281E-2  -3.5306399222E-3  3.1846798956E-3  3.7613599561E-3  -1.3688000035E-4  -8.0063997302E-4
+-1.5970399836E-3  2.3255399428E-3  3.0809799209E-3  -1.7774800071E-3  -1.2604200281E-2  -2.0229380578E-2  -1.1091699824E-2  3.9556599222E-3  1.4385120012E-2  3.9556599222E-3  -1.1091699824E-2  -2.0229380578E-2  -1.2604200281E-2  -1.7774800071E-3  3.0809799209E-3  2.3255399428E-3  -1.5970399836E-3
+-2.5168000138E-4  2.8898599558E-3  4.1121998802E-3  -7.4316998944E-3  -1.8847439438E-2  -1.1091699824E-2  2.1906599402E-2  6.8065837026E-2  9.0580143034E-2  6.8065837026E-2  2.1906599402E-2  -1.1091699824E-2  -1.8847439438E-2  -7.4316998944E-3  4.1121998802E-3  2.8898599558E-3  -2.5168000138E-4
+-4.2019999819E-4  4.2872801423E-3  2.2212199401E-3  -9.0569201857E-3  -1.7508180812E-2  3.9556599222E-3  6.8065837026E-2  0.1445499808      0.1773651242      0.1445499808      6.8065837026E-2  3.9556599222E-3  -1.7508180812E-2  -9.0569201857E-3  2.2212199401E-3  4.2872801423E-3  -4.2019999819E-4
+1.2619999470E-3  5.5893999524E-3  5.5381999118E-4  -9.6372198313E-3  -1.6485679895E-2  1.4385120012E-2  9.0580143034E-2  0.1773651242      0.2120374441      0.1773651242      9.0580143034E-2  1.4385120012E-2  -1.6485679895E-2  -9.6372198313E-3  5.5381999118E-4  5.5893999524E-3  1.2619999470E-3
+-4.2019999819E-4  4.2872801423E-3  2.2212199401E-3  -9.0569201857E-3  -1.7508180812E-2  3.9556599222E-3  6.8065837026E-2  0.1445499808      0.1773651242      0.1445499808      6.8065837026E-2  3.9556599222E-3  -1.7508180812E-2  -9.0569201857E-3  2.2212199401E-3  4.2872801423E-3  -4.2019999819E-4
+-2.5168000138E-4  2.8898599558E-3  4.1121998802E-3  -7.4316998944E-3  -1.8847439438E-2  -1.1091699824E-2  2.1906599402E-2  6.8065837026E-2  9.0580143034E-2  6.8065837026E-2  2.1906599402E-2  -1.1091699824E-2  -1.8847439438E-2  -7.4316998944E-3  4.1121998802E-3  2.8898599558E-3  -2.5168000138E-4
+-1.5970399836E-3  2.3255399428E-3  3.0809799209E-3  -1.7774800071E-3  -1.2604200281E-2  -2.0229380578E-2  -1.1091699824E-2  3.9556599222E-3  1.4385120012E-2  3.9556599222E-3  -1.1091699824E-2  -2.0229380578E-2  -1.2604200281E-2  -1.7774800071E-3  3.0809799209E-3  2.3255399428E-3  -1.5970399836E-3
+-8.0063997302E-4  -1.3688000035E-4  3.7613599561E-3  3.1846798956E-3  -3.5306399222E-3  -1.2604200281E-2  -1.8847439438E-2  -1.7508180812E-2  -1.6485679895E-2  -1.7508180812E-2  -1.8847439438E-2  -1.2604200281E-2  -3.5306399222E-3  3.1846798956E-3  3.7613599561E-3  -1.3688000035E-4  -8.0063997302E-4
+-1.2434000382E-4  5.6215998484E-4  2.1605400834E-3  3.1757799443E-3  3.1846798956E-3  -1.7774800071E-3  -7.4316998944E-3  -9.0569201857E-3  -9.6372198313E-3  -9.0569201857E-3  -7.4316998944E-3  -1.7774800071E-3  3.1846798956E-3  3.1757799443E-3  2.1605400834E-3  5.6215998484E-4  -1.2434000382E-4
+-6.7714002216E-4  -5.8146001538E-4  1.4607800404E-3  2.1605400834E-3  3.7613599561E-3  3.0809799209E-3  4.1121998802E-3  2.2212199401E-3  5.5381999118E-4  2.2212199401E-3  4.1121998802E-3  3.0809799209E-3  3.7613599561E-3  2.1605400834E-3  1.4607800404E-3  -5.8146001538E-4  -6.7714002216E-4
+1.2078000145E-4  4.4606000301E-4  -5.8146001538E-4  5.6215998484E-4  -1.3688000035E-4  2.3255399428E-3  2.8898599558E-3  4.2872801423E-3  5.5893999524E-3  4.2872801423E-3  2.8898599558E-3  2.3255399428E-3  -1.3688000035E-4  5.6215998484E-4  -5.8146001538E-4  4.4606000301E-4  1.2078000145E-4
+-4.3500000174E-5  1.2078000145E-4  -6.7714002216E-4  -1.2434000382E-4  -8.0063997302E-4  -1.5970399836E-3  -2.5168000138E-4  -4.2019999819E-4  1.2619999470E-3  -4.2019999819E-4  -2.5168000138E-4  -1.5970399836E-3  -8.0063997302E-4  -1.2434000382E-4  -6.7714002216E-4  1.2078000145E-4  -4.3500000174E-5
+];
+
+bfilts = [...
+-8.1125000725E-4  4.4451598078E-3  1.2316980399E-2  1.3955879956E-2  1.4179450460E-2  1.3955879956E-2  1.2316980399E-2  4.4451598078E-3  -8.1125000725E-4 ...
+3.9103501476E-3  4.4565401040E-3  -5.8724298142E-3  -2.8760801069E-3  8.5267601535E-3  -2.8760801069E-3  -5.8724298142E-3  4.4565401040E-3  3.9103501476E-3 ...
+1.3462699717E-3  -3.7740699481E-3  8.2581602037E-3  3.9442278445E-2  5.3605638444E-2  3.9442278445E-2  8.2581602037E-3  -3.7740699481E-3  1.3462699717E-3 ...
+7.4700999539E-4  -3.6522001028E-4  -2.2522680461E-2  -0.1105690673      -0.1768419296      -0.1105690673      -2.2522680461E-2  -3.6522001028E-4  7.4700999539E-4 ...
+0.0000000000      0.0000000000      0.0000000000      0.0000000000      0.0000000000      0.0000000000      0.0000000000      0.0000000000      0.0000000000     ...
+-7.4700999539E-4  3.6522001028E-4  2.2522680461E-2  0.1105690673      0.1768419296      0.1105690673      2.2522680461E-2  3.6522001028E-4  -7.4700999539E-4 ...
+-1.3462699717E-3  3.7740699481E-3  -8.2581602037E-3  -3.9442278445E-2  -5.3605638444E-2  -3.9442278445E-2  -8.2581602037E-3  3.7740699481E-3  -1.3462699717E-3 ...
+-3.9103501476E-3  -4.4565401040E-3  5.8724298142E-3  2.8760801069E-3  -8.5267601535E-3  2.8760801069E-3  5.8724298142E-3  -4.4565401040E-3  -3.9103501476E-3 ...
+8.1125000725E-4  -4.4451598078E-3  -1.2316980399E-2  -1.3955879956E-2  -1.4179450460E-2  -1.3955879956E-2  -1.2316980399E-2  -4.4451598078E-3  8.1125000725E-4; ...
+...
+0.0000000000      -8.2846998703E-4  -5.7109999034E-5  4.0110000555E-5  4.6670897864E-3  8.0871898681E-3  1.4807609841E-2  8.6204400286E-3  -3.1221499667E-3 ...
+8.2846998703E-4  0.0000000000      -9.7479997203E-4  -6.9718998857E-3  -2.0865600090E-3  2.3298799060E-3  -4.4814897701E-3  1.4917500317E-2  8.6204400286E-3 ...
+5.7109999034E-5  9.7479997203E-4  0.0000000000      -1.2145539746E-2  -2.4427289143E-2  5.0797060132E-2  3.2785870135E-2  -4.4814897701E-3  1.4807609841E-2 ...
+-4.0110000555E-5  6.9718998857E-3  1.2145539746E-2  0.0000000000      -0.1510555595      -8.2495503128E-2  5.0797060132E-2  2.3298799060E-3  8.0871898681E-3 ...
+-4.6670897864E-3  2.0865600090E-3  2.4427289143E-2  0.1510555595      0.0000000000      -0.1510555595      -2.4427289143E-2  -2.0865600090E-3  4.6670897864E-3 ...
+-8.0871898681E-3  -2.3298799060E-3  -5.0797060132E-2  8.2495503128E-2  0.1510555595      0.0000000000      -1.2145539746E-2  -6.9718998857E-3  4.0110000555E-5 ...
+-1.4807609841E-2  4.4814897701E-3  -3.2785870135E-2  -5.0797060132E-2  2.4427289143E-2  1.2145539746E-2  0.0000000000      -9.7479997203E-4  -5.7109999034E-5 ...
+-8.6204400286E-3  -1.4917500317E-2  4.4814897701E-3  -2.3298799060E-3  2.0865600090E-3  6.9718998857E-3  9.7479997203E-4  0.0000000000      -8.2846998703E-4 ...
+3.1221499667E-3  -8.6204400286E-3  -1.4807609841E-2  -8.0871898681E-3  -4.6670897864E-3  -4.0110000555E-5  5.7109999034E-5  8.2846998703E-4  0.0000000000; ...
+...
+8.1125000725E-4  -3.9103501476E-3  -1.3462699717E-3  -7.4700999539E-4  0.0000000000      7.4700999539E-4  1.3462699717E-3  3.9103501476E-3  -8.1125000725E-4 ...
+-4.4451598078E-3  -4.4565401040E-3  3.7740699481E-3  3.6522001028E-4  0.0000000000      -3.6522001028E-4  -3.7740699481E-3  4.4565401040E-3  4.4451598078E-3 ...
+-1.2316980399E-2  5.8724298142E-3  -8.2581602037E-3  2.2522680461E-2  0.0000000000      -2.2522680461E-2  8.2581602037E-3  -5.8724298142E-3  1.2316980399E-2 ...
+-1.3955879956E-2  2.8760801069E-3  -3.9442278445E-2  0.1105690673      0.0000000000      -0.1105690673      3.9442278445E-2  -2.8760801069E-3  1.3955879956E-2 ...
+-1.4179450460E-2  -8.5267601535E-3  -5.3605638444E-2  0.1768419296      0.0000000000      -0.1768419296     5.3605638444E-2  8.5267601535E-3  1.4179450460E-2 ...
+-1.3955879956E-2  2.8760801069E-3  -3.9442278445E-2  0.1105690673      0.0000000000      -0.1105690673      3.9442278445E-2  -2.8760801069E-3  1.3955879956E-2 ...
+-1.2316980399E-2  5.8724298142E-3  -8.2581602037E-3  2.2522680461E-2  0.0000000000      -2.2522680461E-2  8.2581602037E-3  -5.8724298142E-3  1.2316980399E-2 ...
+-4.4451598078E-3  -4.4565401040E-3  3.7740699481E-3  3.6522001028E-4  0.0000000000      -3.6522001028E-4  -3.7740699481E-3  4.4565401040E-3  4.4451598078E-3 ...
+8.1125000725E-4  -3.9103501476E-3  -1.3462699717E-3  -7.4700999539E-4  0.0000000000      7.4700999539E-4  1.3462699717E-3  3.9103501476E-3  -8.1125000725E-4; ...
+...
+3.1221499667E-3  -8.6204400286E-3  -1.4807609841E-2  -8.0871898681E-3  -4.6670897864E-3  -4.0110000555E-5  5.7109999034E-5  8.2846998703E-4  0.0000000000  ...   
+-8.6204400286E-3  -1.4917500317E-2  4.4814897701E-3  -2.3298799060E-3  2.0865600090E-3  6.9718998857E-3  9.7479997203E-4  -0.0000000000      -8.2846998703E-4 ...
+-1.4807609841E-2  4.4814897701E-3  -3.2785870135E-2  -5.0797060132E-2  2.4427289143E-2  1.2145539746E-2  0.0000000000      -9.7479997203E-4  -5.7109999034E-5 ...
+-8.0871898681E-3  -2.3298799060E-3  -5.0797060132E-2  8.2495503128E-2  0.1510555595      -0.0000000000      -1.2145539746E-2  -6.9718998857E-3  4.0110000555E-5 ...
+-4.6670897864E-3  2.0865600090E-3  2.4427289143E-2  0.1510555595      0.0000000000      -0.1510555595      -2.4427289143E-2  -2.0865600090E-3  4.6670897864E-3 ...
+-4.0110000555E-5  6.9718998857E-3  1.2145539746E-2  0.0000000000      -0.1510555595      -8.2495503128E-2  5.0797060132E-2  2.3298799060E-3  8.0871898681E-3 ...
+5.7109999034E-5  9.7479997203E-4  -0.0000000000      -1.2145539746E-2  -2.4427289143E-2  5.0797060132E-2  3.2785870135E-2  -4.4814897701E-3  1.4807609841E-2 ...
+8.2846998703E-4  -0.0000000000      -9.7479997203E-4  -6.9718998857E-3  -2.0865600090E-3  2.3298799060E-3  -4.4814897701E-3  1.4917500317E-2  8.6204400286E-3 ...
+0.0000000000      -8.2846998703E-4  -5.7109999034E-5  4.0110000555E-5  4.6670897864E-3  8.0871898681E-3  1.4807609841E-2  8.6204400286E-3  -3.1221499667E-3 ...
+]'; 
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp5Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp5Filters.m
new file mode 100755
index 0000000..4cddcfd
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/sp5Filters.m
@@ -0,0 +1,110 @@
+% Steerable pyramid filters.  Transform described  in:
+%
+% @INPROCEEDINGS{Simoncelli95b,
+%       TITLE = "The Steerable Pyramid: A Flexible Architecture for
+%                Multi-Scale Derivative Computation",
+%       AUTHOR = "E P Simoncelli and W T Freeman",
+%       BOOKTITLE = "Second Int'l Conf on Image Processing",
+%       ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 }
+%
+% Filter kernel design described in:
+%
+%@INPROCEEDINGS{Karasaridis96,
+%       TITLE = "A Filter Design Technique for 
+%               Steerable Pyramid Image Transforms",
+%       AUTHOR = "A Karasaridis and E P Simoncelli",
+%       BOOKTITLE = "ICASSP",   ADDRESS = "Atlanta, GA",
+%       MONTH = "May",  YEAR = 1996 }
+
+% Eero Simoncelli, 6/96.
+
+function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp5Filters();
+
+harmonics = [1 3 5];
+
+mtx = [ ...
+    0.3333    0.2887    0.1667    0.0000   -0.1667   -0.2887
+    0.0000    0.1667    0.2887    0.3333    0.2887    0.1667
+    0.3333   -0.0000   -0.3333   -0.0000    0.3333   -0.0000
+    0.0000    0.3333    0.0000   -0.3333    0.0000    0.3333
+    0.3333   -0.2887    0.1667   -0.0000   -0.1667    0.2887
+   -0.0000    0.1667   -0.2887    0.3333   -0.2887    0.1667];
+
+hi0filt = [ 
+-0.00033429 -0.00113093 -0.00171484 -0.00133542 -0.00080639 -0.00133542 -0.00171484 -0.00113093 -0.00033429
+-0.00113093 -0.00350017 -0.00243812 0.00631653 0.01261227 0.00631653 -0.00243812 -0.00350017 -0.00113093
+-0.00171484 -0.00243812 -0.00290081 -0.00673482 -0.00981051 -0.00673482 -0.00290081 -0.00243812 -0.00171484
+-0.00133542 0.00631653 -0.00673482 -0.07027679 -0.11435863 -0.07027679 -0.00673482 0.00631653 -0.00133542
+-0.00080639 0.01261227 -0.00981051 -0.11435863 0.81380200 -0.11435863 -0.00981051 0.01261227 -0.00080639
+-0.00133542 0.00631653 -0.00673482 -0.07027679 -0.11435863 -0.07027679 -0.00673482 0.00631653 -0.00133542
+-0.00171484 -0.00243812 -0.00290081 -0.00673482 -0.00981051 -0.00673482 -0.00290081 -0.00243812 -0.00171484
+-0.00113093 -0.00350017 -0.00243812 0.00631653 0.01261227 0.00631653 -0.00243812 -0.00350017 -0.00113093
+-0.00033429 -0.00113093 -0.00171484 -0.00133542 -0.00080639 -0.00133542 -0.00171484 -0.00113093 -0.00033429];
+
+
+lo0filt = [
+0.00341614 -0.01551246 -0.03848215 -0.01551246 0.00341614
+-0.01551246 0.05586982 0.15925570 0.05586982 -0.01551246
+-0.03848215 0.15925570 0.40304148 0.15925570 -0.03848215
+-0.01551246 0.05586982 0.15925570 0.05586982 -0.01551246
+0.00341614 -0.01551246 -0.03848215 -0.01551246 0.00341614];
+
+lofilt = 2*[
+0.00085404 -0.00244917 -0.00387812 -0.00944432 -0.00962054 -0.00944432 -0.00387812 -0.00244917 0.00085404
+-0.00244917 -0.00523281 -0.00661117 0.00410600 0.01002988 0.00410600 -0.00661117 -0.00523281 -0.00244917
+-0.00387812 -0.00661117 0.01396746 0.03277038 0.03981393 0.03277038 0.01396746 -0.00661117 -0.00387812
+-0.00944432 0.00410600 0.03277038 0.06426333 0.08169618 0.06426333 0.03277038 0.00410600 -0.00944432
+-0.00962054 0.01002988 0.03981393 0.08169618 0.10096540 0.08169618 0.03981393 0.01002988 -0.00962054
+-0.00944432 0.00410600 0.03277038 0.06426333 0.08169618 0.06426333 0.03277038 0.00410600 -0.00944432
+-0.00387812 -0.00661117 0.01396746 0.03277038 0.03981393 0.03277038 0.01396746 -0.00661117 -0.00387812
+-0.00244917 -0.00523281 -0.00661117 0.00410600 0.01002988 0.00410600 -0.00661117 -0.00523281 -0.00244917
+0.00085404 -0.00244917 -0.00387812 -0.00944432 -0.00962054 -0.00944432 -0.00387812 -0.00244917 0.00085404];
+
+bfilts = [...
+ 0.00277643 0.00496194 0.01026699 0.01455399 0.01026699 0.00496194 0.00277643 ...
+-0.00986904 -0.00893064 0.01189859 0.02755155 0.01189859 -0.00893064 -0.00986904 ...
+-0.01021852 -0.03075356 -0.08226445 -0.11732297 -0.08226445 -0.03075356 -0.01021852 ...
+ 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 ...
+ 0.01021852 0.03075356 0.08226445 0.11732297 0.08226445 0.03075356 0.01021852 ...
+ 0.00986904 0.00893064 -0.01189859 -0.02755155 -0.01189859 0.00893064 0.00986904 ...
+-0.00277643 -0.00496194 -0.01026699 -0.01455399 -0.01026699 -0.00496194 -0.00277643;
+...
+-0.00343249 -0.00640815 -0.00073141 0.01124321 0.00182078 0.00285723 0.01166982 ...
+-0.00358461 -0.01977507 -0.04084211 -0.00228219 0.03930573 0.01161195 0.00128000 ...
+ 0.01047717 0.01486305 -0.04819057 -0.12227230 -0.05394139 0.00853965 -0.00459034 ...
+ 0.00790407 0.04435647 0.09454202 -0.00000000 -0.09454202 -0.04435647 -0.00790407 ...
+ 0.00459034 -0.00853965 0.05394139 0.12227230 0.04819057 -0.01486305 -0.01047717 ...
+-0.00128000 -0.01161195 -0.03930573 0.00228219 0.04084211 0.01977507 0.00358461 ...
+-0.01166982 -0.00285723 -0.00182078 -0.01124321 0.00073141 0.00640815 0.00343249;
+...
+ 0.00343249 0.00358461 -0.01047717 -0.00790407 -0.00459034 0.00128000 0.01166982 ...
+ 0.00640815 0.01977507 -0.01486305 -0.04435647 0.00853965 0.01161195 0.00285723 ...
+ 0.00073141 0.04084211 0.04819057 -0.09454202 -0.05394139 0.03930573 0.00182078 ...
+-0.01124321 0.00228219 0.12227230 -0.00000000 -0.12227230 -0.00228219 0.01124321 ...
+-0.00182078 -0.03930573 0.05394139 0.09454202 -0.04819057 -0.04084211 -0.00073141 ...
+-0.00285723 -0.01161195 -0.00853965 0.04435647 0.01486305 -0.01977507 -0.00640815 ...
+-0.01166982 -0.00128000 0.00459034 0.00790407 0.01047717 -0.00358461 -0.00343249;
+...
+-0.00277643 0.00986904 0.01021852 -0.00000000 -0.01021852 -0.00986904 0.00277643 ...
+-0.00496194 0.00893064 0.03075356 -0.00000000 -0.03075356 -0.00893064 0.00496194 ...
+-0.01026699 -0.01189859 0.08226445 -0.00000000 -0.08226445 0.01189859 0.01026699 ...
+-0.01455399 -0.02755155 0.11732297 -0.00000000 -0.11732297 0.02755155 0.01455399 ...
+-0.01026699 -0.01189859 0.08226445 -0.00000000 -0.08226445 0.01189859 0.01026699 ...
+-0.00496194 0.00893064 0.03075356 -0.00000000 -0.03075356 -0.00893064 0.00496194 ...
+-0.00277643 0.00986904 0.01021852 -0.00000000 -0.01021852 -0.00986904 0.00277643;
+...
+-0.01166982 -0.00128000 0.00459034 0.00790407 0.01047717 -0.00358461 -0.00343249 ...
+-0.00285723 -0.01161195 -0.00853965 0.04435647 0.01486305 -0.01977507 -0.00640815 ...
+-0.00182078 -0.03930573 0.05394139 0.09454202 -0.04819057 -0.04084211 -0.00073141 ...
+-0.01124321 0.00228219 0.12227230 -0.00000000 -0.12227230 -0.00228219 0.01124321 ...
+ 0.00073141 0.04084211 0.04819057 -0.09454202 -0.05394139 0.03930573 0.00182078 ...
+ 0.00640815 0.01977507 -0.01486305 -0.04435647 0.00853965 0.01161195 0.00285723 ...
+ 0.00343249 0.00358461 -0.01047717 -0.00790407 -0.00459034 0.00128000 0.01166982;
+...
+-0.01166982 -0.00285723 -0.00182078 -0.01124321 0.00073141 0.00640815 0.00343249 ...
+-0.00128000 -0.01161195 -0.03930573 0.00228219 0.04084211 0.01977507 0.00358461 ...
+ 0.00459034 -0.00853965 0.05394139 0.12227230 0.04819057 -0.01486305 -0.01047717 ...
+ 0.00790407 0.04435647 0.09454202 -0.00000000 -0.09454202 -0.04435647 -0.00790407 ...
+ 0.01047717 0.01486305 -0.04819057 -0.12227230 -0.05394139 0.00853965 -0.00459034 ...
+-0.00358461 -0.01977507 -0.04084211 -0.00228219 0.03930573 0.01161195 0.00128000 ...
+-0.00343249 -0.00640815 -0.00073141 0.01124321 0.00182078 0.00285723 0.01166982]'; 
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrBand.m
new file mode 100755
index 0000000..474a8dc
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrBand.m
@@ -0,0 +1,34 @@
+% [LEV,IND] = spyrBand(PYR,INDICES,LEVEL,BAND)
+%
+% Access a band from a steerable pyramid.
+% 
+%   LEVEL indicates the scale (finest = 1, coarsest = spyrHt(INDICES)).
+% 
+%   BAND (optional, default=1) indicates which subband 
+%     (1 = vertical, rest proceeding anti-clockwise).
+
+% Eero Simoncelli, 6/96.
+
+function res =  spyrBand(pyr,pind,level,band)
+
+if (exist('level') ~= 1)
+  level = 1;
+end
+
+if (exist('band') ~= 1)
+  band = 1;
+end
+
+nbands = spyrNumBands(pind);
+if ((band > nbands) | (band < 1))
+  error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands));
+end     
+
+maxLev = spyrHt(pind);
+if ((level > maxLev) | (level < 1))
+  error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev));
+end
+
+firstband = 1 + band + nbands*(level-1);
+res  = pyrBand(pyr, pind, firstband);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHigh.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHigh.m
new file mode 100755
index 0000000..f91b466
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHigh.m
@@ -0,0 +1,10 @@
+% RES = spyrHigh(PYR, INDICES)
+%
+% Access the highpass residual band from a steerable pyramid.
+
+% Eero Simoncelli, 6/96.
+
+function res =  spyrHigh(pyr,pind)
+
+res  = pyrBand(pyr, pind, 1);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHt.m
new file mode 100755
index 0000000..8706b9e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrHt.m
@@ -0,0 +1,16 @@
+% [HEIGHT] = spyrHt(INDICES)
+%
+% Compute height of steerable pyramid with given index matrix.
+
+% Eero Simoncelli, 6/96.
+
+function [ht] =  spyrHt(pind)
+
+nbands = spyrNumBands(pind);
+
+% Don't count lowpass, or highpass residual bands
+if (size(pind,1) > 2)
+  ht = (size(pind,1)-2)/nbands;
+else
+  ht = 0;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrLev.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrLev.m
new file mode 100755
index 0000000..5cb4a85
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrLev.m
@@ -0,0 +1,24 @@
+% [LEV,IND] = spyrLev(PYR,INDICES,LEVEL)
+%
+% Access a level from a steerable pyramid.
+% Return as an SxB matrix, B = number of bands, S = total size of a band.
+% Also returns an Bx2 matrix containing dimensions of the subbands.
+
+% Eero Simoncelli, 6/96.
+
+function [lev,ind] =  spyrLev(pyr,pind,level)
+
+nbands = spyrNumBands(pind);
+                
+if ((level > spyrHt(pind)) | (level < 1))
+  error(sprintf('Level number must be in the range [1, %d].', spyrHt(pind)));
+end     
+        
+firstband = 2 + nbands*(level-1);
+firstind = 1;
+for l=1:firstband-1
+  firstind = firstind + prod(pind(l,:));
+end
+
+ind = pind(firstband:firstband+nbands-1,:);
+lev  = pyr(firstind:firstind+sum(prod(ind'))-1);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrNumBands.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrNumBands.m
new file mode 100755
index 0000000..68aec3f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/spyrNumBands.m
@@ -0,0 +1,20 @@
+% [NBANDS] = spyrNumBands(INDICES)
+%
+% Compute number of orientation bands in a steerable pyramid with
+% given index matrix.  If the pyramid contains only the highpass and
+% lowpass bands (i.e., zero levels), returns 0.
+
+% Eero Simoncelli, 2/97.
+
+function [nbands] =  spyrNumBands(pind)
+
+if (size(pind,1) == 2)
+  nbands  = 0;
+else
+  % Count number of orientation bands:
+  b = 3;
+  while ((b <= size(pind,1)) & all( pind(b,:) == pind(2,:)) )
+    b = b+1;
+  end
+  nbands = b-2;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer.m
new file mode 100755
index 0000000..8f9c2ac
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer.m
@@ -0,0 +1,68 @@
+% RES = STEER(BASIS, ANGLE, HARMONICS, STEERMTX)
+%
+% Steer BASIS to the specfied ANGLE.  
+% 
+% BASIS should be a matrix whose columns are vectorized rotated copies of a 
+% steerable function, or the responses of a set of steerable filters.
+% 
+% ANGLE can be a scalar, or a column vector the size of the basis.
+% 
+% HARMONICS (optional, default is N even or odd low frequencies, as for 
+% derivative filters) should be a list of harmonic numbers indicating
+% the angular harmonic content of the basis.
+% 
+% STEERMTX (optional, default assumes cosine phase harmonic components,
+% and filter positions at 2pi*n/N) should be a matrix which maps
+% the filters onto Fourier series components (ordered [cos0 cos1 sin1 
+% cos2 sin2 ... sinN]).  See steer2HarmMtx.m
+
+% Eero Simoncelli, 7/96.
+
+function res = steer(basis,angle,harmonics,steermtx)
+
+num = size(basis,2);
+
+if ( any(size(angle) ~= [size(basis,1) 1]) & any(size(angle) ~= [1 1]) )
+  error('ANGLE must be a scalar, or a column vector the size of the basis elements');
+end
+
+%% If HARMONICS are not passed, assume derivatives.
+if (exist('harmonics') ~= 1)
+  if (mod(num,2) == 0)
+    harmonics = [0:(num/2)-1]'*2 + 1;
+  else
+    harmonics = [0:(num-1)/2]'*2;
+  end
+else
+  harmonics = harmonics(:);
+  if ((2*size(harmonics,1)-any(harmonics == 0)) ~= num)
+    error('harmonics list is incompatible with basis size');
+  end
+end
+
+%% If STEERMTX not passed, assume evenly distributed cosine-phase filters:
+if (exist('steermtx') ~= 1)
+  steermtx = steer2HarmMtx(harmonics, pi*[0:num-1]/num, 'even');
+end
+
+steervect = zeros(size(angle,1),num);
+arg = angle * harmonics(find(harmonics~=0))';
+if (all(harmonics))
+        steervect(:, 1:2:num) = cos(arg);
+        steervect(:, 2:2:num) = sin(arg);
+else
+        steervect(:, 1) = ones(size(arg,1),1);
+        steervect(:, 2:2:num) = cos(arg);
+        steervect(:, 3:2:num) = sin(arg);
+end
+
+steervect = steervect * steermtx;
+
+if (size(steervect,1) > 1)
+        tmp = basis' .* steervect';
+        res = sum(tmp)';
+else
+        res = basis * steervect';
+end
+        
+        
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer2HarmMtx.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer2HarmMtx.m
new file mode 100755
index 0000000..1f3e80e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/steer2HarmMtx.m
@@ -0,0 +1,71 @@
+% MTX = steer2HarmMtx(HARMONICS, ANGLES, REL_PHASES)
+%
+% Compute a steering matrix (maps a directional basis set onto the
+% angular Fourier harmonics).  HARMONICS is a vector specifying the
+% angular harmonics contained in the steerable basis/filters.  ANGLES 
+% (optional) is a vector specifying the angular position of each filter.  
+% REL_PHASES (optional, default = 'even') specifies whether the harmonics 
+% are cosine or sine phase aligned about those positions.
+% The result matrix is suitable for passing to the function STEER.
+
+% Eero Simoncelli, 7/96.
+
+function mtx = steer2HarmMtx(harmonics, angles, evenorodd)
+
+%%=================================================================
+%%% Optional Parameters:
+
+if (exist('evenorodd') ~= 1)
+  evenorodd = 'even';
+end
+
+% Make HARMONICS a row vector
+harmonics = harmonics(:)';
+
+numh = 2*size(harmonics,2) - any(harmonics == 0);
+
+if (exist('angles') ~= 1)
+  angles = pi * [0:numh-1]'/numh;
+else
+  angles = angles(:);
+end
+
+%%=================================================================
+
+if isstr(evenorodd)
+  if strcmp(evenorodd,'even')
+    evenorodd = 0;
+  elseif strcmp(evenorodd,'odd')
+    evenorodd = 1;
+  else
+    error('EVEN_OR_ODD should be the string  EVEN or ODD');
+  end
+end
+
+%% Compute inverse matrix, which maps Fourier components onto 
+%% steerable basis.
+imtx = zeros(size(angles,1),numh);
+col = 1;
+for h=harmonics
+  args = h*angles;
+  if (h == 0)
+    imtx(:,col) = ones(size(angles));
+    col = col+1;
+  elseif evenorodd
+    imtx(:,col) = sin(args);
+    imtx(:,col+1) = -cos(args);
+    col = col+2;
+  else
+    imtx(:,col) = cos(args);
+    imtx(:,col+1) = sin(args);
+    col = col+2;
+  end
+end
+  
+r = rank(imtx);
+if (( r ~= numh ) & ( r ~= size(angles,1) ))
+  fprintf(2,'WARNING: matrix is not full rank');
+end  
+
+mtx = pinv(imtx);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/subMtx.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/subMtx.m
new file mode 100755
index 0000000..ea3c2ea
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/subMtx.m
@@ -0,0 +1,21 @@
+% MTX = subMtx(VEC, DIMENSIONS, START_INDEX)
+%
+% Reshape a portion of VEC starting from START_INDEX (optional,
+% default=1) to the given dimensions.
+
+% Eero Simoncelli, 6/96.
+
+function mtx = subMtx(vec, sz, offset)
+
+if (exist('offset') ~= 1)
+   offset = 1;
+end
+
+vec = vec(:);
+sz = sz(:);
+
+if (size(sz,1) ~= 2)
+  error('DIMENSIONS must be a 2-vector.');
+end
+
+mtx = reshape( vec(offset:offset+prod(sz)-1), sz(1), sz(2) );
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureAnalysis.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureAnalysis.m
new file mode 100755
index 0000000..d7a0ec1
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureAnalysis.m
@@ -0,0 +1,245 @@
+function [params] = textureAnalysis(im0, Nsc, Nor, Na)
+
+% Analyze texture for application of Portilla-Simoncelli model/algorithm.
+%
+% [params] = textureAnalysis(im0, Nsc, Nor, Na);
+%       im0:    original image
+%       Nsc:    number of scales
+%       Nor:    number of orientations
+%       Na:     spatial neighborhood considered (Na x Na)       
+%
+% Example: Nsc=4; Nor=4; Na=7;
+%
+% See also textureSynthesis.
+
+% Javier Portilla and Eero Simoncelli.
+% Work described in:
+%  "A Parametric Texture Model based on Joint Statistics of Complex Wavelet Coefficients".
+%  J Portilla and E P Simoncelli. Int'l Journal of Computer Vision,
+%  vol.40(1), pp. 49-71, Dec 2000.   
+%
+% Please refer to this publication if you use the program for research or
+% for technical applications. Thank you.
+%
+% Copyright, Center for Neural Science, New York University, January 2001.
+% All rights reserved.
+
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+Warn = 0;  % Set to 1 if you want to see warning messages
+
+%% Check required args are passed
+if (nargin < 4)
+  error('Function called with too few input arguments');
+end
+
+%% 1D interpolation filter, for scale cross-correlations:
+interp = [-1/16 0 9/16 1 9/16 0 -1/16]/sqrt(2);
+
+if ( mod(Na,2) == 0 )
+  error('Na is not an odd integer');
+end
+
+%% If the spatial neighborhood Na is too big for the lower scales,
+%% "modacor22.m" will make it as big as the spatial support at
+%% each scale:
+
+[Ny,Nx] = size(im0);
+nth = log2(min(Ny,Nx)/Na);
+if nth<Nsc & Warn,
+  fprintf(1,'Warning: Na will be cut off for levels above #%d !\n', floor(nth+1));
+end
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+la = floor((Na-1)/2);
+
+%% Pixel statistics
+[mn0 mx0] = size(im0);
+mean0 = mean2(im0);
+var0 = var2(im0, mean0);
+skew0 = skew2(im0, mean0, var0);
+kurt0 = kurt2(im0, mean0, var0);
+statg0 = [mean0 var0 skew0 kurt0 mn0 mx0];
+
+% Add a little bit of noise to the original, in case it has been 
+% artificially generated, to avoid instability crated by symmetric
+% conditions at the synthesis stage.
+
+%im0 = im0 + (mx0-mn0)/1000*randn(size(im0));        %kvs
+
+%% Build the steerable pyramid
+[pyr0,pind0] = buildSCFpyr(im0,Nsc,Nor-1);
+
+if ( any(vector(mod(pind0,2))) )
+  error('Algorithm will fail: Some bands have odd dimensions!');
+end
+
+%% Subtract mean of lowBand:
+nband = size(pind0,1);
+pyr0(pyrBandIndices(pind0,nband)) = ...
+    real(pyrBand(pyr0,pind0,nband)) - mean2(real(pyrBand(pyr0,pind0,nband)));
+
+rpyr0 = real(pyr0);
+apyr0 = abs(pyr0);
+
+figure(gcf)
+clf
+showIm(im0,'auto',1); title('Original');  drawnow
+
+%% Subtract mean of magnitude:
+magMeans0 = zeros(size(pind0,1), 1);
+for nband = 1:size(pind0,1)
+  indices = pyrBandIndices(pind0,nband);
+  magMeans0(nband) = mean2(apyr0(indices));
+  apyr0(indices) = apyr0(indices) - magMeans0(nband);
+end
+
+%% Compute central autoCorr of lowband
+acr = NaN * ones(Na,Na,Nsc+1);
+nband = size(pind0,1);
+ch = pyrBand(pyr0,pind0,nband);
+[mpyr,mpind] = buildSFpyr(real(ch),0,0);
+im = pyrBand(mpyr,mpind,2);
+[Nly Nlx] = size(ch);
+Sch = min(Nly,Nlx); %size of low band
+le = min(Sch/2-1,la);
+cy = Nly/2+1;
+cx = Nlx/2+1;
+ac = fftshift(real(ifft2(abs(fft2(im)).^2)))/prod(size(ch));
+ac = ac(cy-le:cy+le,cx-le:cx+le);
+acr(la-le+1:la+le+1,la-le+1:la+le+1,Nsc+1) = ac;
+skew0p = zeros(Nsc+1,1);
+kurt0p = zeros(Nsc+1,1);
+vari = ac(le+1,le+1);
+if vari/var0 > 1e-6,
+        skew0p(Nsc+1) = mean2(im.^3)/vari^1.5;
+        kurt0p(Nsc+1) = mean2(im.^4)/vari^2;
+else
+        skew0p(Nsc+1) = 0;
+        kurt0p(Nsc+1) = 3;
+end
+
+%% Compute  central autoCorr of each Mag band, and the autoCorr of the
+%% combined (non-oriented) band.
+ace = NaN * ones(Na,Na,Nsc,Nor);
+for nsc = Nsc:-1:1,
+  for nor = 1:Nor,
+    nband = (nsc-1)*Nor+nor+1;
+    ch = pyrBand(apyr0,pind0,nband);
+    [Nly, Nlx] = size(ch);
+    Sch = min(Nlx, Nly);
+    le = min(Sch/2-1,la);
+    cx = Nlx/2+1;  %Assumes Nlx even
+    cy = Nly/2+1;
+    ac = fftshift(real(ifft2(abs(fft2(ch)).^2)))/prod(size(ch));
+    ac = ac(cy-le:cy+le,cx-le:cx+le);
+    ace(la-le+1:la+le+1,la-le+1:la+le+1,nsc,nor) = ac;
+  end
+
+  %% Combine ori bands
+
+  bandNums = [1:Nor] + (nsc-1)*Nor+1;  %ori bands only
+  ind1 = pyrBandIndices(pind0, bandNums(1));
+  indN = pyrBandIndices(pind0, bandNums(Nor));
+  bandInds = [ind1(1):indN(length(indN))];
+  %% Make fake pyramid, containing dummy hi, ori, lo
+  fakePind = [pind0(bandNums(1),:);pind0(bandNums(1):bandNums(Nor)+1,:)];
+  fakePyr = [zeros(prod(fakePind(1,:)),1);...
+         rpyr0(bandInds); zeros(prod(fakePind(size(fakePind,1),:)),1);];
+  ch = reconSFpyr(fakePyr, fakePind, [1]);     % recon ori bands only
+  im = real(expand(im,2))/4;
+  im = im + ch;  
+  ac = fftshift(real(ifft2(abs(fft2(im)).^2)))/prod(size(ch));
+  ac = ac(cy-le:cy+le,cx-le:cx+le);
+  acr(la-le+1:la+le+1,la-le+1:la+le+1,nsc) = ac;
+  vari = ac(le+1,le+1);
+  if vari/var0 > 1e-6,
+        skew0p(nsc) = mean2(im.^3)/vari^1.5;
+        kurt0p(nsc) = mean2(im.^4)/vari^2;
+  else
+        skew0p(nsc) = 0;
+        kurt0p(nsc) = 3;
+  end
+end
+
+%% Compute the cross-correlation matrices of the coefficient magnitudes
+%% pyramid at the different levels and orientations
+
+C0 = zeros(Nor,Nor,Nsc+1);
+Cx0 = zeros(Nor,Nor,Nsc);
+
+Cr0 = zeros(2*Nor,2*Nor,Nsc+1);
+Crx0 = zeros(2*Nor,2*Nor,Nsc);
+
+for nsc = 1:Nsc,
+  firstBnum = (nsc-1)*Nor+2;
+  cousinSz = prod(pind0(firstBnum,:));
+  ind = pyrBandIndices(pind0,firstBnum);
+  cousinInd = ind(1) + [0:Nor*cousinSz-1];
+
+  if (nsc<Nsc)
+    parents = zeros(cousinSz,Nor);
+    rparents = zeros(cousinSz,Nor*2);
+    for nor=1:Nor,
+      nband = (nsc-1+1)*Nor+nor+1;
+
+      tmp = expand(pyrBand(pyr0, pind0, nband),2)/4;
+      rtmp = real(tmp); itmp = imag(tmp);
+      %% Double phase:
+      tmp = sqrt(rtmp.^2 + itmp.^2) .* exp(2 * sqrt(-1) * atan2(rtmp,itmp));
+      rparents(:,nor) = vector(real(tmp));
+      rparents(:,Nor+nor) = vector(imag(tmp));
+
+      tmp = abs(tmp);
+      parents(:,nor) = vector(tmp - mean2(tmp));
+    end
+  else
+    tmp = real(expand(pyrLow(rpyr0,pind0),2))/4;
+    rparents = [vector(tmp),...
+                vector(shift(tmp,[0 1])), vector(shift(tmp,[0 -1])), ...
+                vector(shift(tmp,[1 0])), vector(shift(tmp,[-1 0]))];
+    parents = [];
+  end
+
+  cousins = reshape(apyr0(cousinInd), [cousinSz Nor]);
+  nc = size(cousins,2);   np = size(parents,2);
+  C0(1:nc,1:nc,nsc) = innerProd(cousins)/cousinSz;
+  if (np > 0)
+    Cx0(1:nc,1:np,nsc) = (cousins'*parents)/cousinSz;
+    if (nsc==Nsc)
+      C0(1:np,1:np,Nsc+1) = innerProd(parents)/(cousinSz/4);
+    end
+  end
+  
+  cousins = reshape(real(pyr0(cousinInd)), [cousinSz Nor]);
+  nrc = size(cousins,2);   nrp = size(rparents,2);  
+  Cr0(1:nrc,1:nrc,nsc) = innerProd(cousins)/cousinSz;
+  if (nrp > 0)
+    Crx0(1:nrc,1:nrp,nsc) = (cousins'*rparents)/cousinSz;
+    if (nsc==Nsc)
+      Cr0(1:nrp,1:nrp,Nsc+1) = innerProd(rparents)/(cousinSz/4);
+    end
+  end
+end
+
+%% Calculate the mean, range and variance of the LF and HF residuals' energy.
+
+channel = pyr0(pyrBandIndices(pind0,1));
+vHPR0 = mean2(channel.^2);
+
+statsLPim = [skew0p kurt0p];
+
+params = struct('pixelStats', statg0, ...
+                'pixelLPStats', statsLPim, ...
+                'autoCorrReal', acr, ...
+                'autoCorrMag', ace, ...
+                'magMeans', magMeans0, ...
+                'cousinMagCorr', C0, ...
+                'parentMagCorr', Cx0, ...
+                'cousinRealCorr', Cr0, ...
+                'parentRealCorr', Crx0, ...
+                'varianceHPR', vHPR0);
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureSynthesis.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureSynthesis.m
new file mode 100755
index 0000000..38fce5a
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureSynthesis.m
@@ -0,0 +1,436 @@
+function [im,snrP,imS] = textureSynthesis(params, im0, Niter, cmask, imask)
+
+% [res,snrP,imS] = textureSynthesis(params, initialIm, Niter, cmask, imask)
+%
+% Synthesize texture applying Portilla-Simoncelli model/algorithm.
+%       
+% params: structure containing texture parameters (as returned by textureAnalysis).
+%
+% im0: initial image, OR a vector (Ydim, Xdim, [SEED]) containing
+% dimensions of desired image and an optional seed for the random
+% number generator.  If dimensions are passed, initial image is
+% Gaussian white noise.
+%
+% Niter (optional): Number of iterations.  Default = 50.
+%
+% cmask (optional): binary column vector (4x1) indicating which sets of
+% constraints we want to apply in the synthesis. The four sets are:
+%               1) Marginal statistics (mean, var, skew, kurt, range)
+%               2) Correlation of subbands (space, orientation, scale)
+%               3) Correlation of magnitude responses (sp, or, sc)
+%               4) Relative local phase
+%
+% imask (optional): imsizex2 matrix.  First column is a mask, second
+%       column contains the image values to be imposed. If only one column is
+%       provided, it assumes it corresponds to the image values, and it uses
+%       a raised cosine square for the mask.
+% snrP (optional):      Set of adjustment values (in dB) of the parameters.
+% imS (optional):       Sequence of synthetic images, from niter = 1 to 2^n, being
+%                       n = floor(log2(Niter)).
+
+% Javier Portilla and Eero Simoncelli.
+% Work described in:
+%  "A Parametric Texture Model based on Joint Statistics of Complex Wavelet Coefficients".
+%  J Portilla and E P Simoncelli. Int'l Journal of Computer Vision,
+%  vol.40(1), pp. 49-71, Dec 2000.   
+%
+% Please refer to this publication if you use the program for research or
+% for technical applications. Thank you.
+%
+% Copyright, Center for Neural Science, New York University, January 2001.
+% All rights reserved.
+
+Warn = 0;  % Set to 1 if you want to see warning messages
+
+%% Check required args are passed:
+if (nargin < 2)
+  error('Function called with too few input arguments');
+end
+
+if ( ~exist('Niter') | isempty(Niter) )
+  Niter = 50;
+end
+
+if (exist('cmask') & ~isempty(cmask) )
+  cmask = (cmask > 0.5);  % indices of ones in mask
+else
+  cmask = ones(4,1);
+end
+
+%% Extract parameters  
+statg0 = params.pixelStats;
+mean0 = statg0(1); var0 =  statg0(2);
+skew0 =  statg0(3); kurt0 =  statg0(4);
+mn0 =  statg0(5);  mx0 = statg0(6);
+statsLPim = params.pixelLPStats;
+skew0p = statsLPim(:,1);
+kurt0p = statsLPim(:,2);
+vHPR0 = params.varianceHPR;
+acr0 = params.autoCorrReal;
+ace0 = params.autoCorrMag;
+magMeans0 = params.magMeans;
+C0 = params.cousinMagCorr;
+Cx0 = params.parentMagCorr;
+Crx0 = params.parentRealCorr;
+
+%% Extract {Nsc, Nor, Na} from params
+tmp = size(params.autoCorrMag);
+Na = tmp(1); Nsc = tmp(3);
+Nor = tmp(length(tmp))*(length(tmp)==4) + (length(tmp)<4);
+la = (Na-1)/2;
+
+%% If im0 is a vector of length 2, create Gaussian white noise image of this
+%% size, with desired pixel mean and variance.  If vector length is
+%% 3,  use the 3rd element to seed the random number generator.
+if ( length(im0) <= 3 )
+  if ( length(im0) == 3)
+    randn('state', im0(3)); % Reset Seed
+    im0 = im0(1:2);
+  end
+  im = mean0 + sqrt(var0)*randn(im0);
+else
+  im = im0;
+end
+
+%% If the spatial neighborhood Na is too big for the lower scales,
+%% "modacor22.m" will make it as big as the spatial support at
+%% each scale:
+[Ny,Nx] = size(im);
+nth = log2(min(Ny,Nx)/Na);
+if nth<Nsc+1 & Warn,
+  fprintf(1,'Warning: Na will be cut off for levels above #%d !\n',floor(nth));
+end
+
+if  exist('imask') & ~isempty(imask),
+        if  size(imask,1) ~= prod(size(im))
+                error(sprintf('imask size %d does not match image dimensions [%d,%d]',...
+                size(imask,1), size(im,1), size(im,2)));
+        end
+        if size(imask,2) == 1,
+                mask = (cos(-pi/2:2*pi/Ny:pi*(1-2/Ny)/2)).'*cos(-pi/2:2*pi/Nx:pi*(1-2/Nx)/2);
+                mask = mask.^2;
+                aux = zeros(size(im));
+                aux(Ny/4+1:Ny/4+Ny/2,Nx/4+1:Nx/4+Nx/2)=mask;
+                mask = aux;
+        else
+                mask = reshape(imask(:,1),size(im));
+        end
+end
+
+imf = max(1,gcf-1); snrf = imf+1;
+figure(imf);  clf
+subplot(1,2,1); grayRange = showIm(im,'auto',1); title('Starting image');
+drawnow
+
+prev_im=im;
+
+imf = max(1,gcf-1);
+figure(imf);   
+clf;showIm(im,'auto',1); title(sprintf('iteration 0'));
+
+nq = 0;
+Nq = floor(log2(Niter));
+imS = zeros(Ny,Nx,Nq);
+
+%% MAIN LOOP
+for niter = 1:Niter
+
+%p = niter/Niter; 
+p = 1;
+
+  %% Build the steerable pyramid
+  [pyr,pind] = buildSCFpyr(im,Nsc,Nor-1);
+
+  if ( any(vector(mod(pind,4))) )
+    error('Algorithm will fail: band dimensions are not all multiples of 4!');
+  end
+
+  %% Subtract mean of lowBand:
+  nband = size(pind,1);
+  pyr(pyrBandIndices(pind,nband)) = ...
+      pyrBand(pyr,pind,nband) - mean2(pyrBand(pyr,pind,nband));
+
+  apyr = abs(pyr);
+
+  %% Adjust autoCorr of lowBand
+  nband = size(pind,1); 
+  ch = pyrBand(pyr,pind,nband);
+  Sch = min(size(ch)/2);
+  nz = sum(sum(~isnan(acr0(:,:,Nsc+1))));
+  lz = (sqrt(nz)-1)/2;
+  le = min(Sch/2-1,lz);
+  im = real(ch);  %Reconstructed image: initialize to lowband
+  [mpyr,mpind] = buildSFpyr(im,0,0);
+  im = pyrBand(mpyr,mpind,2);
+  vari =  acr0(la+1:la+1,la+1:la+1,Nsc+1);
+if cmask(2),
+  if vari/var0 > 1e-4,
+        [im, snr2(niter,Nsc+1)] = ...
+        modacor22(im, acr0(la-le+1:la+le+1,la-le+1:la+le+1,Nsc+1),p);
+  else
+        im = im*sqrt(vari/var2(im));
+  end
+  if (var2(imag(ch))/var2(real(ch)) > 1e-6)
+    fprintf(1,'Discarding non-trivial imaginary part, lowPass autoCorr!');
+  end
+  im = real(im);
+end % cmask(2)
+if cmask(1),
+  if vari/var0 > 1e-4,
+        [im,snr7(niter,2*(Nsc+1)-1)] = modskew(im,skew0p(Nsc+1),p);     % Adjusts skewness 
+        [im,snr7(niter,2*(Nsc+1))] = modkurt(im,kurt0p(Nsc+1),p);       % Adjusts kurtosis 
+  end
+end     % cmask(2)
+ 
+  %% Subtract mean of magnitude
+if cmask(3),
+  magMeans = zeros(size(pind,1), 1);
+  for nband = 1:size(pind,1)
+    indices = pyrBandIndices(pind,nband);
+    magMeans(nband) = mean2(apyr(indices));
+    apyr(indices) = apyr(indices) - magMeans(nband);
+  end
+end     % cmask(3)
+
+  %% Coarse-to-fine loop:
+  for nsc = Nsc:-1:1
+    
+    firstBnum = (nsc-1)*Nor+2;
+    cousinSz = prod(pind(firstBnum,:));
+    ind = pyrBandIndices(pind,firstBnum);
+    cousinInd = ind(1) + [0:Nor*cousinSz-1];
+
+    %% Interpolate parents
+if (cmask(3) | cmask(4)),
+    if (nsc<Nsc)
+      parents = zeros(cousinSz,Nor);
+      rparents = zeros(cousinSz,Nor*2);
+      for nor = 1:Nor
+        nband = (nsc+1-1)*Nor+nor+1; 
+
+        tmp = expand(pyrBand(pyr, pind, nband),2)/4;
+        rtmp = real(tmp); itmp = imag(tmp);
+        tmp = sqrt(rtmp.^2 + itmp.^2) .* exp(2 * sqrt(-1) * atan2(rtmp,itmp));
+        rparents(:,nor) = vector(real(tmp));
+        rparents(:,Nor+nor) = vector(imag(tmp));
+
+        tmp = abs(tmp);
+        parents(:,nor) = vector(tmp - mean2(tmp));
+      end
+    else
+      rparents = [];
+      parents = [];
+    end
+end % if (cmask(3) | cmask(4))
+
+if cmask(3),
+    %% Adjust cross-correlation with MAGNITUDES at other orientations/scales:
+    cousins = reshape(apyr(cousinInd), [cousinSz Nor]);
+    nc = size(cousins,2);   np = size(parents,2);
+    if (np == 0)    
+      [cousins, snr3(niter,nsc)] = adjustCorr1s(cousins, C0(1:nc,1:nc,nsc), 2, p);
+    else
+      [cousins, snr3(niter,nsc), snr4(niter,nsc)] = ...
+          adjustCorr2s(cousins, C0(1:nc,1:nc,nsc), parents, Cx0(1:nc,1:np,nsc), 3, p);
+    end
+    if (var2(imag(cousins))/var2(real(cousins)) > 1e-6)
+      fprintf(1,'Non-trivial imaginary part, mag crossCorr, lev=%d!\n',nsc);
+    else
+      cousins = real(cousins);
+      ind = cousinInd;
+      apyr(ind) = vector(cousins);
+    end
+
+    %% Adjust autoCorr of mag responses 
+    nband = (nsc-1)*Nor+2; 
+    Sch = min(pind(nband,:)/2);
+    nz = sum(sum(~isnan(ace0(:,:,nsc,1))));
+    lz = (sqrt(nz)-1)/2;
+    le = min(Sch/2-1,lz);
+    for nor = 1:Nor,
+      nband = (nsc-1)*Nor+nor+1; 
+      ch = pyrBand(apyr,pind,nband);
+      [ch, snr1(niter,nband-1)] = modacor22(ch,...
+        ace0(la-le+1:la+le+1,la-le+1:la+le+1,nsc,nor), p);
+      ch = real(ch);
+      ind = pyrBandIndices(pind,nband);
+      apyr(ind) = ch;
+      %% Impose magnitude:
+      mag = apyr(ind) + magMeans0(nband);
+      mag = mag .* (mag>0);
+      pyr(ind) = pyr(ind) .* (mag./(abs(pyr(ind))+(abs(pyr(ind))<eps)));
+    end
+end   % cmask(3)
+
+    %% Adjust cross-correlation of REAL PARTS at other orientations/scales:
+    cousins = reshape(real(pyr(cousinInd)), [cousinSz Nor]);
+    Nrc = size(cousins,2);  Nrp = size(rparents,2);
+    if  cmask(4) & (Nrp ~= 0)
+        a3 = 0; a4 = 0;
+        for nrc = 1:Nrc,
+          cou = cousins(:,nrc);
+          [cou, s3, s4] = ...
+            adjustCorr2s(cou,mean(cou.^2),rparents,Crx0(nrc,1:Nrp,nsc), 3);
+          a3 = s3 + a3;
+          a4 = s4 + a4;
+          cousins(:,nrc) = cou;
+        end
+        snr4r(niter,nsc) = a4/Nrc;
+    end
+    if (var2(imag(cousins))/var2(real(cousins)) > 1e-6)
+      fprintf(1,'Non-trivial imaginary part, real crossCorr, lev=%d!\n',nsc);
+    else
+      %%% NOTE: THIS SETS REAL PART ONLY - signal is now NONANALYTIC!
+      pyr(cousinInd) = vector(cousins(1:Nor*cousinSz));
+    end
+
+    %% Re-create analytic subbands
+    dims = pind(firstBnum,:);
+    ctr = ceil((dims+0.5)/2);
+    ang = mkAngle(dims, 0, ctr);
+    ang(ctr(1),ctr(2)) = -pi/2;
+    for nor = 1:Nor,
+      nband = (nsc-1)*Nor+nor+1; 
+      ind = pyrBandIndices(pind,nband); 
+      ch = pyrBand(pyr, pind, nband);
+      ang0 = pi*(nor-1)/Nor;
+      xang = mod(ang-ang0+pi, 2*pi) - pi;
+      amask = 2*(abs(xang) < pi/2) + (abs(xang) == pi/2);
+      amask(ctr(1),ctr(2)) = 1;
+      amask(:,1) = 1;
+      amask(1,:) = 1; 
+      amask = fftshift(amask);
+      ch = ifft2(amask.*fft2(ch));      % "Analytic" version
+      pyr(ind) = ch;
+    end
+
+    %% Combine ori bands
+    bandNums = [1:Nor] + (nsc-1)*Nor+1;  %ori bands only
+    ind1 = pyrBandIndices(pind, bandNums(1));
+    indN = pyrBandIndices(pind, bandNums(Nor));
+    bandInds = [ind1(1):indN(length(indN))];
+    %% Make fake pyramid, containing dummy hi, ori, lo
+    fakePind = pind([bandNums(1), bandNums, bandNums(Nor)+1],:);
+    fakePyr = [zeros(prod(fakePind(1,:)),1);...
+         real(pyr(bandInds)); zeros(prod(fakePind(size(fakePind,1),:)),1)]; 
+    ch = reconSFpyr(fakePyr, fakePind, [1]);     % recon ori bands only
+    im = real(expand(im,2))/4;
+    im = im + ch;
+    vari =  acr0(la+1:la+1,la+1:la+1,nsc);
+if cmask(2),
+    if vari/var0 > 1e-4,
+        [im, snr2(niter,nsc)] = ...
+        modacor22(im, acr0(la-le+1:la+le+1,la-le+1:la+le+1,nsc), p);
+    else
+        im = im*sqrt(vari/var2(im));
+    end
+end     % cmask(2)
+    im = real(im);  
+
+if cmask(1),
+  %% Fix marginal stats 
+  if vari/var0 > 1e-4,
+        [im,snr7(niter,2*nsc-1)] = modskew(im,skew0p(nsc),p);       % Adjusts skewness 
+        [im,snr7(niter,2*nsc)] = modkurt(im,kurt0p(nsc),p);         % Adjusts kurtosis
+  end
+end     % cmask(1)
+
+  end  %END Coarse-to-fine loop
+
+  %% Adjust variance in HP, if higher than desired
+if (cmask(2)|cmask(3)|cmask(4)),
+  ind = pyrBandIndices(pind,1);
+  ch = pyr(ind);
+  vHPR = mean2(ch.^2);
+  if vHPR > vHPR0,
+        ch = ch * sqrt(vHPR0/vHPR);
+        pyr(ind) = ch;
+  end
+end % cmask
+  im = im + reconSFpyr(real(pyr), pind, [0]);  %recon hi only
+
+  %% Pixel statistics
+  means = mean2(im);
+  vars = var2(im, means);
+  snr7(niter,2*(Nsc+1)+1) = snr(var0,var0-vars);
+  im = im-means;                        % Adjusts mean and variance
+  [mns mxs] = range2(im + mean0);
+  snr7(niter,2*(Nsc+1)+2) = snr(mx0-mn0,sqrt((mx0-mxs)^2+(mn0-mns)^2));
+if cmask(1),
+  im = im*sqrt(((1-p)*vars + p*var0)/vars);     
+end     % cmaks(1)
+  im = im+mean0;
+if cmask(1),
+  [im, snr7(niter,2*(Nsc+1)+3)] = modskew(im,skew0,p);  % Adjusts skewness (keep mean and variance)
+  [im, snr7(niter,2*(Nsc+1)+4)] = modkurt(im,kurt0,p);  % Adjusts kurtosis (keep mean and variance,
+                                        % but not skewness)
+  im = max(min(im,(1-p)*max(max(im))+p*mx0),...
+                  (1-p)*min(min(im))+p*mn0);            % Adjusts range (affects everything)    
+else 
+  snr7(niter,2*(Nsc+1)+3) = snr(skew0,skew0-skew2(im));
+  snr7(niter,2*(Nsc+1)+4) = snr(kurt0,kurt0-kurt2(im));
+end     % cmask(1)
+
+  %% Force pixels specified by image mask
+  if (exist('imask') & ~isempty(imask) )
+        im = mask.*reshape(imask(:,2 - (size(imask,2)==1)),size(im)) + ...
+                (1-mask).*im;
+  end
+
+  snr6(niter,1) = snr(im-mean0,im-prev_im);
+
+  if floor(log2(niter))==log2(niter),
+        nq = nq + 1;
+        imS(:,:,nq) = im;
+  end
+
+  tmp = prev_im;
+  prev_im=im;   
+
+  figure(imf);
+  subplot(1,2,1);
+  showIm(im-tmp,'auto',1); title('Change');
+  subplot(1,2,2);
+  showIm(im,'auto',1); title(sprintf('iteration %d/%d',niter,Niter));
+  drawnow
+  
+  % accelerator
+  alpha = 0.8;
+  im = im + alpha*(im - tmp);
+  
+commented = 1;  % set it to 0 for displaying convergence of parameters in SNR (dB)
+if ~commented,    
+   
+% The graphs that appear reflect
+% the relative distance of each parameter or group
+% of parametersi, to the original's, in decibels.
+% Note, however, that when the original parameters
+% are close to zero, this measurement is meaningless.
+% This is why in some cases it seems that some of
+% the parameters do not converge at all.
+
+figure(snrf);
+if cmask(1)
+  subplot(171); plot(snr7); title('Mrgl stats');
+end
+if cmask(2),
+  subplot(172); plot(snr2); title('Raw auto');
+end
+if cmask(3),
+  subplot(173); plot(snr1); title('Mag auto'); 
+  subplot(174); plot(snr3); title('Mag ori');
+  subplot(175); plot(snr4); title('Mag scale');
+end
+if (Nrp > 0) & cmask(4),
+  subplot(176); plot(snr4r); title('Phs scale');
+end
+  subplot(177); plot(snr6); title('Im change');
+  drawnow
+  
+end  % if ~commented
+
+end %END  MAIN LOOP
+
+im = prev_im;
+
+snrP = [snr7 snr2 snr1 snr3 snr4 snr4r snr6];
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/upBlur.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/upBlur.m
new file mode 100755
index 0000000..948c2e1
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/upBlur.m
@@ -0,0 +1,52 @@
+% RES = upBlur(IM, LEVELS, FILT)
+%
+% Upsample and blur an image.  The blurring is done with filter
+% kernel specified by FILT (default = 'binom5'), which can be a string
+% (to be passed to namedFilter), a vector (applied separably as a 1D
+% convolution kernel in X and Y), or a matrix (applied as a 2D
+% convolution kernel).  The downsampling is always by 2 in each
+% direction.
+%
+% The procedure is applied recursively LEVELS times (default=1).
+
+% Eero Simoncelli, 4/97.
+
+function res = upBlur(im, nlevs, filt)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('nlevs') ~= 1) 
+  nlevs = 1;
+end
+
+if (exist('filt') ~= 1) 
+  filt = 'binom5';
+end
+
+%------------------------------------------------------------
+
+if isstr(filt)
+  filt = namedFilter(filt);
+end  
+
+if nlevs > 1
+  im = upBlur(im,nlevs-1,filt);
+end
+
+if (nlevs >= 1)
+  if (any(size(im)==1))
+    if (size(im,1)==1)
+      filt = filt';
+    end
+    res = upConv(im,filt,'reflect1',(size(im)~=1)+1);
+  elseif (any(size(filt)==1))
+    filt = filt(:);
+    res = upConv(im,filt,'reflect1',[2 1]);
+    res = upConv(res,filt','reflect1',[1 2]);
+  else
+    res = upConv(im,filt,'reflect1',[2 2]);
+  end
+else
+  res = im;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/upConv.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/upConv.m
new file mode 100755
index 0000000..10bea46
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/upConv.m
@@ -0,0 +1,80 @@
+% RES = upConv(IM, FILT, EDGES, STEP, START, STOP, RES)
+%
+% Upsample matrix IM, followed by convolution with matrix FILT.  These
+% arguments should be 1D or 2D matrices, and IM must be larger (in
+% both dimensions) than FILT.  The origin of filt
+% is assumed to be floor(size(filt)/2)+1.
+%
+% EDGES is a string determining boundary handling:
+%    'circular' - Circular convolution
+%    'reflect1' - Reflect about the edge pixels
+%    'reflect2' - Reflect, doubling the edge pixels
+%    'repeat'   - Repeat the edge pixels
+%    'zero'     - Assume values of zero outside image boundary
+%    'extend'   - Reflect and invert
+%    'dont-compute' - Zero output when filter overhangs OUTPUT boundaries
+%
+% Upsampling factors are determined by STEP (optional, default=[1 1]),
+% a 2-vector [y,x].
+% 
+% The window over which the convolution occurs is specfied by START 
+% (optional, default=[1,1], and STOP (optional, default = 
+% step .* (size(IM) + floor((start-1)./step))).
+%
+% RES is an optional result matrix.  The convolution result will be 
+% destructively added into this matrix.  If this argument is passed, the 
+% result matrix will not be returned. DO NOT USE THIS ARGUMENT IF 
+% YOU DO NOT UNDERSTAND WHAT THIS MEANS!!
+% 
+% NOTE: this operation corresponds to multiplication of a signal
+% vector by a matrix whose columns contain copies of the time-reversed
+% (or space-reversed) FILT shifted by multiples of STEP.  See corrDn.m
+% for the operation corresponding to the transpose of this matrix.
+
+% Eero Simoncelli, 6/96.  revised 2/97.
+
+function result = upConv(im,filt,edges,step,start,stop,res)
+
+%% THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
+
+%fprintf(1,'WARNING: You should compile the MEX version of "upConv.c",\n         found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path.  It is MUCH faster, and provides more boundary-handling options.\n');
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('edges') == 1) 
+  if (strcmp(edges,'reflect1') ~= 1)
+    warning('Using REFLECT1 edge-handling (use MEX code for other options).');
+  end
+end
+
+if (exist('step') ~= 1)
+  step = [1,1];
+end     
+
+if (exist('start') ~= 1)
+  start = [1,1];
+end     
+
+% A multiple of step
+if (exist('stop') ~= 1)
+  stop = step .* (floor((start-ones(size(start)))./step)+size(im))
+end     
+
+if ( ceil((stop(1)+1-start(1)) / step(1)) ~= size(im,1) )
+  error('Bad Y result dimension');
+end
+if ( ceil((stop(2)+1-start(2)) / step(2)) ~= size(im,2) )
+  error('Bad X result dimension');
+end
+
+if (exist('res') ~= 1)
+  res = zeros(stop-start+1);
+end     
+
+%------------------------------------------------------------
+
+tmp = zeros(size(res));
+tmp(start(1):step(1):stop(1),start(2):step(2):stop(2)) = im;
+
+result = rconv2(tmp,filt) + res;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/var2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/var2.m
new file mode 100755
index 0000000..6957eff
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/var2.m
@@ -0,0 +1,17 @@
+% V = VAR2(MTX,MEAN)
+%
+% Sample variance of a matrix.
+%  Passing MEAN (optional) makes the calculation faster.
+
+function res = var2(mtx, mn)
+
+if (exist('mn') ~= 1)
+  mn =  mean2(mtx);
+end
+
+if (isreal(mtx))
+  res = sum(sum(abs(mtx-mn).^2)) / max((prod(size(mtx)) - 1),1);
+else
+  res = sum(sum(real(mtx-mn).^2)) + i*sum(sum(imag(mtx-mn).^2));
+  res = res  / max((prod(size(mtx)) - 1),1);
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/vectify.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/vectify.m
new file mode 100755
index 0000000..3664223
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/vectify.m
@@ -0,0 +1,8 @@
+% [VEC] = columnize(MTX)
+% 
+% Pack elements of MTX into a column vector.  Just provides a
+% function-call notatoin for the operation MTX(:)
+
+function vec = columnize(mtx)
+
+vec = mtx(:);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/vector.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/vector.m
new file mode 100755
index 0000000..6168151
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/vector.m
@@ -0,0 +1,7 @@
+% [VEC] = vector(MTX)
+% 
+% Pack elements of MTX into a column vector.  Same as VEC = MTX(:)
+
+function vec = vector(mtx)
+
+vec = mtx(:);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrBand.m
new file mode 100755
index 0000000..c027cca
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrBand.m
@@ -0,0 +1,39 @@
+% RES = wpyrBand(PYR, INDICES, LEVEL, BAND)
+%
+% Access a subband from a separable QMF/wavelet pyramid.  
+% 
+% LEVEL (optional, default=1) indicates the scale (finest = 1,
+% coarsest = wpyrHt(INDICES)).  
+% 
+% BAND (optional, default=1) indicates which subband (1=horizontal,
+% 2=vertical, 3=diagonal).
+
+% Eero Simoncelli, 6/96.
+
+function im =  wpyrBand(pyr,pind,level,band)
+
+if (exist('level') ~= 1)
+  level = 1;
+end
+
+if (exist('band') ~= 1)
+  band = 1;
+end
+
+if ((pind(1,1) == 1) | (pind(1,2) ==1))
+  nbands = 1;
+else
+  nbands = 3;
+end
+                
+if ((band > nbands) | (band < 1))
+  error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands));
+end
+        
+maxLev = wpyrHt(pind);
+if ((level > maxLev) | (level < 1))
+  error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev));
+end
+
+band = band + nbands*(level-1);
+im = pyrBand(pyr,pind,band);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrHt.m
new file mode 100755
index 0000000..476be83
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrHt.m
@@ -0,0 +1,15 @@
+% [HEIGHT] = wpyrHt(INDICES)
+%
+% Compute height of separable QMF/wavelet pyramid with given index matrix.
+
+% Eero Simoncelli, 6/96.
+
+function [ht] =  wpyrHt(pind)
+
+if ((pind(1,1) == 1) | (pind(1,2) ==1))
+        nbands = 1;
+else
+        nbands = 3;
+end
+
+ht = (size(pind,1)-1)/nbands;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrLev.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrLev.m
new file mode 100755
index 0000000..18f30ae
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/wpyrLev.m
@@ -0,0 +1,30 @@
+% [LEV,IND] = wpyrLev(PYR,INDICES,LEVEL)
+%
+% Access a level from a separable QMF/wavelet pyramid.
+% Return as an SxB matrix, B = number of bands, S = total size of a band.
+% Also returns an Bx2 matrix containing dimensions of the subbands.
+
+% Eero Simoncelli, 6/96.
+
+function [lev,ind] =  wpyrLev(pyr,pind,level)
+
+if ((pind(1,1) == 1) | (pind(1,2) ==1))
+  nbands = 1;
+else
+  nbands = 3;
+end
+                
+if ((level > wpyrHt(pind)) | (level < 1))
+  error(sprintf('Level number must be in the range [1, %d].', wpyrHt(pind)));
+end     
+        
+firstband = 1 + nbands*(level-1)
+firstind = 1;
+for l=1:firstband-1
+  firstind = firstind + prod(pind(l,:));
+end
+
+
+ind = pind(firstband:firstband+nbands-1,:);
+lev  = pyr(firstind:firstind+sum(prod(ind'))-1);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/zconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/zconv2.m
new file mode 100755
index 0000000..f678d89
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlab/zconv2.m
@@ -0,0 +1,41 @@
+% RES = ZCONV2(MTX1, MTX2, CTR)
+%
+% Convolution of two matrices, with boundaries handled as if the larger mtx
+% lies in a sea of zeros. Result will be of size of LARGER vector.
+% 
+% The origin of the smaller matrix is assumed to be its center.
+% For even dimensions, the origin is determined by the CTR (optional) 
+% argument:
+%      CTR   origin
+%       0     DIM/2      (default)
+%       1     (DIM/2)+1  (behaves like conv2(mtx1,mtx2,'same'))
+
+% Eero Simoncelli, 2/97.
+
+function c = zconv2(a,b,ctr)
+
+if (exist('ctr') ~= 1)
+  ctr = 0;
+end
+
+if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
+    large = a; small = b;
+elseif  (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
+    large = b; small = a;
+else
+  error('one arg must be larger than the other in both dimensions!');
+end
+
+ly = size(large,1);
+lx = size(large,2);
+sy = size(small,1);
+sx = size(small,2);
+
+%% These values are the index of the small mtx that falls on the
+%% border pixel of the large matrix when computing the first
+%% convolution response sample:
+sy2 = floor((sy+ctr+1)/2);
+sx2 = floor((sx+ctr+1)/2);
+
+clarge = conv2(large,small);
+c = clarge(sy2:ly+sy2-1, sx2:lx+sx2-1);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ChangeLog b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ChangeLog
new file mode 100755
index 0000000..f20c499
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ChangeLog
@@ -0,0 +1,430 @@
+           Log of changes made to matlabPyrTools code
+                (important changes marked with **)
+----------------------------------------------------------------------- 
+2004-10-14  Eero Simoncelli  <eero@sesto.cns.nyu.edu>
+
+        * Made new tarfile (version 1.3) 
+        
+        * Incorporated complex-valued steerable pyramid code (buildSCFpyr,
+        buildSCFpyrLevs,reconSCFpyr) written by Javier Portilla in 9/97,
+        and used in our work on texture representation/synthesis
+        (Portilla&Simoncelli, Int'l Journal of Computer Vision,
+        40(1):49-71, Dec 2000).
+        
+        * Incorporated imGradient.m from personal code.
+        
+        * reagan.pgm out.  feynam.pgm in
+        
+2004-03-20  Eero Simoncelli  <eero@sesto.cns.nyu.edu>
+
+        * blur.m added (just calls blurDn and then upBlur).
+        
+2003-08-06  Eero Simoncelli  <eero@sesto.cns.nyu.edu>
+
+        * blurDn.m (filt): Forced correct scaling of filters in  1D
+
+2003-05-28  Eero Simoncelli  <eero@ferrando.cns.nyu.edu>
+
+        * incorporated setPyrBand.m from local code
+
+2002-10-01  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * incorporated clip.m from local code
+
+2002-09-18  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * pointOp.m: Added the new 'extrap' option for matlab's interp1 to
+          make this m-file version more compatible with the mex version.
+
+Wed Aug 28 2002  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * var2.m: now returns zero (instead of error) for matrix of size 1.
+        * function VECTORIZE renamed to VECTIFY, since it was colliding
+          with a function introduced in standard matlab.
+        
+Dec 27 2001  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * Modified calls to upConv in reconSpyr.m and reconSpyrLevs.m so
+        that the returned result is bound.  Previously, had relied on the
+        MEX version of upConv to destructively modify the result array,
+        users had been getting errors because they were using the m-file
+        version of upConv.
+        
+Wed Sep 19 2001  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+        
+        * buildSFpyrLevs/reconSFpyrLevs: replace use of "i" with sqrt(-1), to
+          avoid  problems if user rebinds it!
+        
+Wed Mar 28 10:22:01 2001  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * Moved innerProd.m and all associated MEX files from the
+        matlabLocal source tree into matlabPyrTools.  
+        * Added innerProd to Contents.m
+        * Updated/clarified WARNINGS in all *.m files that have MEX versions.
+        
+Tue Mar 27 11:21:53 2001  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * Incorporated Windows MEX files (*.dll) into MEX subdirectory.
+         Windows users should either copy these into the main directory,
+         or put the MEX subdirectory in their matlab path.
+        
+Fri Mar 23 14:46:16 2001  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * buildSFpyrLevs.m, reconSFpyrLevs.m: shift the raised-cosine
+        lookup table (Xrcos) instead of incrementing the log-radial image
+        (log_rad).  THis is more efficient...
+
+Fri Oct  1 19:37:03 1999  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * upConv.m: Did not return correct size result when STOP argument
+        was passed.  Thanks to hertzman@mrl.nyu.edu for pointing this out.
+        
+Fri Sep 17 15:53:26 1999  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * buildSFpyrLevs.m: Changed lutsize to 1024, giving a slight
+        increase in accuracy.
+
+Thu Feb 25 18:10:38 1999  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * histo1.m: Modified histo.m to be more compatible (but still not
+        exactly the same) as the MEX file version.
+
+Fri Jun 12 21:15:39 1998  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * TUTORIALS pyramids.m upgraded.
+
+Tue Feb 17 13:22:28 1998  Eero Simoncelli  <eero.simoncelli@nyu.edu>
+
+        * showIm.m: Dims are now printed followed by the zoom factor.
+
+Mon Oct 13 14:49:51 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * mkSquare.m: Modified to do raised-cosine soft threshold
+        transitions.
+
+Tue Oct  7 10:13:51 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * upConv.m: Argument order was wrong (this function is not used
+        anyway, unless you don't compile the MEX code). - Thanks to
+        farid@psyche.mit.edu for pointing this out.
+
+Thu Sep 25 16:09:49 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * MEX/wrap.c: Changed #include <malloc.h> to <stdlib.h>, as
+        suggested by David Brainard.  * Incorporated Mac-compiled mex
+        files, courtesy of David Brainard.
+        
+Sat Sep  6 16:10:25 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * MEX/convolve.h:  abstracted out type of images with typedef image_type.
+        Added ansi declarations.
+        
+Fri Aug 29 13:49:16 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** showIm.m: Modified to behave better under resizing (and printing):
+        resets axis units to "normalized".
+
+Thu Aug 28 22:56:52 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** MEX/edges.c: reflect1, reflect2, repeat, extend upgraded to work
+        properly for non-symmetric filters.  reflect2 and extend were also
+        broken for upConv.  Added qreflect2 to handle even-length QMF's
+        which broke under the reflect2 modification.
+        * Added example code to TUTORIALS/matlabPyrTools to illustrate the
+        boundary-handling behavior...
+        
+Thu Aug 21 13:34:17 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * var2, skew2, kurt2: modified to return complex values for complex images.
+        * imStats.m: now gives an error for complex args.
+
+Thu Aug 14 15:24:29 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Modified shift.m: negated the meaning of the offset parameter,
+        such that RES=shift(MTX,OFFSET) means RES(POS)=MTX(POS-OFFSET)
+        (this is more intuitive).
+
+Thu Jul 10 17:06:52 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Modified MEX/Makefile-* to be consistent with matlab5:
+           - call mex instead of cmex
+           - use -V4 flag (creating matlab v4 compatible binaries)
+        
+        * showIm.m (xlbl_offset): Modified to use "points" units, so that
+        printed images look correct.  Still slightly busted for arbitrary figure
+        window sizes and for printing.
+        
+        * Modified upConv.c: does not return ANYTHING if you pass a result
+        argument (this had been causing occasional problems with matlab's 
+        memory manager).
+        
+Mon Jun 30 12:09:30 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * reconSFpyr.m (res): now returns real part (oops).
+
+        * reconSpyrLevs.m (maxLev): got rid of superfluous nbands argument
+        (can be calculated from bfilts).
+
+Mon May 26 12:29:54 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * showIm.m/pgmWrite.m: Modified 'auto3'-scaling to use a
+        histogram.  This gives a significant speedup.
+
+        * fixed a few minor bugs in the TUTORIALS, having to do with 
+        matching image sizes to the machine speed...
+
+Sat May 10 17:27:25 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * pgmWrite.m: fixed auto-scaling bug.  Added new scaling
+        calculations, parallel to those of imShow.
+
+Fri May  9 09:02:56 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * buildSFpyr.m: Changed NBANDS argument to be ORDER, which is one
+        less than the number of orientation bands.  This is consistent
+        with the derivative order, and the labels on the spNFilters files.
+
+Tue May  6 19:08:18 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** Added buildSFpyr, reconSFpyr: Steerable pyramids constructed
+        in the Fourier domain.  Radial functions tile, with a
+        raised-cosine falloff.  Angular functions are
+        cos(theta-k\pi/(K+1))^K, where K is the order (number of bands
+        minus 1).  Compared to the convolution version:
+            + Reconstruction is exact (within floating point errors) 
+            + Can produce any number of orientation bands. 
+            - Typically slower.
+            - Boundary-handling must be circular.
+        Could be made much more efficient by taking advantage of symmetries in
+        the fft!
+        
+        * Added example usage of Fourier steerable pyramid to TUTORIALS/pyramids.m
+        
+        * steer.m:  fixed for harmonic lists including zero.
+
+Sun May  4 15:16:10 1997  Eero Simoncelli  <eero@ferrando.cns.nyu.edu>
+
+        * MEX/Makefile-linux: created.
+        
+        * spyrHt, spyrNumBands: Modified to return 0 for pyramids of height 0.
+        
+        * reconWpyr.m: utilize desctructive addition in calls to upConv.
+        
+        * reconSpyr.m: Added error check to ensure consistancy between
+        pyramid and filter file.  Utilize destructive addition in upConv
+        call on highpass band.  Modified to work properly with pyramids of
+        height 0.
+        
+Mon Apr 28 13:38:10 1997  Eero Simoncelli  <eero@ferrando.cns.nyu.edu>
+
+        * lplot.m: modified to handle complex vectors,  use standard MatLab 
+          indices, and show minimal axes.  Added xrange parameter to allow
+          adjustment of X axis labeling.
+
+Sun Apr 27 20:20:41 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * var2, skew2, kurt2: enhanced to work on complex matrices.
+        
+Sat Apr 26 11:16:12 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Changed parent directory (and distribution) name:
+                   matlabImTools -> matlabPyrTools
+
+        * namedFilter.m: Added two more Daubechies filters, and modified
+        names to match the reference (e.g., daub2 is now a 4-tap filter).
+
+        * Added vectorize.m: trivial function to pack matrix into vector (i.e., 
+        computes mtx(:)).
+        
+        * Added upBlur.m: Upsample and blur (parallels blurDn).
+
+Sun Apr 13 14:23:38 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * TUTORIALS/pyramids.m: Added plots of Fourier spectra for Wavelet bases.
+        
+        * make-tar-file: switched from compress to  gzip  for the
+        distribution tarfile.
+
+        * namedFilter.m: Added a few even-length QMF's from Johnston80.
+
+Fri Apr 11 19:16:21 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * buildWpyr.m, reconWpyr.m: Modified slightly, so that subsampling
+        lattice is better for even-length filters.
+        
+        * TUTORIALS/pyramids.m: Substantially overhauled.
+        
+Thu Apr 10 15:20:23 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * blurDn.m: added this function to downsample an image by a factor
+        2^L.
+
+        * Fixed minor bug in upConv.m: errors in image size checking.
+
+Mon Apr  7 13:25:37 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Changed TUTORIALS/matlabImTools.m to use histo.mex instead of
+        matlab's hist.
+
+Wed Apr  2 13:20:55 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** Incorporated Denis Pelli's ThinkC and MetroWorks projects for
+        Macintosh versions of the MEX code, along with MEX binaries.  These
+        are included as an HQX'ed self-extracting archive
+        (Macintosh-MEX.sit.hqx), in the MEX subdirectory.
+
+Tue Apr  1 15:35:31 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * edges.c: modified by Denis Pelli to support THINK C.  * edges.c:
+        
+        * histo.c, upConv.c, corrDn.c: minor changes in error message
+        printouts, to work around bugs in THINK C.
+        
+        * Included Denis Pelli's MacReadMe file in the MEX subdirectory,
+        which gives instructions for MEX file compilation on a MacIntosh
+        (PPC or 68k).
+        
+        * wrap.c, convolve.c, edges.c: added explicit int function
+        declarations, and return values.
+
+        * range2.m/range2.c: A MEX function for fast min/max computation.
+        Adjusted entropy2.m, histo.m, imStats.m, pgmWrite.m, showIm.m,
+        showLpyr.m, showSpyr.m, showWpyr.m to call it.
+          
+Thu Mar 27 17:23:05 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** histo.m/histo.c: Added MEX function HISTO, a fast replacement
+        for matlab's HIST function.  Modified histoMatch.m, entropy2.m to
+        call it.
+        
+        * Changed main directory  name to matlabImTools.
+        
+        * Added TUTORIALS/README file.
+        
+Wed Mar 19 14:19:51 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Changed directory name: MEX_SRC -> MEX
+
+Wed Mar 12 17:00:03 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * mkGaussian.m: fixed another (X,Y) bug: both dimensions and 
+        cov/mean are now specified in [y,x] order.
+
+Tue Mar 11 19:08:17 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * showSpyr.m: Fixed a bug that was dropping display of one
+        orientation band when there were more than 2 of them!
+
+Mon Mar 10 19:08:24 1997  Eero Simoncelli  <eero@chrysothemis.cims.nyu.edu>
+
+        * Added shift.m
+        
+        * makeSteerMtx -> steerDir2HarmMtx
+        
+        * Added TUTORIALS/matlab-EPS.m: examples using the code in this
+        distribution.
+
+Sun Mar  9 17:49:18 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** showIm.m:  
+          - args: changed order so that NSHADES is last.
+          - TITLES: Can now pass a string for IM, which will be evaluated
+            in the global environment to get the matrix.  The string is
+            used as a title.  MATLAB v.5 ONLY!!!
+          - Added 'auto3' RANGE value, that scales based on percentiles.
+            THis is more robust to outliers than 'auto2' or 'auto1'.
+        
+        * pixelAxes.m: Made a more serious attempt to reverse-engineer
+          Mathworks' image pixelization.  It is improved, but still makes
+          occasional errors.
+        
+        * Added skew2.m.
+        
+Fri Mar  7 10:11:07 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * pixelAxes.m: Modified to take an optional
+        ZOOM argument.  Fixed dimension ordering bug
+        (positions are reported (x,y), but mtx dims are (y,x)!)
+        
+        * showIm.m: Added an optional ZOOM argument.
+
+Thu Mar  6 14:17:19 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Added showLpyr, showWpyr, showSpyr.  Modified
+        TUTORIALS/pyramids.m to use them.
+        
+        * added pixelAxes.m: Adjusts size (in pixels) of currently
+        displayed image to be a multiple of the matrix dimensions, 
+        thus eliminating display aliasing artifacts.
+         This is now called by all the "show" commands.
+
+Mon Mar  3 17:33:25 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Fixed bug in pgmWrite (dimensions were written in reverse order).
+
+        * Fixed bug in showIm (X and Y coords were swapped on label display).
+        
+        * Fixed bug in reconLpyr (swapped X and Y coords on int_sz)
+        
+        * Changed calls to "reshape" to pass dimensions individually --
+        older version of matlab do not accept the reshape(mtx,[y x]) form.
+        
+        * Fixed bug in mkDisc: sz a scalar.
+        
+        * Added ifftshift.m
+        
+Fri Feb 28 11:07:20 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+        
+        * Re-worked TUTORIALS/pyramids.m
+
+        * buildGpyr and buildLpyr now use 1+maxPyrHt for default height.
+        
+        * Fixed buildGpyr to work on 1D signals.
+        
+        ** Gaussian/Laplacian/Wavelet pyramid build and recon functions:
+          - work properly with new corrDn/upConv.
+          - use separable convolutions 
+          - use destructive modification ability of upConv (less memory
+          allocation)
+        
+        * modulateFlipShift -> modulateFlip.
+        
+        * added lpyrHt, wpyrHt, spyrHt to return number of levels in a pyramid.
+        
+Thu Feb 27 15:39:53 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        * Changed angular coordinate systems to CLOCKWISE in mkRamp,
+        mkTheta, mkSine, mkSquare.  This is unnatural for screen viewing,
+        but consistent with an origin in the upper left corner of the
+        image, which is the way one addresses the underlying matrix.
+
+        * mkSine and mkSquare can now take a frequency vector or the 
+          period and direction args
+        
+Tue Feb 25 11:58:33 1997  Eero Simoncelli  <eero@servilia.cns.nyu.edu>
+
+        ** Rewrote corrDn/upConv C routines:
+          - more efficient
+          - changed START parameters to have [1 1] origin, consistent with
+            matlab
+          - added STOP parameters
+          - upConv allows destructive modification of a result arg
+          - changed order of other params (sorry)
+          - wrote test file conv_test.m
+        * wrote zconv2.m
+
+Wed Aug 19 20:39:15 1996  Eero Simoncelli  (eero@tarpon.cis.upenn.edu)
+
+        ** Added "pointOp" function (MUCH faster than interp1).
+        ** Added "histoMatch" function.
+
+Fri Aug  2 00:56:31 1996  Eero Simoncelli  (eero@tarpon.cis.upenn.edu)
+
+        * Changed all function/file-names to be of the form "fooBar".  *
+        Fixed entropy2.m (busted due to typo).
+
+Original convolution code was written in Spring 1986, and comes from
+OBVIUS (Object-Based Vision and Image Understanding System), an
+interactive image-processing system written in Common Lisp (with calls
+to C code).
+        
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/Contents.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/Contents.m
new file mode 100755
index 0000000..d19f067
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/Contents.m
@@ -0,0 +1,107 @@
+% Image and Multi-scale Pyramid Tools
+% Version 1.3,  October 2004.
+% Created: Early Spring, 1996. Eero Simoncelli, eero.simoncelli@nyu.edu
+%
+% See README file for brief description.
+% See ChangeLog file for latest modifications. 
+% See TUTORIALS subdirectory for demonstrations.
+% Type "help <command-name>" for documentation on individual commands.
+% -----------------------------------------------------------------
+% Synthetic Images (matrices):
+%   mkImpulse  - Make an image containing an impulse.
+%   mkRamp     - Make an image containing a ramp function.
+%   mkR        - Make an image containing distance from the origin.
+%   mkAngle    - Make an image containing angle about origin.
+%   mkDisc     - Make an image containing a disk image.
+%   mkGaussian - Make an image containing a Gaussian function.
+%   mkZonePlate - Make an image containing a zone plate (cos(r^2)).
+%   mkAngularSine - Make an image containing an angular sine wave (pinwheel).
+%   mkSine     - Make an image containing a sine grating.
+%   mkSquare   - Make an image containing a square grating.
+%   mkFract    - Make an image containing fractal (1/f) noise.
+%
+% Point Operations:
+%   clip       - clip values to a range. 
+%   pointOp    - Lookup table (much faster than interp1) [MEX file]
+%   histo      - Efficient histogram computation [MEX file]
+%   histoMatch - Modify matrix elements to match specified histogram stats.
+%
+% Convolution (first two are significantly faster):
+%   corrDn     - Correlate & downsample with boundary-handling [MEX file]
+%   upConv     - Upsample & convolve with boundary-handling [MEX file]
+%   blurDn     - Blur and subsample a signal/image.
+%   upBlur     - Upsample and blur a signal/image.
+%   blur       - Multi-scale blurring, calls blurDn and then upBlur.
+%   cconv2     - Circular convolution.
+%   rconv2     - Convolution with reflected boundaries.
+%   zconv2     - Convolution assuming zeros beyond image boundaries.
+%
+% General pyramids:
+%   pyrLow     - Access lowpass subband from (any type of) pyramid
+%   pyrBand    - Access a subband from (any type of) pyramid
+%   setPyrBand - Insert an image into (any type of) pyramid as a subband 
+%   pyrBandIndices - Returns indices for given band in a pyramid vector
+%   maxPyrHt   - compute maximum number of scales in a pyramid
+%
+% Gaussian/Laplacian Pyramids:
+%   buildGpyr  - Build a Gaussian pyramid of an input signal/image.
+%   buildLpyr  - Build a Laplacian pyramid of an input signal/image.
+%   reconLpyr  - Reconstruct (invert) the Laplacian pyramid transform.
+%
+% Separable orthonormal QMF/wavelet Pyramids:
+%   buildWpyr  - Build a separable wavelet representation of an input signal/image.
+%   reconWpyr  - Reconstruct (invert) the wavelet transform.
+%   wpyrBand   - Extract a single band of the wavelet representation.
+%   wpyrLev    - Extract (packed) subbands at a particular level
+%   wpyrHt     - Number of levels (height) of a wavelet pyramid.
+%
+% Steerable Pyramids:
+%   buildSpyr  - Build a steerable pyramid representation of an input image.
+%   reconSpyr  - Reconstruct (invert) the steerable pyramid transform.
+%   buildSFpyr - Build a steerable pyramid representation in the Fourier domain.
+%   reconSFpyr - Reconstruct (invert) the (Fourier domain) steerable pyramid transform.
+%   spyrBand   - Extract a single band from a steerable pyramid.
+%   spyrHigh   - Highpass residual band.
+%   spyrLev    - A whole level (i.e., all images at a given scale) of a steerable pyramid.
+%   spyrHt     - Number of levels (height) of a steerable pyramid.
+%   spyrNumBands - Number of orientation bands in a steerable pyramid.
+%
+% Steerable filters / derivatives:
+%   imGradient - Compute gradient of image using directionally accurete filters.
+%   steer      - Steer filters (or responses).
+%   steer2HarmMtx - Construct a matrix mapping direcional basis to angular harmonics. 
+% 
+% Filters:
+%   binomialFilter  - returns a filter of binomial coefficients.
+%   namedFilter     - some typical Laplacian/Wavelet pyramid filters
+%   spNFilters      - Set of Nth order steerable pyramid filters.
+%   derivNFiltersS  - Matched set of S-tap 1D derivatives, orders 0 to N.
+% 
+% Display:
+%   showIm     - Display a matrix (real or complex) as grayscale image(s).
+%                Displays dimensions, subsampling, and range of pixel values.
+%   showLpyr   - Display a Laplacian pyramid.
+%   showWpyr   - Display a separable wavelet pyramid.
+%   showSpyr   - Display a steerable pyramid.
+%   lplot      - "lollipop" plot.
+%   nextFig    - Make next figure window current.
+%   pixelAxes  - Make image display use an integer number of pixels 
+%                per sample to avoid resampling artifacts.
+% 
+% Statistics (for 2D Matrices):
+%   range2     - Min and max of image (matrix) [MEX file]
+%   mean2      - Sample mean of an image (matrix). 
+%   var2       - Sample variance of an image (matrix). 
+%   skew2      - Sample skew (3rd moment / variance^1.5) of an image (matrix). 
+%   kurt2      - Sample kurtosis (4th moment / variance^2) of an image (matrix). 
+%   entropy2   - Sample entropy of an image (matrix).
+%   imStats    - Report sample statistics of an image, or pair of images.
+%
+% Miscellaneous:
+%   pgmRead    - Load a "pgm" image into a MatLab matrix [try einstein.pgm,feynman.pgm]
+%   pgmWrite   - Write a MatLab matrix to a "pgm" image file.
+%   shift      - circular shift a 2D matrix by an arbitrary amount.
+%   vectify    - pack matrix into column vector (i.e., function to compute mtx(:)).
+%   ifftshift  - inverse of MatLab's FFTSHIFT (differs for odd-length dimensions)
+%   rcosFn     - return a lookup table of a raised-cosine threshold fn.
+%   innerProd  - Compute M'*M efficiently (i.e., do not copy) [MEX file]
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/-MacReadMe b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/-MacReadMe
new file mode 100755
index 0000000..898dc0c
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/-MacReadMe
@@ -0,0 +1 @@
+MacReadMe
How to compile a MEX file for Macintosh
(Based on a similar note written by David Brainard and Denis Pelli to accompany the Psychophysics Toolbox.)

A MEX file (short for "MATLAB extension") contains code that implements a new MATLAB function, allowing users to use the full power of the C language and the Macintosh hardware and operating system in implementing a new MATLAB function. This document explains how to produce a MEX file that is "fat" (i.e. will run as native code on both 68K and PowerPC Macs) and is compatible with both MATLAB 4 and 5.

1) To produce a MATLAB MEX file with PowerPC code you must have the Metrowerks CodeWarrior C compiler (version 10 or better, abbreviated as CW below). To produce 68K code we still use the Symantec THINK C compiler (version from Symantec C++ 8 CD-ROM release 5), but we will soon be switching to Metrowerks CodeWarrior. (See note A below.)

2) Place a copy of the MATLAB 4:Extern folder, supplied by Mathworks, on your compiler's search path. We suggest that you name the copy "MEX V4". (See notes B and C, below.) 

3) Build any of the MEX files simply by opening its project file and asking your compiler to "Build Code Resource" (in THINK C) or to "Make" it (in CW).  For each MEX file, e.g. histo.mex, there are two associated projects, e.g. histo.µ for CW, and histo.¹.4 for THINK C. To build a "fat" MEX, that runs native on both 68K and PowerPC, you should first compile in THINK C, and then in CW. (See note A, below.)

Denis Pelli
April 2, 1997

Notes

A) The Mathworks support only the THINK C compiler to make 68K MEX code for MATLAB version 4 and only the CW compiler to make PPC MEX files for MATLAB 4 and both 68K and PPC for MATLAB 5. This archive includes THINK and CW projects. To build a fat MEX file for MATLAB 4, first "make" the THINK C version (e.g. histo.¹.4), producing a file with a .rsrc extension (e.g. histo.µ.rsrc). This is the 68K MEX file. When you then "make" histo.µ, the CW project incorporates the .rsrc file and generates a "fat" MEX file that will run native (i.e. fast) on both 68K and PowerPC. To make a 68K-only MEX file, simply rename, e.g., histo.µ.rsrc to histo.mex after you make the THINK project, and set the file type and creator to match the other MEX files. THINK C is slow and hard to work with. Symantec hasn't significantly upgraded in it many years. There is an error in the math.h header (version from Symantec C++ 8 CD-ROM release 5). We fix that error by some tricky preprocessor defines and undefines in the THINK C Prefix in each of the THINK projects. 

B) The easiest way to put a folder on your compilerÕs search path is simply to put the folder in the same folder as the compiler itself. If you want to use both CW and THINK C, then put the folder under CW, make an alias of it, and put the alias in THINK C's "Aliases" folder.

C) Happily, MATLAB 5 is capable of running both V4 and V5 MEX files. Thus we are currently distributing sources that compile into V4 MEX files. The resulting MEX files run both under V4 and V5. In the future we will drop support for V4 and THINK C. (See note A above.) 
\ No newline at end of file
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.AppleDouble/.Parent b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.AppleDouble/.Parent
new file mode 100755
index 0000000..f242a99
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.AppleDouble/.Parent
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.FBCIndex b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.FBCIndex
new file mode 100755
index 0000000..848736b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.FBCIndex
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.FBCLockFolder/.FBCSemaphoreFile b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.FBCLockFolder/.FBCSemaphoreFile
new file mode 100755
index 0000000..ab2c684
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/.FBCLockFolder/.FBCSemaphoreFile
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-linux b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-linux
new file mode 100755
index 0000000..726dd31
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-linux
@@ -0,0 +1,39 @@
+MLAB = /usr/local/matlab5.1
+
+MXSFX = mexlx
+MEX = ${MLAB}/bin/mex
+
+MFLAGS = -V4
+INC = -I ${MLAB}/extern/include
+LIB = -L ${MLAB}/extern/lib
+
+CC = gcc -Wall -pedantic
+C_OPTIMIZE_SWITCH = -O2    ## For GCC
+CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
+
+all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
+        histo.${MXSFX} range2.${MXSFX}
+
+clean:
+        /bin/rm *.o
+
+corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
+
+upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
+
+pointOp.${MXSFX}: pointOp.o
+        ${MEX} ${MFLAGS} pointOp.o
+
+histo.${MXSFX}: histo.o
+        ${MEX} ${MFLAGS} histo.o
+
+range2.${MXSFX}: range2.o
+        ${MEX} ${MFLAGS} range2.o
+
+convolve.o wrap.o edges.o: convolve.h 
+
+%.o : %.c
+        ${CC} -c ${CFLAGS} $<           
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-ml6-linux b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-ml6-linux
new file mode 100755
index 0000000..f596ad7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-ml6-linux
@@ -0,0 +1,39 @@
+MLAB = /usr/local/matlab6.0
+
+MXSFX = mexglx
+MEX = ${MLAB}/bin/mex
+
+MFLAGS = -V4
+INC = -I ${MLAB}/extern/include
+LIB = -L ${MLAB}/extern/lib
+
+CC = gcc -Wall -pedantic
+C_OPTIMIZE_SWITCH = -O2    ## For GCC
+CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
+
+all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
+        histo.${MXSFX} range2.${MXSFX}
+
+clean:
+        /bin/rm *.o
+
+corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
+
+upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
+
+pointOp.${MXSFX}: pointOp.o
+        ${MEX} ${MFLAGS} pointOp.o
+
+histo.${MXSFX}: histo.o
+        ${MEX} ${MFLAGS} histo.o
+
+range2.${MXSFX}: range2.o
+        ${MEX} ${MFLAGS} range2.o
+
+convolve.o wrap.o edges.o: convolve.h 
+
+%.o : %.c
+        ${CC} -c ${CFLAGS} $<           
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-osx b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-osx
new file mode 100755
index 0000000..352d15b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-osx
@@ -0,0 +1,39 @@
+MLAB = /share/wotan/matlab13
+
+MXSFX = mexosx
+MEX = ${MLAB}/bin/mex
+
+MFLAGS =
+INC = -I ${MLAB}/extern/include
+LIB = -L ${MLAB}/extern/lib
+
+CC = cc -Wall -pedantic -no-cpp-precomp
+C_OPTIMIZE_SWITCH = -O2    ## For GCC
+CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
+
+all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
+        histo.${MXSFX} range2.${MXSFX}
+
+clean:
+        /bin/rm *.o
+
+corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
+
+upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
+
+pointOp.${MXSFX}: pointOp.o
+        ${MEX} ${MFLAGS} pointOp.o
+
+histo.${MXSFX}: histo.o
+        ${MEX} ${MFLAGS} histo.o
+
+range2.${MXSFX}: range2.o
+        ${MEX} ${MFLAGS} range2.o
+
+convolve.o wrap.o edges.o: convolve.h 
+
+%.o : %.c
+        ${CC} -c ${CFLAGS} $<           
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-solaris b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-solaris
new file mode 100755
index 0000000..2be2bdb
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-solaris
@@ -0,0 +1,38 @@
+MLAB = /export/home/Solaris2/matlab5.1
+
+MXSFX = mexsol
+MEX = ${MLAB}/bin/mex
+
+MFLAGS = -V4
+INC = -I ${MLAB}/extern/include
+LIB = -L ${MLAB}/extern/lib
+
+CC = gcc -Wall -pedantic
+C_OPTIMIZE_SWITCH = -O2    ## For GCC
+CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
+
+all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
+        histo.${MXSFX} range2.${MXSFX}
+
+clean:
+        /bin/rm *.o
+
+corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
+
+upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
+
+pointOp.${MXSFX}: pointOp.o
+        ${MEX} ${MFLAGS} pointOp.o
+
+histo.${MXSFX}: histo.o
+        ${MEX} ${MFLAGS} histo.o
+
+range2.${MXSFX}: range2.o
+        ${MEX} ${MFLAGS} range2.o
+
+convolve.o wrap.o edges.o: convolve.h 
+
+%.o : %.c
+        ${CC} -c ${CFLAGS} $<
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-sun4 b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-sun4
new file mode 100755
index 0000000..432b181
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/Makefile-sun4
@@ -0,0 +1,39 @@
+MLAB = /home/alberich/matlab4
+
+MXSFX = mex4
+MEX = ${MLAB}/bin/cmex
+
+MFLAGS = 
+INC = -I ${MLAB}/extern/include
+LIB = -L ${MLAB}/extern/lib/sun4
+
+CC = gcc
+C_OPTIMIZE_SWITCH = -O2    ## For GCC
+CFLAGS = ${C_OPTIMIZE_SWITCH} ${INC} ${LIB}
+
+all: corrDn.${MXSFX} upConv.${MXSFX} pointOp.${MXSFX} \
+        histo.${MXSFX} range2.${MXSFX}
+
+clean:
+        /bin/rm *.o
+
+corrDn.${MXSFX}: corrDn.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} corrDn.o wrap.o convolve.o edges.o
+
+upConv.${MXSFX}: upConv.o wrap.o convolve.o edges.o
+        ${MEX} ${MFLAGS} upConv.o wrap.o convolve.o edges.o
+
+pointOp.${MXSFX}: pointOp.o
+        ${MEX} ${MFLAGS} pointOp.o
+
+histo.${MXSFX}: histo.o
+        ${MEX} ${MFLAGS} histo.o
+
+range2.${MXSFX}: range2.o
+        ${MEX} ${MFLAGS} range2.o
+
+convolve.o wrap.o edges.o: convolve.h 
+
+%.o : %.c
+        ${CC} -c ${CFLAGS} $<           
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.c
new file mode 100755
index 0000000..60a11a4
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.c
@@ -0,0 +1,325 @@
+/* 
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;;  File: convolve.c
+;;;  Author: Eero Simoncelli
+;;;  Description: General convolution code for 2D images
+;;;  Creation Date: Spring, 1987.
+;;;  MODIFICATIONS:
+;;;     10/89: approximately optimized the choice of register vars on SPARCS.
+;;;      6/96: Switched array types to double float.
+;;;      2/97: made more robust and readable.  Added STOP arguments.
+;;;      8/97: Bug: when calling internal_reduce with edges in {reflect1,repeat,
+;;;            extend} and an even filter dimension.  Solution: embed the filter
+;;;            in the upper-left corner of a filter with odd Y and X dimensions.
+;;;  ----------------------------------------------------------------
+;;;    Object-Based Vision and Image Understanding System (OBVIUS),
+;;;      Copyright 1988, Vision Science Group,  Media Laboratory,  
+;;;              Massachusetts Institute of Technology.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+*/
+
+#include <stdio.h>
+#include <math.h>
+#include "convolve.h"
+
+/*
+  --------------------------------------------------------------------
+  Correlate FILT with IMAGE, subsampling according to START, STEP, and
+  STOP parameters, with values placed into RESULT array.  RESULT
+  dimensions should be ceil((stop-start)/step).  TEMP should be a
+  pointer to a temporary double array the size of the filter.
+  EDGES is a string specifying how to handle boundaries -- see edges.c.
+  The convolution is done in 9 sections, where the border sections use
+  specially computed edge-handling filters (see edges.c). The origin 
+  of the filter is assumed to be (floor(x_fdim/2), floor(y_fdim/2)).
+------------------------------------------------------------------------ */
+
+/* abstract out the inner product computation */
+#define INPROD(XCNR,YCNR)  \
+        { \
+        sum=0.0; \
+        for (im_pos=YCNR*x_dim+XCNR, filt_pos=0, x_filt_stop=x_fdim; \
+             x_filt_stop<=filt_size; \
+             im_pos+=(x_dim-x_fdim), x_filt_stop+=x_fdim) \
+            for (; \
+                 filt_pos<x_filt_stop; \
+                 filt_pos++, im_pos++) \
+              sum+= image[im_pos]*temp[filt_pos]; \
+        result[res_pos] = sum; \
+        }
+
+int internal_reduce(image, x_dim, y_dim, filt, temp, x_fdim, y_fdim,
+                x_start, x_step, x_stop, y_start, y_step, y_stop,
+                result, edges)
+  register image_type *image, *temp;
+  register int x_fdim, x_dim;
+  register image_type *result;
+  register int x_step, y_step;
+  int x_start, y_start;
+  int x_stop, y_stop;     
+  image_type *filt; 
+  int y_dim, y_fdim;
+  char *edges;
+  { 
+  register double sum;
+  register int filt_pos, im_pos, x_filt_stop;
+  register int x_pos, filt_size = x_fdim*y_fdim;
+  register int y_pos, res_pos;
+  register int y_ctr_stop = y_dim - ((y_fdim==1)?0:y_fdim);
+  register int x_ctr_stop = x_dim - ((x_fdim==1)?0:x_fdim);
+  register int x_res_dim = (x_stop-x_start+x_step-1)/x_step;
+  int x_ctr_start = ((x_fdim==1)?0:1);
+  int y_ctr_start = ((y_fdim==1)?0:1);
+  int x_fmid = x_fdim/2;
+  int y_fmid = y_fdim/2;
+  int base_res_pos;
+  fptr reflect = edge_function(edges);  /* look up edge-handling function */
+
+  if (!reflect) return(-1);
+
+  /* shift start/stop coords to filter upper left hand corner */
+  x_start -= x_fmid;   y_start -=  y_fmid;
+  x_stop -=  x_fmid;   y_stop -=  y_fmid;
+
+  if (x_stop < x_ctr_stop) x_ctr_stop = x_stop;
+  if (y_stop < y_ctr_stop) y_ctr_stop = y_stop;
+
+  for (res_pos=0, y_pos=y_start;              /* TOP ROWS */
+       y_pos<y_ctr_start;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start;                       /* TOP-LEFT CORNER */
+         x_pos<x_ctr_start;
+         x_pos+=x_step, res_pos++)
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-1,temp,REDUCE);
+      INPROD(0,0)
+      }
+
+    (*reflect)(filt,x_fdim,y_fdim,0,y_pos-1,temp,REDUCE);
+    for (;                                    /* TOP EDGE */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(x_pos,0)
+
+    for (;                                    /* TOP-RIGHT CORNER */
+         x_pos<x_stop;
+         x_pos+=x_step, res_pos++) 
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-1,temp,REDUCE);
+      INPROD(x_ctr_stop,0)
+      }
+    } /* end TOP ROWS */   
+
+  y_ctr_start = y_pos;                        /* hold location of top */
+  for (base_res_pos=res_pos, x_pos=x_start;   /* LEFT EDGE */
+       x_pos<x_ctr_start;
+       x_pos+=x_step, base_res_pos++)
+    {
+    (*reflect)(filt,x_fdim,y_fdim,x_pos-1,0,temp,REDUCE);
+    for (y_pos=y_ctr_start, res_pos=base_res_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, res_pos+=x_res_dim)
+      INPROD(0,y_pos)
+    }
+
+  (*reflect)(filt,x_fdim,y_fdim,0,0,temp,REDUCE);
+  for (;                                      /* CENTER */
+       x_pos<x_ctr_stop;
+       x_pos+=x_step, base_res_pos++) 
+    for (y_pos=y_ctr_start, res_pos=base_res_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, res_pos+=x_res_dim)
+      INPROD(x_pos,y_pos)
+
+  for (;                                      /* RIGHT EDGE */
+       x_pos<x_stop;
+       x_pos+=x_step, base_res_pos++)
+    {
+    (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,0,temp,REDUCE);
+    for (y_pos=y_ctr_start, res_pos=base_res_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, res_pos+=x_res_dim)
+      INPROD(x_ctr_stop,y_pos)
+    }
+
+  for (res_pos-=(x_res_dim-1);
+       y_pos<y_stop;                          /* BOTTOM ROWS */
+       y_pos+=y_step) 
+    {
+    for (x_pos=x_start;                       /* BOTTOM-LEFT CORNER */
+         x_pos<x_ctr_start;
+         x_pos+=x_step, res_pos++)
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-y_ctr_stop+1,temp,REDUCE);
+      INPROD(0,y_ctr_stop)
+      }
+
+    (*reflect)(filt,x_fdim,y_fdim,0,y_pos-y_ctr_stop+1,temp,REDUCE);
+    for (;                                    /* BOTTOM EDGE */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(x_pos,y_ctr_stop)
+
+    for (;                                    /* BOTTOM-RIGHT CORNER */
+         x_pos<x_stop;
+         x_pos+=x_step, res_pos++) 
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-y_ctr_stop+1,temp,REDUCE);
+      INPROD(x_ctr_stop,y_ctr_stop)
+      }
+    } /* end BOTTOM */
+  return(0);
+  } /* end of internal_reduce */
+
+
+/*
+  --------------------------------------------------------------------
+  Upsample IMAGE according to START,STEP, and STOP parameters and then
+  convolve with FILT, adding values into RESULT array.  IMAGE
+  dimensions should be ceil((stop-start)/step).  See
+  description of internal_reduce (above).
+
+  WARNING: this subroutine destructively modifies the RESULT array!
+ ------------------------------------------------------------------------ */
+
+/* abstract out the inner product computation */
+#define INPROD2(XCNR,YCNR)  \
+        { \
+        val = image[im_pos]; \
+        for (res_pos=YCNR*x_dim+XCNR, filt_pos=0, x_filt_stop=x_fdim; \
+             x_filt_stop<=filt_size; \
+             res_pos+=(x_dim-x_fdim), x_filt_stop+=x_fdim) \
+            for (; \
+                 filt_pos<x_filt_stop; \
+                 filt_pos++, res_pos++) \
+              result[res_pos] += val*temp[filt_pos]; \
+        }
+
+int internal_expand(image,filt,temp,x_fdim,y_fdim,
+                x_start,x_step,x_stop,y_start,y_step,y_stop,
+                result,x_dim,y_dim,edges)
+  register image_type *result, *temp;
+  register int x_fdim, x_dim;
+  register int x_step, y_step;
+  register image_type *image; 
+  int x_start, y_start;
+  image_type *filt; 
+  int y_fdim, y_dim;
+  char *edges;
+  {
+  register double val;
+  register int filt_pos, res_pos, x_filt_stop;
+  register int x_pos, filt_size = x_fdim*y_fdim;
+  register int y_pos, im_pos;
+  register int x_ctr_stop = x_dim - ((x_fdim==1)?0:x_fdim);
+  int y_ctr_stop = (y_dim - ((y_fdim==1)?0:y_fdim));
+  int x_ctr_start = ((x_fdim==1)?0:1);
+  int y_ctr_start = ((y_fdim==1)?0:1);
+  int x_fmid = x_fdim/2;
+  int y_fmid = y_fdim/2;
+  int base_im_pos, x_im_dim = (x_stop-x_start+x_step-1)/x_step;
+  fptr reflect = edge_function(edges);  /* look up edge-handling function */     
+
+  if (!reflect) return(-1);
+
+  /* shift start/stop coords to filter upper left hand corner */
+  x_start -= x_fmid;   y_start -=  y_fmid;
+  x_stop -=  x_fmid;   y_stop -=  y_fmid;
+
+  if (x_stop < x_ctr_stop) x_ctr_stop = x_stop;
+  if (y_stop < y_ctr_stop) y_ctr_stop = y_stop;
+
+  for (im_pos=0, y_pos=y_start;               /* TOP ROWS */
+       y_pos<y_ctr_start;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start;                       /* TOP-LEFT CORNER */
+         x_pos<x_ctr_start;
+         x_pos+=x_step, im_pos++)
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-1,temp,EXPAND);
+      INPROD2(0,0)
+      }
+
+    (*reflect)(filt,x_fdim,y_fdim,0,y_pos-1,temp,EXPAND);
+    for (;                                    /* TOP EDGE */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(x_pos,0)
+
+    for (;                                    /* TOP-RIGHT CORNER */
+         x_pos<x_stop;
+         x_pos+=x_step, im_pos++) 
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-1,temp,EXPAND);
+      INPROD2(x_ctr_stop,0)
+      }
+    }                                           /* end TOP ROWS */   
+
+  y_ctr_start = y_pos;                        /* hold location of top */
+  for (base_im_pos=im_pos, x_pos=x_start;     /* LEFT EDGE */
+       x_pos<x_ctr_start;
+       x_pos+=x_step, base_im_pos++)
+    {
+    (*reflect)(filt,x_fdim,y_fdim,x_pos-1,0,temp,EXPAND);
+    for (y_pos=y_ctr_start, im_pos=base_im_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, im_pos+=x_im_dim)
+      INPROD2(0,y_pos)
+    }
+
+  (*reflect)(filt,x_fdim,y_fdim,0,0,temp,EXPAND);
+  for (;                                      /* CENTER */
+       x_pos<x_ctr_stop;
+       x_pos+=x_step, base_im_pos++) 
+    for (y_pos=y_ctr_start, im_pos=base_im_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, im_pos+=x_im_dim)
+      INPROD2(x_pos,y_pos)
+
+  for (;                                      /* RIGHT EDGE */
+       x_pos<x_stop;
+       x_pos+=x_step, base_im_pos++)
+    {
+    (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,0,temp,EXPAND);
+    for (y_pos=y_ctr_start, im_pos=base_im_pos;
+         y_pos<y_ctr_stop;
+         y_pos+=y_step, im_pos+=x_im_dim)
+      INPROD2(x_ctr_stop,y_pos)
+    }  
+
+  for (im_pos-=(x_im_dim-1);
+       y_pos<y_stop;                          /* BOTTOM ROWS */
+       y_pos+=y_step) 
+    {
+    for (x_pos=x_start;                       /* BOTTOM-LEFT CORNER */
+         x_pos<x_ctr_start;
+         x_pos+=x_step, im_pos++)
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-1,y_pos-y_ctr_stop+1,temp,EXPAND);
+      INPROD2(0,y_ctr_stop)
+      }
+
+    (*reflect)(filt,x_fdim,y_fdim,0,y_pos-y_ctr_stop+1,temp,EXPAND);
+    for (;                                    /* BOTTOM EDGE */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(x_pos,y_ctr_stop)
+
+    for (;                                    /* BOTTOM-RIGHT CORNER */
+         x_pos<x_stop;
+         x_pos+=x_step, im_pos++) 
+      {
+      (*reflect)(filt,x_fdim,y_fdim,x_pos-x_ctr_stop+1,y_pos-y_ctr_stop+1,temp,EXPAND);
+      INPROD2(x_ctr_stop,y_ctr_stop)
+      }
+    } /* end BOTTOM */
+  return(0);
+  } /* end of internal_expand */
+
+
+/* Local Variables: */
+/* buffer-read-only: t */
+/* End: */
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.h b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.h
new file mode 100755
index 0000000..48d55f7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/convolve.h
@@ -0,0 +1,55 @@
+/* 
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;;  File: convolve.h
+;;;  Author: Simoncelli
+;;;  Description: Header file for convolve.c
+;;;  Creation Date:
+;;;  ----------------------------------------------------------------
+;;;    Object-Based Vision and Image Understanding System (OBVIUS),
+;;;      Copyright 1988, Vision Science Group,  Media Laboratory,  
+;;;              Massachusetts Institute of Technology.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+*/
+
+#include <stdio.h>
+#include <stdlib.h> 
+
+#define ABS(x)    (((x)>=0) ? (x) : (-(x)))
+#define ROOT2 1.4142135623730951
+#define REDUCE 0
+#define EXPAND 1
+#define IS    ==
+#define ISNT  !=
+#define AND &&
+#define OR ||
+
+typedef  int (*fptr)();
+
+typedef struct 
+  {
+  char *name;
+  fptr func;
+  } EDGE_HANDLER;
+
+typedef double image_type;
+
+fptr edge_function(char *edges);
+int internal_reduce(image_type *image, int x_idim, int y_idim, 
+                    image_type *filt, image_type *temp, int x_fdim, int y_fdim,
+                    int x_start, int x_step, int x_stop, 
+                    int y_start, int y_step, int y_stop,
+                    image_type *result, char *edges);
+int internal_expand(image_type *image, 
+                    image_type *filt, image_type *temp, int x_fdim, int y_fdim,
+                    int x_start, int x_step, int x_stop, 
+                    int y_start, int y_step, int y_stop,
+                    image_type *result, int x_rdim, int y_rdim, char *edges);
+int internal_wrap_reduce(image_type *image, int x_idim, int y_idim, 
+                         image_type *filt, int x_fdim, int y_fdim,
+                         int x_start, int x_step, int x_stop, 
+                         int y_start, int y_step, int y_stop,
+                         image_type *result);
+int internal_wrap_expand(image_type *image, image_type *filt, int x_fdim, int y_fdim,
+                         int x_start, int x_step, int x_stop, 
+                         int y_start, int y_step, int y_stop,
+                         image_type *result, int x_rdim, int y_rdim);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/corrDn.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/corrDn.c
new file mode 100755
index 0000000..c74df1f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/corrDn.c
@@ -0,0 +1,145 @@
+/* 
+RES = corrDn(IM, FILT, EDGES, STEP, START, STOP);
+  >>> See corrDn.m for documentation <<<
+  This is a matlab interface to the internal_reduce function. 
+  EPS, 7/96.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  /* Matlab matrices */
+#include <mex.h>
+
+#include "convolve.h"
+
+#define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it))
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+  {
+  double *image,*filt, *temp, *result;
+  int x_fdim, y_fdim, x_idim, y_idim;
+  int x_rdim, y_rdim;
+  int x_start = 1;
+  int x_step = 1;
+  int y_start = 1;
+  int y_step = 1;
+  int x_stop, y_stop;
+  mxArray *arg;
+  double *mxMat;
+  char edges[15] = "reflect1";
+  
+  if (nrhs<2) mexErrMsgTxt("requres at least 2 args.");
+
+  /* ARG 1: IMAGE  */
+  arg = prhs[0];
+  if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a non-sparse double float matrix.");
+  image = mxGetPr(arg);
+  x_idim = (int) mxGetM(arg); /* X is inner index! */
+  y_idim = (int) mxGetN(arg);
+
+  /* ARG 2: FILTER */
+  arg = prhs[1];
+  if notDblMtx(arg) mexErrMsgTxt("FILTER arg must be non-sparse double float matrix.");
+  filt = mxGetPr(arg);
+  x_fdim = (int) mxGetM(arg); 
+  y_fdim = (int) mxGetN(arg);
+
+  if ((x_fdim > x_idim) || (y_fdim > y_idim))
+    {
+    mexPrintf("Filter: [%d %d], Image: [%d %d]\n",x_fdim,y_fdim,x_idim,y_idim);
+    mexErrMsgTxt("FILTER dimensions larger than IMAGE dimensions.");
+    }
+
+  /* ARG 3 (optional): EDGES */
+  if (nrhs>2) 
+      {
+      if (!mxIsChar(prhs[2]))
+        mexErrMsgTxt("EDGES arg must be a string.");
+      mxGetString(prhs[2],edges,15);
+      }
+
+  /* ARG 4 (optional): STEP */
+  if (nrhs>3)
+      {
+      arg = prhs[3];
+      if notDblMtx(arg) mexErrMsgTxt("STEP arg must be a double float matrix.");
+      if (mxGetM(arg) * mxGetN(arg) != 2)
+         mexErrMsgTxt("STEP arg must contain two elements.");
+      mxMat = mxGetPr(arg);
+      x_step = (int) mxMat[0];
+      y_step = (int) mxMat[1];
+      if ((x_step<1) || (y_step<1))
+         mexErrMsgTxt("STEP values must be greater than zero.");
+      }
+
+  /* ARG 5 (optional): START */
+  if (nrhs>4)
+      {
+      arg = prhs[4];
+      if notDblMtx(arg) mexErrMsgTxt("START arg must be a double float matrix.");
+      if (mxGetM(arg) * mxGetN(arg) != 2)
+        mexErrMsgTxt("START arg must contain two elements.");
+      mxMat = mxGetPr(arg);
+      x_start = (int) mxMat[0];
+      y_start = (int) mxMat[1];
+      if ((x_start<1) || (x_start>x_idim) ||
+          (y_start<1) || (y_start>y_idim))
+         mexErrMsgTxt("START values must lie between 1 and the image dimensions.");
+      }
+  x_start--;  /* convert from Matlab to standard C indexes */
+  y_start--;
+
+  /* ARG 6 (optional): STOP */
+  if (nrhs>5)
+      {
+      if notDblMtx(prhs[5]) mexErrMsgTxt("STOP arg must be double float matrix.");
+      if (mxGetM(prhs[5]) * mxGetN(prhs[5]) != 2)
+         mexErrMsgTxt("STOP arg must contain two elements.");
+      mxMat = mxGetPr(prhs[5]);
+      x_stop = (int) mxMat[0];
+      y_stop = (int) mxMat[1];
+      if ((x_stop<x_start) || (x_stop>x_idim) ||
+          (y_stop<y_start) || (y_stop>y_idim))
+         mexErrMsgTxt("STOP values must lie between START and the image dimensions.");
+      }
+  else
+      {
+      x_stop = x_idim;
+      y_stop = y_idim;
+      }
+          
+  x_rdim = (x_stop-x_start+x_step-1) / x_step;
+  y_rdim = (y_stop-y_start+y_step-1) / y_step;
+  
+  /*  mxFreeMatrix(plhs[0]); */
+  plhs[0] = (mxArray *) mxCreateDoubleMatrix(x_rdim,y_rdim,mxREAL);
+  if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix");
+  result = mxGetPr(plhs[0]);
+
+  temp = mxCalloc(x_fdim*y_fdim, sizeof(double));
+  if (temp == NULL)
+    mexErrMsgTxt("Cannot allocate necessary temporary space");
+
+  /*
+    printf("i(%d, %d), f(%d, %d), r(%d, %d), X(%d, %d, %d), Y(%d, %d, %d), %s\n",
+         x_idim,y_idim,x_fdim,y_fdim,x_rdim,y_rdim,
+         x_start,x_step,x_stop,y_start,y_step,y_stop,edges);
+         */
+
+  if (strcmp(edges,"circular") == 0)
+        internal_wrap_reduce(image, x_idim, y_idim, filt, x_fdim, y_fdim,
+                             x_start, x_step, x_stop, y_start, y_step, y_stop,
+                             result);
+  else internal_reduce(image, x_idim, y_idim, filt, temp, x_fdim, y_fdim,
+                       x_start, x_step, x_stop, y_start, y_step, y_stop,
+                       result, edges);
+
+  mxFree((char *) temp);
+  return;
+  } 
+
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges-orig.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges-orig.c
new file mode 100755
index 0000000..1f6a98b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges-orig.c
@@ -0,0 +1,494 @@
+/* 
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;;  File: edges.c
+;;;  Author: Eero Simoncelli
+;;;  Description: Boundary handling routines for use with convolve.c
+;;;  Creation Date: Spring 1987.
+;;;  MODIFIED, 6/96, to operate on double float arrays.
+;;;  MODIFIED by dgp, 4/1/97, to support THINK C.
+;;;  ----------------------------------------------------------------
+;;;    Object-Based Vision and Image Understanding System (OBVIUS),
+;;;      Copyright 1988, Vision Science Group,  Media Laboratory,  
+;;;              Massachusetts Institute of Technology.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+*/
+
+/* 
+This file contains functions which determine how edges are to be
+handled when performing convolutions of images with linear filters.
+Any edge handling function which is local and linear may be defined,
+except (unfortunately) constants cannot be added.  So to treat the
+edges as if the image is surrounded by a gray field, you must paste it
+into a gray image, convolve, and crop it out...
+The main convolution function is called internal_filter and is defined
+in the file convolve.c.  The idea is that the convolution function
+calls the edge handling function which computes a new filter based on
+the old filter and the distance to the edge of the image.  For
+example, reflection is done by reflecting the filter through the
+appropriate axis and summing.  Currently defined functions are listed
+below.  
+*/
+
+/*
+#define DEBUG
+*/
+
+#include <stdio.h>
+#include <math.h>
+#include <string.h>
+#include "convolve.h"
+
+#define sgn(a)  ( ((a)>0)?1:(((a)<0)?-1:0) )
+#define clip(a,mn,mx)  ( ((a)<(mn))?(mn):(((a)>=(mx))?(mx-1):(a)) )
+
+int reflect1(), reflect2(), repeat(), zero(), Extend(), nocompute();
+int ereflect(), predict();
+
+/* Lookup table matching a descriptive string to the edge-handling function */
+#if !THINK_C
+        static EDGE_HANDLER edge_foos[] =
+          {
+            { "dont-compute", nocompute }, /* zero output for filter touching edge */
+            { "zero",     zero     },   /* zero outside of image */
+            { "repeat",   repeat   },   /* repeat edge pixel */
+            { "reflect1", reflect1 },   /* reflect about edge pixels  */
+            { "reflect2", reflect2 },   /* reflect image, including edge pixels  */
+            { "extend",   Extend   },   /* extend (reflect & invert) */
+            { "predict",  predict  },   /* predict based on portion covered by filt */
+            { "ereflect", ereflect },   /* orthogonal QMF reflection */
+          };
+#else
+        /*
+        This is really stupid, but THINK C won't allow initialization of static variables in
+        a code resource with string addresses. So we do it this way.
+        The 68K code for a MATLAB 4 MEX file can only be created by THINK C.
+        However, for MATLAB 5, we'll be able to use Metrowerks CodeWarrior for both 68K and PPC, so this
+        cludge can be dropped when we drop support for MATLAB 4.
+        Denis Pelli, 4/1/97. 
+        */
+        static EDGE_HANDLER edge_foos[8];
+
+        void InitializeTable(EDGE_HANDLER edge_foos[])
+        {
+                static int i=0;
+                
+                if(i>0) return;
+                edge_foos[i].name="dont-compute";
+                edge_foos[i++].func=nocompute;
+                edge_foos[i].name="zero";
+                edge_foos[i++].func=zero;
+                edge_foos[i].name="repeat";
+                edge_foos[i++].func=repeat;
+                edge_foos[i].name="reflect1";
+                edge_foos[i++].func=reflect1;
+                edge_foos[i].name="reflect2";
+                edge_foos[i++].func=reflect2;
+                edge_foos[i].name="extend";
+                edge_foos[i++].func=Extend;
+                edge_foos[i].name="predict";
+                edge_foos[i++].func=predict;
+                edge_foos[i].name="ereflect";
+                edge_foos[i++].func=ereflect;
+        }
+#endif
+
+/*
+Function looks up an edge handler id string in the structure above, and
+returns the associated function 
+*/
+fptr edge_function(char *edges)
+  {
+  int i;
+
+#if THINK_C
+  InitializeTable(edge_foos);
+#endif
+  for (i = 0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++)
+    if (strcmp(edges,edge_foos[i].name) == 0)
+      return(edge_foos[i].func);
+  printf("Error: '%s' is not the name of a valid edge-handler!\n",edges);
+  for (i=0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++)
+      {
+      if (i==0) printf("  Options are: ");
+      else printf(", ");
+      printf("%s",edge_foos[i].name);
+      }
+  printf("\n");
+  return(0);
+  }
+
+/* 
+---------------- EDGE HANDLER ARGUMENTS ------------------------
+filt - array of filter taps.
+x_dim, y_dim - x and y dimensions of filt.
+x_pos - position of filter relative to the horizontal image edges. Negative
+       values indicate left edge, positive indicate right edge.  Zero 
+       indicates that the filter is not touching either edge.  An absolute
+       value of 1 indicates that the edge tap of the filter is over the 
+       edge pixel of the image.
+y_pos - analogous to x_pos.
+result - array where the resulting filter will go.  The edge
+       of this filter will be aligned with the image for application...
+f_or_e - equal to one of the two constants EXPAND or FILTER.
+-------------------------------------------------------------------- 
+*/ 
+
+
+/* --------------------------------------------------------------------
+nocompute() - Return zero for values where filter hangs over the edge.
+*/
+
+int nocompute(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int i;
+  register int size = x_dim*y_dim;
+
+  if ( (x_pos>1) OR (x_pos<-1) OR (y_pos>1) OR (y_pos<-1) )
+    for (i=0; i<size; i++)  result[i] = 0.0;
+  else
+    for (i=0; i<size; i++)  result[i] = filt[i];
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+zero() - Zero outside of image.  Discontinuous, but adds zero energy. */
+
+int zero(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  int filt_sz = x_dim*y_dim;
+  int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_res=y_start;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    if ((y_res >= 0) AND (y_res < filt_sz))
+      for (x_filt=y_filt, x_res=x_start;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        if ((x_res >= 0) AND (x_res < x_dim))
+          result[y_res+x_res] = filt[x_filt];
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+repeat() - repeat edge pixel.  Continuous, but content is usually
+different from image.  
+*/
+
+int repeat(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  int filt_sz = x_dim*y_dim;
+  int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_res=y_start;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    for (x_filt=y_filt, x_res=x_start;
+         x_filt<y_filt+x_dim;
+         x_filt++, x_res++)
+      result[((y_res>=0)?((y_res<filt_sz)?y_res:(filt_sz-x_dim)):0) 
+             + ((x_res>=0)?((x_res<x_dim)?x_res:(x_dim-1)):0)]      
+        += filt[x_filt];
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+reflect2() - "Normal" image reflection.  The edge pixel is repeated,
+then the next pixel, etc.  Continuous, attempting to maintain
+"similar" content, but discontinuous first derivative.
+*/
+
+int reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int y_filt,x_filt, y_edge,x_edge;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; 
+  int filt_sz = x_dim*y_dim;
+  int x_edge_dist = (x_pos>0)?(x_pos-x_dim-1):(x_pos+1);
+  int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim-1):(y_pos+1));
+  int i;
+
+  #ifdef DEBUG
+    printf("(%d,%d)  ",y_pos,x_pos);
+    if (x_pos==0) printf("\n");
+  #endif
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_edge=y_edge_dist;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_edge+=x_dim)
+      {
+      if (y_edge IS 0) y_edge+=x_dim;
+      for (x_filt=y_filt, x_edge=x_edge_dist;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_edge++)
+          {
+          if (x_edge IS 0) x_edge++;
+          result[ABS(y_base-ABS(y_edge)+x_dim) + ABS(x_base-ABS(x_edge)+1)]
+            += filt[x_filt];
+          }
+      }
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+reflect1() - Reflection through the edge pixels.  This is the right thing
+to do if you are subsampling by 2, since it maintains parity (even 
+pixels positions remain even, odd ones remain odd). (note: procedure differs 
+depending on f_or_e parameter).  */      
+
+int reflect1(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  int filt_sz = x_dim*y_dim;
+  register int x_start = 0, y_start = 0, x_stop = x_dim, y_stop = filt_sz;
+  register int y_filt,x_filt, y_edge,x_edge;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; 
+  int x_edge_dist = (x_pos>0)?(x_pos-x_dim):((x_pos<0)?(x_pos+1):0);
+  int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim):((y_pos<0)?(y_pos+1):0));
+  int i;
+  int mx_pos = (x_dim/2)+1;
+  int my_pos = (y_dim/2)+1;
+
+  #ifdef DEBUG
+    printf("(%d,%d)  ",y_pos,x_pos);
+    if (x_pos==0) printf("\n");
+  #endif
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  /* if EXPAND and filter is centered on image edge, do not reflect */
+  if (f_or_e IS EXPAND)
+      {
+      if (x_pos IS mx_pos) x_stop = (x_dim+1)/2;
+      else if (x_pos IS -mx_pos) { x_start = x_dim/2; x_edge_dist = 0; }
+
+      if (y_pos IS my_pos) y_stop = x_dim*((y_dim+1)/2);
+      else if (y_pos IS -my_pos) { y_start = x_dim*(y_dim/2); y_edge_dist = 0;}
+      }
+
+  /* reflect at boundary of image */
+  for (y_filt=y_start, y_edge=y_edge_dist;
+       y_filt<y_stop;
+       y_filt+=x_dim, y_edge+=x_dim)
+    for (x_filt=y_filt+x_start, x_edge=x_edge_dist;
+         x_filt<y_filt+x_stop;
+         x_filt++, x_edge++)
+        result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))]
+          += filt[x_filt];
+
+  /* if EXPAND and filter is not centered on image edge, mult edge by 2 */
+    if (f_or_e IS EXPAND)
+      {
+      if ( (ABS(x_pos) ISNT mx_pos) AND (x_pos ISNT 0) )
+        for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim)
+          result[y_filt] += result[y_filt];
+      if ( (ABS(y_pos) ISNT my_pos) AND (y_pos ISNT 0) )
+        for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++)
+          result[x_filt] += result[x_filt];
+      }
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+Extend() - Extend image by reflecting and inverting about edge pixel
+value.  Maintains continuity in intensity AND first derivative (but
+not higher derivs).
+*/
+
+int Extend(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  int filt_sz = x_dim*y_dim;
+  register int x_start = 0, y_start = 0, x_stop = x_dim, y_stop = filt_sz;
+  register int y_filt,x_filt, y_edge,x_edge;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = (y_pos>0)?(x_dim*(y_dim-1)):0; 
+  int x_edge_dist = (x_pos>0)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0);
+  int y_edge_dist = x_dim * ((y_pos>0)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0));
+  int i;
+  int mx_pos = (x_dim/2)+1;
+  int my_pos = (y_dim/2)+1;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  /* if EXPAND and filter is centered on image edge, do not reflect */
+  if (f_or_e IS EXPAND)
+      {
+      if (x_pos IS mx_pos) x_stop = (x_dim+1)/2;
+      else if (x_pos IS -mx_pos) { x_start = x_dim/2; x_edge_dist = 0; }
+
+      if (y_pos IS my_pos) y_stop = x_dim*((y_dim+1)/2);
+      else if (y_pos IS -my_pos) { y_start = x_dim*(y_dim/2); y_edge_dist = 0;}
+      }
+
+  /* reflect at boundary of image */
+  for (y_filt=y_start, y_edge=y_edge_dist;
+       y_filt<y_stop;
+       y_filt+=x_dim, y_edge+=x_dim)
+    for (x_filt=y_filt+x_start, x_edge=x_edge_dist;
+         x_filt<y_filt+x_stop;
+         x_filt++, x_edge++)
+      if (((!y_base AND (sgn(y_edge) IS -1)) /* y overhanging */
+           OR
+           (y_base AND (sgn(y_edge) IS 1)))
+          ISNT                               /* XOR */
+          ((!x_base AND (sgn(x_edge) IS -1)) /* x overhanging */
+           OR
+           (x_base AND (sgn(x_edge) IS 1))))
+          {
+          result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))]
+            -= filt[x_filt];
+          result[clip(y_base+y_edge,0,y_dim) + clip(x_base+x_edge,0,x_dim)]
+            += filt[x_filt] + filt[x_filt];
+          }
+      else result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))]
+          += filt[x_filt];
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+predict() - Simple prediction.  Like zero, but multiplies the result
+by the reciprocal of the percentage of filter being used.  (i.e. if
+50% of the filter is hanging over the edge of the image, multiply the
+taps being used by 2).  */
+
+int predict(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  register double taps_used = 0.0; /* int *** */
+  register double fraction = 0.0;
+  int filt_sz = x_dim*y_dim;
+  int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_res=y_start;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    if ((y_res >= 0) AND (y_res < filt_sz))
+      for (x_filt=y_filt, x_res=x_start;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        if ((x_res >= 0) AND (x_res < x_dim))
+          {
+            result[y_res+x_res] = filt[x_filt];
+            taps_used += ABS(filt[x_filt]);
+          }
+  printf("TU: %f\n",taps_used);
+  if (f_or_e IS FILTER)
+      {
+      /* fraction = ( (double) filt_sz ) / ( (double) taps_used ); */
+      for (i=0; i<filt_sz; i++) fraction += ABS(filt[i]);
+      fraction = ( fraction / taps_used );
+      for (i=0; i<filt_sz; i++) result[i] *= fraction;
+      }
+  return(0);
+  }
+
+
+/* --------------------------------------------------------------------
+Reflect, multiplying tap of filter which is at the edge of the image
+by root 2.  This maintains orthogonality of odd-length linear-phase
+QMF filters, but it is not useful for most applications, since it
+alters the DC level.  */
+
+int ereflect(filt,x_dim,y_dim,x_pos,y_pos,result,f_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, f_or_e;
+  {
+  register int y_filt,x_filt, y_edge,x_edge;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ( (y_pos>0)?(y_dim-1):0 ); 
+  int filt_sz = x_dim*y_dim;
+  int x_edge_dist = (x_pos>1)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0);
+  int y_edge_dist = x_dim * ( (y_pos>1)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0) );
+  int i;
+  double norm,onorm;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  /* reflect at boundary */       
+  for (y_filt=0, y_edge=y_edge_dist;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_edge+=x_dim)
+    for (x_filt=y_filt, x_edge=x_edge_dist;
+         x_filt<y_filt+x_dim;
+         x_filt++, x_edge++)
+      result[ABS(y_base-ABS(y_edge)) + ABS(x_base-ABS(x_edge))]
+        += filt[x_filt];
+
+  /* now multiply edge by root 2 */
+  if (x_pos ISNT 0) 
+    for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim)
+      result[y_filt] *= ROOT2;
+  if (y_pos ISNT 0) 
+    for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++)
+      result[x_filt] *= ROOT2;
+
+  /* now normalize to norm of original filter */
+  for (norm=0.0,i=0; i<filt_sz; i++)
+    norm += (result[i]*result[i]);
+  norm=sqrt(norm);
+
+  for (onorm=0.0,i=0; i<filt_sz; i++)
+    onorm += (filt[i]*filt[i]);
+  onorm = sqrt(onorm);
+
+  norm = norm/onorm;
+  for (i=0; i<filt_sz; i++)
+    result[i] /= norm;
+  return(0);
+  }
+
+
+/* ------- printout stuff for testing ------------------------------
+  printf("Xpos: %d, Ypos: %d", x_pos, y_pos);
+    for (y_filt=0; y_filt<y_dim; y_filt++)
+      {
+      printf("\n");
+      for (x_filt=0; x_filt<x_dim; x_filt++)
+        printf("%6.1f", result[y_filt*x_dim+x_filt]);
+      }
+  printf("\n");
+*/
+
+
+
+/* Local Variables: */
+/* buffer-read-only: t */
+/* End: */
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges.c
new file mode 100755
index 0000000..98b377d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/edges.c
@@ -0,0 +1,647 @@
+/* 
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;;  File: edges.c
+;;;  Author: Eero Simoncelli
+;;;  Description: Boundary handling routines for use with convolve.c
+;;;  Creation Date: Spring 1987.
+;;;  MODIFIED, 6/96, to operate on double float arrays.
+;;;  MODIFIED by dgp, 4/1/97, to support THINK C.
+;;;  MODIFIED, 8/97: reflect1, reflect2, repeat, extend upgraded to 
+;;;       work properly for non-symmetric filters.  Added qreflect2 to handle
+;;;       even-length QMF's which broke under the reflect2 modification.
+;;;  ----------------------------------------------------------------
+;;;    Object-Based Vision and Image Understanding System (OBVIUS),
+;;;      Copyright 1988, Vision Science Group,  Media Laboratory,  
+;;;              Massachusetts Institute of Technology.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+*/
+
+/* This file contains functions which determine how edges are to be
+handled when performing convolutions of images with linear filters.
+Any edge handling function which is local and linear may be defined,
+except (unfortunately) constants cannot be added.  So to treat the
+edges as if the image is surrounded by a gray field, you must paste it
+into a gray image, convolve, and crop it out...  The main convolution
+functions are called internal_reduce and internal_expand and are
+defined in the file convolve.c.  The idea is that the convolution
+function calls the edge handling function which computes a new filter
+based on the old filter and the distance to the edge of the image.
+For example, reflection is done by reflecting the filter through the
+appropriate axis and summing.  Currently defined functions are listed
+below.
+*/
+
+
+#include <stdio.h>
+#include <math.h>
+#include <string.h>
+#include "convolve.h"
+
+#define sgn(a)  ( ((a)>0)?1:(((a)<0)?-1:0) )
+#define clip(a,mn,mx)  ( ((a)<(mn))?(mn):(((a)>=(mx))?(mx-1):(a)) )
+
+int reflect1(), reflect2(), qreflect2(), repeat(), zero(), Extend(), nocompute();
+int ereflect(), predict();
+
+/* Lookup table matching a descriptive string to the edge-handling function */
+#if !THINK_C
+        static EDGE_HANDLER edge_foos[] =
+          {
+            { "dont-compute", nocompute }, /* zero output for filter touching edge */
+            { "zero",     zero     },   /* zero outside of image */
+            { "repeat",   repeat   },   /* repeat edge pixel */
+            { "reflect1", reflect1 },   /* reflect about edge pixels  */
+            { "reflect2", reflect2 },   /* reflect image, including edge pixels  */
+            { "qreflect2", qreflect2 },   /* reflect image, including edge pixels
+                                             for even-length QMF decompositions */
+            { "extend",   Extend   },   /* extend (reflect & invert) */
+            { "ereflect", ereflect },   /* orthogonal QMF reflection */
+          };
+#else
+        /*
+        This is really stupid, but THINK C won't allow initialization of static variables in
+        a code resource with string addresses. So we do it this way.
+        The 68K code for a MATLAB 4 MEX file can only be created by THINK C.
+        However, for MATLAB 5, we'll be able to use Metrowerks CodeWarrior for both 68K and PPC, so this
+        cludge can be dropped when we drop support for MATLAB 4.
+        Denis Pelli, 4/1/97. 
+        */
+        static EDGE_HANDLER edge_foos[8];
+
+        void InitializeTable(EDGE_HANDLER edge_foos[])
+        {
+                static int i=0;
+                
+                if(i>0) return;
+                edge_foos[i].name="dont-compute";
+                edge_foos[i++].func=nocompute;
+                edge_foos[i].name="zero";
+                edge_foos[i++].func=zero;
+                edge_foos[i].name="repeat";
+                edge_foos[i++].func=repeat;
+                edge_foos[i].name="reflect1";
+                edge_foos[i++].func=reflect1;
+                edge_foos[i].name="reflect2";
+                edge_foos[i++].func=reflect2;
+                edge_foos[i].name="qreflect2";
+                edge_foos[i++].func=qreflect2;
+                edge_foos[i].name="extend";
+                edge_foos[i++].func=Extend;
+                edge_foos[i].name="ereflect";
+                edge_foos[i++].func=ereflect;
+        }
+#endif
+
+/*
+Function looks up an edge handler id string in the structure above, and
+returns the associated function 
+*/
+fptr edge_function(char *edges)
+  {
+  int i;
+
+#if THINK_C
+  InitializeTable(edge_foos);
+#endif
+  for (i = 0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++)
+    if (strcmp(edges,edge_foos[i].name) IS 0)
+      return(edge_foos[i].func);
+  printf("Error: '%s' is not the name of a valid edge-handler!\n",edges);
+  for (i=0; i<sizeof(edge_foos)/sizeof(EDGE_HANDLER); i++)
+      {
+      if (i IS 0) printf("  Options are: ");
+      else printf(", ");
+      printf("%s",edge_foos[i].name);
+      }
+  printf("\n");
+  return(0);
+  }
+
+/* 
+---------------- EDGE HANDLER ARGUMENTS ------------------------
+filt - array of filter taps.
+x_dim, y_dim - x and y dimensions of filt.
+x_pos - position of filter relative to the horizontal image edges. Negative
+       values indicate left edge, positive indicate right edge.  Zero 
+       indicates that the filter is not touching either edge.  An absolute
+       value of 1 indicates that the edge tap of the filter is over the 
+       edge pixel of the image.
+y_pos - analogous to x_pos.
+result - array where the resulting filter will go.  The edge
+       of this filter will be aligned with the image for application...
+r_or_e - equal to one of the two constants EXPAND or REDUCE.
+-------------------------------------------------------------------- 
+*/ 
+
+
+/* --------------------------------------------------------------------
+nocompute() - Return zero for values where filter hangs over the edge.
+*/
+
+int nocompute(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  register int i;
+  register int size = x_dim*y_dim;
+
+  if ( (x_pos>1) OR (x_pos<-1) OR (y_pos>1) OR (y_pos<-1) )
+    for (i=0; i<size; i++)  result[i] = 0.0;
+  else
+    for (i=0; i<size; i++)  result[i] = filt[i];
+
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+zero() - Zero outside of image.  Discontinuous, but adds zero energy. */
+
+int zero(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  int filt_sz = x_dim*y_dim;
+  int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_res=y_start;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    if ((y_res >= 0) AND (y_res < filt_sz))
+      for (x_filt=y_filt, x_res=x_start;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        if ((x_res >= 0) AND (x_res < x_dim))
+          result[y_res+x_res] = filt[x_filt];
+  return(0);
+  }
+
+
+/* --------------------------------------------------------------------
+reflect1() - Reflection through the edge pixels.  Continuous, but
+discontinuous first derivative.  This is the right thing to do if you
+are subsampling by 2, since it maintains parity (even pixels positions
+remain even, odd ones remain odd).
+*/       
+
+int reflect1(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  int filt_sz = x_dim*y_dim;
+  register int y_filt,x_filt, y_res, x_res;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); 
+  int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0);
+  int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+  int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2);
+  int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2));
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  if (r_or_e IS REDUCE)
+    for (y_filt=0, y_res=y_overhang-y_base;
+         y_filt<filt_sz;
+         y_filt+=x_dim, y_res+=x_dim)
+      for (x_filt=y_filt, x_res=x_overhang-x_base;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        result[ABS(y_base-ABS(y_res)) + ABS(x_base-ABS(x_res))]
+          += filt[x_filt];
+  else {
+      y_overhang = ABS(y_overhang); 
+      x_overhang = ABS(x_overhang);
+      for (y_res=y_base, y_filt = y_base-y_overhang;
+           y_filt > y_base-filt_sz;
+           y_filt-=x_dim, y_res-=x_dim)
+          {
+          for (x_res=x_base, x_filt=x_base-x_overhang;
+               x_filt > x_base-x_dim;
+               x_res--, x_filt--)
+            result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+          if ((x_overhang ISNT mx_pos) AND (x_pos ISNT 0))
+            for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang;
+                 x_filt > x_base-x_dim;
+                 x_res--, x_filt--)
+              result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+          }
+      if ((y_overhang ISNT my_pos) AND (y_pos ISNT 0))
+        for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang;
+             y_filt > y_base-filt_sz;
+             y_filt-=x_dim, y_res-=x_dim)
+            {
+            for (x_res=x_base, x_filt=x_base-x_overhang;
+                 x_filt > x_base-x_dim;
+                 x_res--, x_filt--)
+              result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+            if  ((x_overhang ISNT mx_pos) AND (x_pos ISNT 0))
+              for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang;
+                   x_filt > x_base-x_dim;
+                   x_res--, x_filt--)
+                result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+            }
+      }
+
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+reflect2() - Reflect image at boundary.  The edge pixel is repeated,
+then the next pixel, etc.  Continuous, but discontinuous first
+derivative.
+*/
+
+int reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  int filt_sz = x_dim*y_dim;
+  register int y_filt,x_filt, y_res, x_res;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); 
+  int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0);
+  int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+  int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2);
+  int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2));
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  if (r_or_e IS REDUCE)
+    for (y_filt=0, y_res = (y_overhang-y_base) - ((y_pos>0)?x_dim:0);
+         y_filt<filt_sz;
+         y_filt+=x_dim, y_res+=x_dim)
+        {
+        if (y_res IS 0) y_res+=x_dim;
+        for (x_filt=y_filt, x_res = (x_overhang-x_base) - ((x_pos>0)?1:0);
+             x_filt<y_filt+x_dim;
+             x_filt++, x_res++)
+            {
+            if (x_res IS 0) x_res++;
+            result[ABS(y_base-ABS(y_res)+x_dim) + ABS(x_base-ABS(x_res)+1)]
+              += filt[x_filt];
+            }
+        }
+  else {
+      y_overhang = ABS(y_overhang); 
+      x_overhang = ABS(x_overhang);
+      for (y_res=y_base, y_filt = y_base-y_overhang;
+           y_filt > y_base-filt_sz;
+           y_filt-=x_dim, y_res-=x_dim)
+          {
+          for (x_res=x_base, x_filt=x_base-x_overhang;
+               x_filt > x_base-x_dim;
+               x_res--, x_filt--)
+            result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+          if (x_pos ISNT 0)
+            for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1;
+                 x_filt > x_base-x_dim;
+                 x_res--, x_filt--)
+              result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+          }
+       if (y_pos ISNT 0)
+         for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang-x_dim;
+              y_filt > y_base-filt_sz;
+              y_filt-=x_dim, y_res-=x_dim)
+             {
+             for (x_res=x_base, x_filt=x_base-x_overhang;
+                  x_filt > x_base-x_dim;
+                  x_res--, x_filt--)
+               result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+             if (x_pos ISNT 0)
+               for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1;
+                    x_filt > x_base-x_dim;
+                    x_res--, x_filt--)
+                 result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+             }
+      }
+
+  return(0);
+  }
+
+
+/* --------------------------------------------------------------------
+qreflect2() - Modified version of reflect2 that  works properly for 
+even-length QMF filters.
+*/
+
+int qreflect2(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  double *filt, *result;
+  int x_dim, y_dim, x_pos, y_pos, r_or_e;
+  {
+  reflect2(filt,x_dim,y_dim,x_pos,y_pos,result,0);
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+repeat() - repeat edge pixel.  Continuous, with discontinuous first
+derivative.
+*/
+
+int repeat(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res, y_tmp, x_tmp;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); 
+  int x_overhang = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int filt_sz = x_dim*y_dim;
+  int mx_pos = (x_dim/2);
+  int my_pos = x_dim * (y_dim/2);
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  if (r_or_e IS REDUCE)
+    for (y_filt=0, y_res=y_overhang;
+         y_filt<filt_sz;
+         y_filt+=x_dim, y_res+=x_dim)
+      for (x_filt=y_filt, x_res=x_overhang;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        /* Clip the index: */
+        result[((y_res>=0)?((y_res<filt_sz)?y_res:(filt_sz-x_dim)):0) 
+               + ((x_res>=0)?((x_res<x_dim)?x_res:(x_dim-1)):0)]      
+                 += filt[x_filt];
+  else {
+    if ((y_base-y_overhang) ISNT my_pos)
+      for (y_res=y_base, y_filt=y_base-ABS(y_overhang);
+           y_filt > y_base-filt_sz;
+           y_filt-=x_dim, y_res-=x_dim)
+        if ((x_base-x_overhang) ISNT mx_pos)
+          for (x_res=x_base, x_filt=x_base-ABS(x_overhang);
+               x_filt > x_base-x_dim;
+               x_res--, x_filt--)
+            result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+        else  /* ((x_base-x_overhang) IS mx_pos) */
+          for (x_res=x_base, x_filt=x_base-ABS(x_overhang);
+               x_filt > x_base-x_dim;
+               x_filt--, x_res--)
+            for(x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--)
+              result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_tmp)];
+    else /* ((y_base-y_overhang) IS my_pos) */
+      for (y_res=y_base, y_filt=y_base-ABS(y_overhang);
+           y_filt > y_base-filt_sz;
+           y_filt-=x_dim, y_res-=x_dim)
+        for (y_tmp=y_filt; y_tmp > y_base-filt_sz; y_tmp-=x_dim)
+          if  ((x_base-x_overhang) ISNT mx_pos)
+            for (x_res=x_base, x_filt=x_base-ABS(x_overhang);
+                 x_filt > x_base-x_dim;
+                 x_filt--, x_res--)
+              result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_tmp)+ABS(x_filt)];
+          else /* ((x_base-x_overhang) IS mx_pos) */
+            for (x_res=x_base, x_filt=x_base-ABS(x_overhang);
+                 x_filt > x_base-x_dim;
+                 x_filt--, x_res--)
+              for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--)
+                result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_tmp)+ABS(x_tmp)];
+    } /* End, if r_or_e IS EXPAND */
+
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+extend() - Extend image by reflecting and inverting about edge pixel
+value.  Maintains continuity in intensity AND first derivative (but
+not higher derivs).
+*/
+
+int Extend(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  int filt_sz = x_dim*y_dim;
+  register int y_filt,x_filt, y_res,x_res, y_tmp, x_tmp;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); 
+  int x_overhang = (x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0);
+  int y_overhang = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int mx_pos = (x_pos<0)?(x_dim/2):((x_dim-1)/2);
+  int my_pos = x_dim * ((y_pos<0)?(y_dim/2):((y_dim-1)/2));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  /* Modeled on reflect1() */
+  if (r_or_e IS REDUCE)
+    for (y_filt=0, y_res=y_overhang;
+         y_filt<filt_sz;
+         y_filt+=x_dim, y_res+=x_dim)
+      if ((y_res>=0) AND (y_res<filt_sz))
+        for (x_filt=y_filt, x_res=x_overhang;
+             x_filt<y_filt+x_dim;
+             x_filt++, x_res++)
+          if ((x_res>=0) AND (x_res<x_dim))
+            result[y_res+x_res] += filt[x_filt];
+          else
+              {
+              result[y_res+ABS(x_base-ABS(x_res-x_base))] -= filt[x_filt];
+              result[y_res+x_base] += 2*filt[x_filt];
+              }
+      else
+        for (x_filt=y_filt, x_res=x_overhang;
+             x_filt<y_filt+x_dim;
+             x_filt++, x_res++)
+          if ((x_res>=0) AND (x_res<x_dim))
+              {
+              result[ABS(y_base-ABS(y_res-y_base))+x_res] -= filt[x_filt];
+              result[y_base+x_res] += 2*filt[x_filt];
+              }
+          else
+              {
+              result[ABS(y_base-ABS(y_res-y_base))+ABS(x_base-ABS(x_res-x_base))] 
+                -= filt[x_filt];
+              result[y_base+x_base] += 2*filt[x_filt];
+              }
+  else {  /* r_or_e ISNT  REDUCE */
+      y_overhang = ABS(y_overhang); 
+      x_overhang = ABS(x_overhang);
+      for (y_res=y_base, y_filt = y_base-y_overhang;
+           y_filt > y_base-filt_sz;
+           y_filt-=x_dim, y_res-=x_dim)
+          {
+          for (x_res=x_base, x_filt=x_base-x_overhang;
+               x_filt > x_base-x_dim;
+               x_res--, x_filt--)
+            result[ABS(y_res)+ABS(x_res)] += filt[ABS(y_filt)+ABS(x_filt)];
+          if (x_pos ISNT 0)
+            if (x_overhang ISNT mx_pos)
+              for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang;
+                   x_filt > x_base-x_dim;
+                   x_res--, x_filt--)
+                result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)];
+            else /* x_overhang IS mx_pos */
+              for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1;
+                   x_filt > x_base-x_dim;
+                   x_res--, x_filt--)
+                for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--)
+                  result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_filt)+ABS(x_tmp)];
+          }
+       if (y_pos ISNT 0)
+         if (y_overhang ISNT my_pos)
+           for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang;
+                y_filt > y_base-filt_sz;
+                y_filt-=x_dim, y_res-=x_dim)
+               {
+               for (x_res=x_base, x_filt=x_base-x_overhang;
+                    x_filt > x_base-x_dim;
+                    x_res--, x_filt--)
+                 result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)];
+               if ((x_pos ISNT 0) AND (x_overhang ISNT mx_pos))
+                 for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang;
+                      x_filt > x_base-x_dim;
+                      x_res--, x_filt--)
+                   result[ABS(y_res)+ABS(x_res)] -= filt[ABS(y_filt)+ABS(x_filt)];
+               }
+         else /* y_overhang IS my_pos */
+           for (y_res=y_base, y_filt = y_base-2*my_pos+y_overhang-x_dim;
+                y_filt > y_base-filt_sz;
+                y_res-=x_dim, y_filt-=x_dim)
+             for (y_tmp=y_filt; y_tmp > y_base-filt_sz; y_tmp-=x_dim)
+                 {
+                 for (x_res=x_base, x_filt=x_base-x_overhang;
+                      x_filt > x_base-x_dim;
+                      x_res--, x_filt--)
+                   result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_tmp)+ABS(x_filt)];
+                 if ((x_pos ISNT 0) AND (x_overhang IS mx_pos))
+                   for (x_res=x_base, x_filt=x_base-2*mx_pos+x_overhang-1;
+                        x_filt > x_base-x_dim;
+                        x_res--, x_filt--)
+                     for (x_tmp=x_filt; x_tmp > x_base-x_dim; x_tmp--)
+                       result[ABS(y_res)+ABS(x_res)] += 2*filt[ABS(y_tmp)+ABS(x_tmp)];
+                 }
+      }  /* r_or_e ISNT  REDUCE */
+
+  return(0);
+  }
+
+/* --------------------------------------------------------------------
+predict() - Simple prediction.  Like zero, but multiplies the result
+by the reciprocal of the percentage of filter being used.  (i.e. if
+50% of the filter is hanging over the edge of the image, multiply the
+taps being used by 2).  */
+
+int predict(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  register double taps_used = 0.0; /* int *** */
+  register double fraction = 0.0;
+  int filt_sz = x_dim*y_dim;
+  int x_start = ((x_pos>0)?(x_pos-1):((x_pos<0)?(x_pos+1):0));
+  int y_start = x_dim * ((y_pos>0)?(y_pos-1):((y_pos<0)?(y_pos+1):0));
+  int i;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  for (y_filt=0, y_res=y_start;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    if ((y_res >= 0) AND (y_res < filt_sz))
+      for (x_filt=y_filt, x_res=x_start;
+           x_filt<y_filt+x_dim;
+           x_filt++, x_res++)
+        if ((x_res >= 0) AND (x_res < x_dim))
+          {
+            result[y_res+x_res] = filt[x_filt];
+            taps_used += ABS(filt[x_filt]);
+          }
+
+  if (r_or_e IS REDUCE)
+      {
+      /* fraction = ( (double) filt_sz ) / ( (double) taps_used ); */
+      for (i=0; i<filt_sz; i++) fraction += ABS(filt[i]);
+      fraction = ( fraction / taps_used );
+      for (i=0; i<filt_sz; i++) result[i] *= fraction;
+      }
+  return(0);
+  }
+
+
+/* --------------------------------------------------------------------
+Reflect, multiplying tap of filter which is at the edge of the image
+by root 2.  This maintains orthogonality of odd-length linear-phase
+QMF filters, but it is not useful for most applications, since it
+alters the DC level.  */
+
+int ereflect(filt,x_dim,y_dim,x_pos,y_pos,result,r_or_e)
+  register double *filt, *result;
+  register int x_dim;
+  int y_dim, x_pos, y_pos, r_or_e;
+  {
+  register int y_filt,x_filt, y_res,x_res;
+  register int x_base = (x_pos>0)?(x_dim-1):0;
+  register int y_base = x_dim * ((y_pos>0)?(y_dim-1):0); 
+  int filt_sz = x_dim*y_dim;
+  int x_overhang = (x_pos>1)?(x_pos-x_dim):((x_pos<-1)?(x_pos+1):0);
+  int y_overhang = x_dim * ( (y_pos>1)?(y_pos-y_dim):((y_pos<-1)?(y_pos+1):0) );
+  int i;
+  double norm,onorm;
+
+  for (i=0; i<filt_sz; i++) result[i] = 0.0;
+
+  /* reflect at boundary */       
+  for (y_filt=0, y_res=y_overhang;
+       y_filt<filt_sz;
+       y_filt+=x_dim, y_res+=x_dim)
+    for (x_filt=y_filt, x_res=x_overhang;
+         x_filt<y_filt+x_dim;
+         x_filt++, x_res++)
+      result[ABS(y_base-ABS(y_res)) + ABS(x_base-ABS(x_res))]
+        += filt[x_filt];
+
+  /* now multiply edge by root 2 */
+  if (x_pos ISNT 0) 
+    for (y_filt=x_base; y_filt<filt_sz; y_filt+=x_dim)
+      result[y_filt] *= ROOT2;
+  if (y_pos ISNT 0) 
+    for (x_filt=y_base; x_filt<y_base+x_dim; x_filt++)
+      result[x_filt] *= ROOT2;
+
+  /* now normalize to norm of original filter */
+  for (norm=0.0,i=0; i<filt_sz; i++)
+    norm += (result[i]*result[i]);
+  norm=sqrt(norm);
+
+  for (onorm=0.0,i=0; i<filt_sz; i++)
+    onorm += (filt[i]*filt[i]);
+  onorm = sqrt(onorm);
+
+  norm = norm/onorm;
+  for (i=0; i<filt_sz; i++)
+    result[i] /= norm;
+  return(0);
+  }
+
+
+/* ------- printout stuff for testing ------------------------------
+  printf("Xpos: %d, Ypos: %d", x_pos, y_pos);
+    for (y_filt=0; y_filt<y_dim; y_filt++)
+      {
+      printf("\n");
+      for (x_filt=0; x_filt<x_dim; x_filt++)
+        printf("%6.1f", result[y_filt*x_dim+x_filt]);
+      }
+  printf("\n");
+*/
+
+
+
+/* Local Variables: */
+/* buffer-read-only: t */
+/* End: */
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/histo.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/histo.c
new file mode 100755
index 0000000..43a99c7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/histo.c
@@ -0,0 +1,140 @@
+/* 
+[N, X] = histo(MTX, NBINS_OR_BINSIZE, BIN_CENTER)
+  >>> See histo.m for documentation <<<
+  EPS, ported from OBVIUS, 3/97.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  /* Matlab matrices */
+#include <mex.h>
+
+#include <stddef.h>  /* NULL */
+#include <math.h>  /* ceil */
+
+#define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it))
+
+#define PAD 0.49999 /* A hair below 1/2, to avoid roundoff errors */
+#define MAXBINS 20000
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+  {
+  register double temp;
+  register int binnum, i, size;
+  register double *im, binsize;
+  register double origin, *hist, mn, mx, mean;
+  register int nbins;
+  double *bincenters; 
+  mxArray *arg;
+  double *mxMat;
+
+  if (nrhs < 1 ) mexErrMsgTxt("requires at least 1 argument.");
+
+  /* ARG 1: MATRIX  */
+  arg = prhs[0];
+  if notDblMtx(arg) mexErrMsgTxt("MTX arg must be a real non-sparse matrix.");
+  im = mxGetPr(arg);
+  size = (int) mxGetM(arg) * mxGetN(arg);
+
+  /* FIND min, max, mean values of MTX */
+  mn = *im;   mx = *im;  binsize = 0;
+  for (i=1; i<size; i++)
+    {
+      temp = im[i];
+      if (temp < mn)
+        mn = temp;
+      else if (temp > mx)
+        mx = temp;
+      binsize += temp;
+    }
+  mean = binsize / size;
+
+  /* ARG 3: BIN_CENTER */
+  if (nrhs > 2)
+    {
+    arg = prhs[2];
+    if notDblMtx(arg) mexErrMsgTxt("BIN_CENTER arg must be a real scalar.");
+    if (mxGetM(arg) * mxGetN(arg) != 1)
+      mexErrMsgTxt("BIN_CENTER must be a real scalar.");
+    mxMat= mxGetPr(arg);
+    origin = *mxMat;
+    }
+  else
+    origin = mean;
+
+  /* ARG 2: If positive, NBINS.  If negative, -BINSIZE. */
+  if (nrhs > 1)
+    {
+    arg = prhs[1];
+    if notDblMtx(arg) mexErrMsgTxt("NBINS_OR_BINSIZE arg must be a real scalar.");
+    if (mxGetM(arg) * mxGetN(arg) != 1)
+      mexErrMsgTxt("NBINS_OR_BINSIZE must be a real scalar.");
+    mxMat= mxGetPr(arg);
+    binsize = *mxMat;
+    }
+  else
+    {
+    binsize = 101;  /* DEFAULT: 101 bins */
+    }
+
+  /* --------------------------------------------------
+     Adjust origin, binsize, nbins such that
+        mx <= origin + (nbins-1)*binsize + PAD*binsize
+        mn >= origin - PAD*binsize
+     -------------------------------------------------- */
+  if (binsize < 0)              /* user specified BINSIZE */
+      {
+      binsize = -binsize;
+      origin -= binsize * ceil((origin-mn-PAD*binsize)/binsize);
+      nbins = (int) ceil((mx-origin-PAD*binsize)/binsize) + 1;
+      }
+  else                          /* user specified NBINS */
+      {
+      nbins = (int) (binsize + 0.5);    /* round to int */
+      if (nbins == 0)
+        mexErrMsgTxt("NBINS must be greater than zero.");
+      binsize = (mx-mn)/(nbins-1+2*PAD);   /* start with lower bound */
+      i = ceil((origin-mn-binsize/2)/binsize);
+      if ( mn < (origin-i*binsize-PAD*binsize) )
+        binsize = (origin-mn)/(i+PAD);
+      else if ( mx > (origin+(nbins-1-i)*binsize+PAD*binsize) )
+        binsize = (mx-origin)/((nbins-1-i)+PAD);
+      origin -= binsize * ceil((origin-mn-PAD*binsize)/binsize);
+      }
+
+  if (nbins > MAXBINS)
+      {
+      mexPrintf("nbins: %d,  MAXBINS: %d\n",nbins,MAXBINS);
+      mexErrMsgTxt("Number of histo bins has exceeded maximum");
+      }
+
+  /* Allocate hist  and xvals */
+  plhs[0] = (mxArray *) mxCreateDoubleMatrix(1,nbins,mxREAL);
+  if (plhs[0] == NULL) mexErrMsgTxt("Error allocating result matrix");
+  hist = mxGetPr(plhs[0]);
+
+  if (nlhs > 1)
+      {
+      plhs[1] = (mxArray *) mxCreateDoubleMatrix(1,nbins,mxREAL);
+      if (plhs[1] == NULL) mexErrMsgTxt("Error allocating result matrix");
+      bincenters = mxGetPr(plhs[1]);
+      for (i=0, temp=origin; i<nbins; i++, temp+=binsize)
+        bincenters[i] = temp;
+      }
+
+  for (i=0; i<size; i++)
+      {
+      binnum = (int) ((im[i] - origin)/binsize + 0.5);
+      if ((binnum < nbins) && (binnum >= 0))
+        (hist[binnum]) += 1.0;
+      else
+        printf("HISTO warning: value %f outside of range [%f,%f]\n",
+               im[i], origin-0.5*binsize, origin+(nbins-0.5)*binsize);
+      }
+
+  return;
+  }      
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.c
new file mode 100755
index 0000000..8fa1224
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.c
@@ -0,0 +1,52 @@
+/* 
+RES = innerProd(MAT);
+  Computes mat'*mat  
+  Odelia Schwartz, 8/97.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  
+
+#include <stdio.h>
+#include <ctype.h>
+#include <math.h>
+#include <strings.h>
+#include <stdlib.h>
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+{
+   register double *res, *mat, tmp;
+   register int len, wid, i, k, j, jlen, ilen, imat, jmat;
+   mxArray *arg;
+   
+   /* get matrix input argument */
+   /* should be matrix in which num rows >= num columns */
+   arg=prhs[0];                     
+   mat= mxGetPr(arg);
+   len = (int) mxGetM(arg);
+   wid = (int) mxGetN(arg);
+   if ( wid > len )
+     printf("innerProd: Warning: width %d is greater than length %d.\n",wid,len); 
+   plhs[0] = (mxArray *) mxCreateDoubleMatrix(wid,wid,mxREAL);
+   if (plhs[0] == NULL) 
+     mexErrMsgTxt(sprintf("Error allocating %dx%d result matrix",wid,wid));
+   res = mxGetPr(plhs[0]);
+
+   for(i=0, ilen=0; i<wid; i++, ilen+=len)
+     {
+      for(j=i, jlen=ilen; j<wid; j++, jlen+=len)
+         {
+            tmp = 0.0;
+            for(k=0, imat=ilen, jmat=jlen; k<len; k++, imat++, jmat++)
+              tmp += mat[imat]*mat[jmat];
+            res[i*wid+j] = tmp;
+            res[j*wid+i] = tmp;
+         }
+   }
+   return;
+
+}
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.dll b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.dll
new file mode 100755
index 0000000..40ac896
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.dll
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexglx b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexglx
new file mode 100755
index 0000000..749a5b5
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexglx
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexlx b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexlx
new file mode 100755
index 0000000..151b08f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexlx
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexmac b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexmac
new file mode 100755
index 0000000..6e11fcd
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexmac
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexsol b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexsol
new file mode 100755
index 0000000..d761ed8
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/innerProd.mexsol
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/pointOp.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/pointOp.c
new file mode 100755
index 0000000..6ffcb45
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/pointOp.c
@@ -0,0 +1,126 @@
+/* 
+RES = pointOp(IM, LUT, ORIGIN, INCREMENT, WARNINGS)
+  >>> See pointOp.m for documentation <<<
+  EPS, ported from OBVIUS, 7/96.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  /* Matlab matrices */
+#include <mex.h>
+
+#include <stddef.h>  /* NULL */
+
+#define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it))
+
+void internal_pointop();
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+  {
+  double *image, *lut, *res;
+  double origin, increment;
+  int x_dim, y_dim, lx_dim, ly_dim;
+  int warnings = 1;
+  mxArray *arg;
+  double *mxMat;
+
+  if (nrhs < 4 ) mexErrMsgTxt("requres  at least 4 args.");
+
+  /* ARG 1: IMAGE  */
+  arg = prhs[0];
+  if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a real non-sparse matrix.");
+  image = mxGetPr(arg);
+  x_dim = (int) mxGetM(arg); /* X is inner index! */
+  y_dim = (int) mxGetN(arg);
+
+  /* ARG 2: Lookup table */
+  arg = prhs[1];
+  if notDblMtx(arg) mexErrMsgTxt("LUT arg must be a real non-sparse matrix.");
+  lut = mxGetPr(arg);
+  lx_dim = (int) mxGetM(arg); /* X is inner index! */
+  ly_dim = (int) mxGetN(arg);
+  if ( (lx_dim != 1) && (ly_dim != 1) )
+    mexErrMsgTxt("Lookup table must be a row or column vector.");
+
+  /* ARG 3: ORIGIN */
+  arg = prhs[2];
+  if notDblMtx(arg) mexErrMsgTxt("ORIGIN arg must be a real scalar.");
+  if (mxGetM(arg) * mxGetN(arg) != 1)
+     mexErrMsgTxt("ORIGIN arg must be a real scalar.");
+  mxMat = mxGetPr(arg);
+  origin = *mxMat;
+
+  /* ARG 4: INCREMENT */
+  arg = prhs[3];
+  if notDblMtx(arg) mexErrMsgTxt("INCREMENT arg must be a real scalar.");
+  if (mxGetM(arg) * mxGetN(arg) != 1)
+     mexErrMsgTxt("INCREMENT arg must be a real scalar.");
+  mxMat = mxGetPr(arg);
+  increment = *mxMat;
+
+  /* ARG 5: WARNINGS */
+  if (nrhs>4)
+    {
+    arg = prhs[4];
+    if notDblMtx(arg) mexErrMsgTxt("WARINGS arg must be a real scalar.");
+    if (mxGetM(arg) * mxGetN(arg) != 1)
+      mexErrMsgTxt("WARNINGS arg must be a real scalar.");
+    mxMat = mxGetPr(arg);
+    warnings = (int) *mxMat;
+    }
+
+  plhs[0] = (mxArray *)  mxCreateDoubleMatrix(x_dim,y_dim,mxREAL);
+  if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix");
+  res = mxGetPr(plhs[0]);
+      
+  internal_pointop(image, res, x_dim*y_dim, lut, lx_dim*ly_dim, 
+                   origin, increment, warnings);
+  return;
+  }      
+
+
+/* Use linear interpolation on a lookup table.
+   Taken from OBVIUS.  EPS, Spring, 1987.
+ */
+void internal_pointop (im, res, size, lut, lutsize, origin, increment, warnings)
+  register double *im, *res, *lut;
+  register double origin, increment; 
+  register int size, lutsize, warnings;
+  {
+  register int i, index;
+  register double pos;
+  register int l_unwarned = warnings;
+  register int r_unwarned = warnings;
+
+  lutsize = lutsize - 2;        /* Maximum index value */
+  if (increment > 0)
+    for (i=0; i<size; i++)
+        {
+        pos = (im[i] - origin) / increment;
+        index = (int) pos;   /* Floor */
+        if (index < 0)
+            {
+            index = 0;
+            if (l_unwarned)
+                {
+                mexPrintf("Warning: Extrapolating to left of lookup table...\n");
+                l_unwarned = 0;
+                }
+            }
+        else if (index > lutsize)
+            {
+            index = lutsize;
+            if (r_unwarned)
+                {
+                mexPrintf("Warning: Extrapolating to right of lookup table...\n");
+                r_unwarned = 0;
+                }
+            }
+        res[i] = lut[index] + (lut[index+1] - lut[index]) * (pos - index);
+        }
+  else
+    for (i=0; i<size; i++) res[i] = *lut;
+  }
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/range2.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/range2.c
new file mode 100755
index 0000000..b84f4e1
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/range2.c
@@ -0,0 +1,56 @@
+/* 
+[MIN, MAX] = range2(MTX)
+  >>> See range2.m for documentation <<<
+  EPS, 3/97.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  /* Matlab matrices */
+#include <mex.h>
+
+#include <stddef.h>  /* NULL */
+
+#define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it))
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+  {
+  register double temp, mn, mx;
+  register double *mtx;
+  register int i, size;
+  mxArray *arg;
+
+  if (nrhs != 1) mexErrMsgTxt("requires 1 argument.");
+
+  /* ARG 1: MATRIX  */
+  arg = prhs[0];
+  if notDblMtx(arg) mexErrMsgTxt("MTX arg must be a real non-sparse matrix.");
+  mtx = mxGetPr(arg);
+  size = (int) mxGetM(arg) * mxGetN(arg);
+
+  /* FIND min, max values of MTX */
+  mn = *mtx;   mx = *mtx;  
+  for (i=1; i<size; i++)
+      {
+      temp = mtx[i];
+      if (temp < mn)
+        mn = temp;
+      else if (temp > mx)
+        mx = temp;
+      }
+
+  plhs[0] = (mxArray *) mxCreateDoubleMatrix(1,1,mxREAL);
+  if (plhs[0] == NULL) mexErrMsgTxt("Error allocating result matrix");
+  plhs[1] = (mxArray *) mxCreateDoubleMatrix(1,1,mxREAL);
+  if (plhs[1] == NULL) mexErrMsgTxt("Error allocating result matrix");
+  mtx = mxGetPr(plhs[0]);
+  mtx[0] = mn;
+  mtx = mxGetPr(plhs[1]);
+  mtx[0] = mx;
+
+  return;
+  }      
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/upConv.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/upConv.c
new file mode 100755
index 0000000..3708f8a
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/upConv.c
@@ -0,0 +1,195 @@
+/* 
+RES = upConv(IM, FILT, EDGES, STEP, START, STOP, RES);
+  >>> See upConv.m for documentation <<<
+  This is a matlab interface to the internal_expand function. 
+  EPS, 7/96.
+*/
+
+#define V4_COMPAT
+#include <matrix.h>  /* Matlab matrices */
+#include <mex.h>
+
+#include "convolve.h"
+
+#define notDblMtx(it) (!mxIsNumeric(it) || !mxIsDouble(it) || mxIsSparse(it) || mxIsComplex(it))
+
+void mexFunction(int nlhs,           /* Num return vals on lhs */
+                 mxArray *plhs[],    /* Matrices on lhs      */
+                 int nrhs,           /* Num args on rhs    */
+                 const mxArray *prhs[]     /* Matrices on rhs */
+                 )
+  {
+  double *image,*filt, *temp, *result, *orig_filt;
+  int x_fdim, y_fdim, x_idim, y_idim;
+  int orig_x = 0, orig_y, x, y;
+  int x_rdim, y_rdim;
+  int x_start = 1;
+  int x_step = 1;
+  int y_start = 1;
+  int y_step = 1;
+  int x_stop, y_stop;
+  mxArray *arg;
+  double *mxMat;
+  char edges[15] = "reflect1";
+
+  if (nrhs<2) mexErrMsgTxt("requres at least 2 args.");
+
+  /* ARG 1: IMAGE  */
+  arg = prhs[0];
+  if notDblMtx(arg) mexErrMsgTxt("IMAGE arg must be a non-sparse double float matrix.");
+  image = mxGetPr(arg);
+  x_idim = (int) mxGetM(arg); /* X is inner index! */
+  y_idim = (int) mxGetN(arg);
+
+  /* ARG 2: FILTER */
+  arg = prhs[1];
+  if notDblMtx(arg) mexErrMsgTxt("FILTER arg must be non-sparse double float matrix.");  filt = mxGetPr(arg);
+  x_fdim = (int) mxGetM(arg); 
+  y_fdim = (int) mxGetN(arg);
+
+  /* ARG 3 (optional): EDGES */
+  if (nrhs>2) 
+          {
+          if (!mxIsChar(prhs[2]))
+                mexErrMsgTxt("EDGES arg must be a string.");
+          mxGetString(prhs[2],edges,15);
+          }
+
+  /* ARG 4 (optional): STEP */
+  if (nrhs>3)
+      {
+      arg = prhs[3];
+      if notDblMtx(arg) mexErrMsgTxt("STEP arg must be double float matrix.");
+      if (mxGetM(arg) * mxGetN(arg) != 2)
+         mexErrMsgTxt("STEP arg must contain two elements.");
+      mxMat = mxGetPr(arg);
+      x_step = (int) mxMat[0];
+      y_step = (int) mxMat[1];
+      if ((x_step<1) || (y_step<1))
+         mexErrMsgTxt("STEP values must be greater than zero.");
+      }
+
+  /* ARG 5 (optional): START */
+  if (nrhs>4)
+      {
+      arg = prhs[4];
+      if notDblMtx(arg) mexErrMsgTxt("START arg must be double float matrix.");
+      if (mxGetM(arg) * mxGetN(arg) != 2)
+        mexErrMsgTxt("START arg must contain two elements.");
+      mxMat = mxGetPr(arg);
+      x_start = (int) mxMat[0];
+      y_start = (int) mxMat[1];
+      if ((x_start<1) || (y_start<1))
+         mexErrMsgTxt("START values must be greater than zero.");
+      }
+  x_start--;  /* convert to standard C indexes */
+  y_start--;
+
+  /* ARG 6 (optional): STOP */
+  if (nrhs>5)
+      {
+      if notDblMtx(prhs[5]) mexErrMsgTxt("STOP arg must be double float matrix.");
+      if (mxGetM(prhs[5]) * mxGetN(prhs[5]) != 2)
+         mexErrMsgTxt("STOP arg must contain two elements.");
+      mxMat = mxGetPr(prhs[5]);
+      x_stop = (int) mxMat[0];
+      y_stop = (int) mxMat[1];
+      if ((x_stop<x_start) || (y_stop<y_start))
+         mexErrMsgTxt("STOP values must be greater than START values.");
+      }
+  else
+      { /* default: make res dims a multiple of STEP size */
+      x_stop = x_step * ((x_start/x_step) + x_idim);
+      y_stop = y_step * ((y_start/y_step) + y_idim);
+      }
+
+  /* ARG 6 (optional): RESULT image */
+  if (nrhs>6)
+      {
+      arg = prhs[6];
+      if notDblMtx(arg) mexErrMsgTxt("RES arg must be double float matrix.");
+
+      /* 7/10/97: Returning one of the args causes problems with Matlab's memory 
+         manager, so we don't return anything if the result image is passed */
+      /*  plhs[0] = arg;  */
+      result = mxGetPr(arg);
+      x_rdim =  (int) mxGetM(arg); /* X is inner index! */
+      y_rdim = (int) mxGetN(arg);
+      if  ((x_stop>x_rdim) || (y_stop>y_rdim))
+        mexErrMsgTxt("STOP values must within image dimensions.");
+      }
+  else
+      {
+      x_rdim = x_stop; 
+      y_rdim = y_stop;
+      /*  x_rdim = x_step * ((x_stop+x_step-1)/x_step);
+          y_rdim = y_step * ((y_stop+y_step-1)/y_step);  */
+
+      plhs[0] = (mxArray *) mxCreateDoubleMatrix(x_rdim,y_rdim,mxREAL);
+      if (plhs[0] == NULL) mexErrMsgTxt("Cannot allocate result matrix");
+      result = mxGetPr(plhs[0]);
+      }
+          
+  if ( (((x_stop-x_start+x_step-1) / x_step) != x_idim) ||
+       (((y_stop-y_start+y_step-1) / y_step) != y_idim) )
+    {
+      mexPrintf("Im dims: [%d %d]\n",x_idim,y_idim);
+      mexPrintf("Start:   [%d %d]\n",x_start,y_start);
+      mexPrintf("Step:    [%d %d]\n",x_step,y_step);
+      mexPrintf("Stop:    [%d %d]\n",x_stop,y_stop);
+      mexPrintf("Res dims: [%d %d]\n",x_rdim,y_rdim);
+      mexErrMsgTxt("Image sizes and upsampling args are incompatible!");
+    }
+
+  /* upConv has a bug for even-length kernels when using the 
+     reflect1, extend, or repeat edge-handlers */
+  if ((!strcmp(edges,"reflect1") || !strcmp(edges,"extend") || !strcmp(edges,"repeat"))
+      &&
+      ((x_fdim%2 == 0) || (y_fdim%2 == 0)))
+      {
+      orig_filt = filt;
+      orig_x = x_fdim; 
+      orig_y = y_fdim;
+      x_fdim = 2*(orig_x/2)+1;
+      y_fdim = 2*(orig_y/2)+1;
+      filt = mxCalloc(x_fdim*y_fdim, sizeof(double));
+      if (filt == NULL)
+        mexErrMsgTxt("Cannot allocate necessary temporary space");
+      for (y=0; y<orig_y; y++)
+        for (x=0; x<orig_x; x++)
+            filt[y*x_fdim + x] = orig_filt[y*orig_x + x];
+      }
+
+  if ((x_fdim > x_rdim) || (y_fdim > y_rdim))
+    {
+    mexPrintf("Filter: [%d %d], ",x_fdim,y_fdim);
+    mexPrintf("Result: [%d %d]\n",x_rdim,y_rdim);
+    mexErrMsgTxt("FILTER dimensions larger than RESULT dimensions.");
+    }
+ 
+  temp = mxCalloc(x_fdim*y_fdim, sizeof(double));
+  if (temp == NULL)
+    mexErrMsgTxt("Cannot allocate necessary temporary space");
+
+  /*
+  printf("(%d, %d), (%d, %d), (%d, %d), (%d, %d), (%d, %d), %s\n",
+         x_idim,y_idim,x_fdim,y_fdim,x_rdim,y_rdim,
+         x_start,x_step,y_start,y_step,edges);
+         */
+
+  if (strcmp(edges,"circular") == 0)
+        internal_wrap_expand(image, filt, x_fdim, y_fdim,
+                             x_start, x_step, x_stop, y_start, y_step, y_stop,
+                             result, x_rdim, y_rdim);
+  else internal_expand(image, filt, temp, x_fdim, y_fdim,
+                       x_start, x_step, x_stop, y_start, y_step, y_stop,
+                       result, x_rdim, y_rdim, edges);
+
+  if (orig_x) mxFree((char *) filt);
+  mxFree((char *) temp);
+
+  return;
+  }      
+
+
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/wrap.c b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/wrap.c
new file mode 100755
index 0000000..a081123
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/MEX/wrap.c
@@ -0,0 +1,281 @@
+/* 
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;;  File: wrap.c
+;;;  Author: Eero Simoncelli
+;;;  Description: Circular convolution on 2D images.
+;;;  Creation Date: Spring, 1987.
+;;;  MODIFICATIONS:
+;;;      6/96: Switched array types to double float.
+;;;      2/97: made more robust and readable.  Added STOP arguments.
+;;;  ----------------------------------------------------------------
+;;;    Object-Based Vision and Image Understanding System (OBVIUS),
+;;;      Copyright 1988, Vision Science Group,  Media Laboratory,  
+;;;              Massachusetts Institute of Technology.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+*/
+
+#include <stdlib.h>
+
+#include "convolve.h"
+
+/*
+ --------------------------------------------------------------------
+ Performs correlation (i.e., convolution with filt(-x,-y)) of FILT
+ with IMAGE followed by subsampling (a.k.a. REDUCE in Burt&Adelson81).
+ The operations are combined to avoid unnecessary computation of the
+ convolution samples that are to be discarded in the subsampling
+ operation.  The convolution is done in 9 sections so that mod
+ operations are not performed unnecessarily.  The subsampling lattice
+ is specified by the START, STEP and STOP parameters.
+ -------------------------------------------------------------------- */
+
+/* abstract out the inner product computation */
+#define INPROD(YSTART,YIND,XSTART,XIND) \
+      { \
+      sum=0.0; \
+      for (y_im=YSTART, filt_pos=0, x_filt_stop=x_fdim; \
+           x_filt_stop<=filt_size; \
+           y_im++, x_filt_stop+=x_fdim) \
+         for (x_im=XSTART ; \
+              filt_pos<x_filt_stop; \
+              filt_pos++, x_im++) \
+           sum += imval[YIND][XIND] * filt[filt_pos]; \
+      result[res_pos] = sum; \
+      }
+
+int internal_wrap_reduce(image, x_dim, y_dim, filt, x_fdim, y_fdim,
+                     x_start, x_step, x_stop, y_start, y_step, y_stop, 
+                     result)
+  register image_type *filt, *result;
+  register int x_dim, y_dim, x_fdim, y_fdim;
+  image_type *image;
+  int x_start, x_step, x_stop, y_start, y_step, y_stop;
+  {
+  register double sum;
+  register int filt_size = x_fdim*y_fdim;
+  image_type **imval;
+  register int filt_pos, x_im, y_im, x_filt_stop;
+  register int x_pos, y_pos, res_pos;
+  int x_ctr_stop = x_dim - x_fdim + 1;
+  int y_ctr_stop = y_dim - y_fdim + 1;
+  int x_ctr_start = 0;
+  int y_ctr_start = 0;
+  int x_fmid = x_fdim/2;
+  int y_fmid = y_fdim/2;
+  
+  /* shift start/stop coords to filter upper left hand corner */
+  x_start -= x_fmid;   y_start -=  y_fmid;
+  x_stop -=  x_fmid;   y_stop -=  y_fmid;
+
+  if (x_stop < x_ctr_stop) x_ctr_stop = x_stop;
+  if (y_stop < y_ctr_stop) y_ctr_stop = y_stop;
+
+  /* Set up pointer array for rows */
+  imval = (image_type **) malloc(y_dim*sizeof(image_type *));
+  if (imval IS NULL)
+      {
+      printf("INTERNAL_WRAP: Failed to allocate temp array!");
+      return(-1);
+      }
+  for (y_pos=y_im=0;y_pos<y_dim;y_pos++,y_im+=x_dim)
+    imval[y_pos] = (image+y_im);
+  
+  for (res_pos=0, y_pos=y_start;              /* TOP ROWS */
+       y_pos<y_ctr_start;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start;
+         x_pos<x_ctr_start;
+         x_pos+=x_step, res_pos++)
+      INPROD(y_pos+y_dim, y_im%y_dim, x_pos+x_dim, x_im%x_dim)
+
+    for (; 
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos+y_dim, y_im%y_dim, x_pos, x_im)
+
+    for (; 
+         x_pos<x_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos+y_dim, y_im%y_dim, x_pos, x_im%x_dim)
+    } /* end TOP ROWS */
+  
+  for (;                        /* MID ROWS */
+       y_pos<y_ctr_stop;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start;
+         x_pos<x_ctr_start;
+         x_pos+=x_step, res_pos++)
+      INPROD(y_pos, y_im, x_pos+x_dim, x_im%x_dim)
+
+    for (;                      /* CENTER SECTION */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos, y_im, x_pos, x_im)
+
+    for (; 
+         x_pos<x_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos, y_im, x_pos, x_im%x_dim)
+    } /* end MID ROWS */
+  
+  for (;                        /* BOTTOM ROWS */
+       y_pos<y_stop;
+       y_pos+=y_step) 
+     {
+    for (x_pos=x_start;
+         x_pos<x_ctr_start;
+         x_pos+=x_step, res_pos++)
+      INPROD(y_pos, y_im%y_dim, x_pos+x_dim, x_im%x_dim)
+
+    for (; 
+         x_pos<x_ctr_stop; 
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos, y_im%y_dim, x_pos, x_im)
+
+    for (;
+         x_pos<x_stop;
+         x_pos+=x_step, res_pos++) 
+      INPROD(y_pos, y_im%y_dim, x_pos, x_im%x_dim)
+    } /* end BOTTOM ROWS */
+
+  free ((image_type **) imval);
+
+  return(0);
+  }     /* end of internal_wrap_reduce */
+
+
+
+/*
+ --------------------------------------------------------------------
+ Performs upsampling (padding with zeros) followed by convolution of
+ FILT with IMAGE (a.k.a. EXPAND in Burt&Adelson81).  The operations
+ are combined to avoid unnecessary multiplication of filter samples
+ with zeros in the upsampled image.  The convolution is done in 9
+ sections so that mod operation is not performed unnecessarily.
+ Arguments are described in the comment above internal_wrap_reduce.
+
+ WARNING: this subroutine destructively modifes the RESULT image, so
+ the user must zero the result before invocation!
+ -------------------------------------------------------------------- */
+
+/* abstract out the inner product computation */
+#define INPROD2(YSTART,YIND,XSTART,XIND) \
+      { \
+      val = image[im_pos]; \
+      for (y_res=YSTART, filt_pos=0, x_filt_stop=x_fdim; \
+           x_filt_stop<=filt_size; \
+           y_res++, x_filt_stop+=x_fdim) \
+        for (x_res=XSTART; \
+             filt_pos<x_filt_stop; \
+             filt_pos++, x_res++) \
+          imval[YIND][XIND] += val * filt[filt_pos]; \
+      }
+
+int internal_wrap_expand(image, filt, x_fdim, y_fdim,
+              x_start, x_step, x_stop, y_start, y_step, y_stop,
+              result, x_dim, y_dim)
+  register image_type *filt, *result;
+  register int x_fdim, y_fdim, x_dim, y_dim;
+  image_type *image; 
+  int x_start, x_step, x_stop, y_start, y_step, y_stop;
+  {
+  register double val;
+  register int filt_size = x_fdim*y_fdim;
+  image_type **imval;
+  register int filt_pos, x_res, y_res, x_filt_stop;
+  register int x_pos, y_pos, im_pos;
+  int x_ctr_stop = x_dim - x_fdim + 1;
+  int y_ctr_stop = y_dim - y_fdim + 1;
+  int x_ctr_start = 0;
+  int y_ctr_start = 0;
+  int x_fmid = x_fdim/2;
+  int y_fmid = y_fdim/2;
+  
+  /* shift start/stop coords to filter upper left hand corner */
+  x_start -= x_fmid;   y_start -=  y_fmid;
+  x_stop -=  x_fmid;   y_stop -=  y_fmid;
+
+  if (x_stop < x_ctr_stop) x_ctr_stop = x_stop;
+  if (y_stop < y_ctr_stop) y_ctr_stop = y_stop;
+
+  /* Set up pointer array for rows */
+  imval = (image_type **) malloc(y_dim*sizeof(image_type *));
+  if (imval IS NULL)
+      {
+      printf("INTERNAL_WRAP: Failed to allocate temp array!");
+      return(-1);
+      }
+  for (y_pos=y_res=0;y_pos<y_dim;y_pos++,y_res+=x_dim)
+    imval[y_pos] = (result+y_res);
+  
+  for (im_pos=0, y_pos=y_start; /* TOP ROWS */
+       y_pos<y_ctr_start;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start; 
+         x_pos<x_ctr_start;
+         x_pos+=x_step, im_pos++)
+      INPROD2(y_pos+y_dim, y_res%y_dim, x_pos+x_dim, x_res%x_dim)
+        
+    for (; 
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos+y_dim, y_res%y_dim, x_pos, x_res)
+
+    for (; 
+         x_pos<x_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos+y_dim, y_res%y_dim, x_pos, x_res%x_dim)
+    } /* end TOP ROWS */
+  
+  for (;                        /* MID ROWS */
+       y_pos<y_ctr_stop;
+       y_pos+=y_step)
+    {
+    for (x_pos=x_start; 
+         x_pos<x_ctr_start;
+         x_pos+=x_step, im_pos++)
+      INPROD2(y_pos, y_res, x_pos+x_dim, x_res%x_dim)
+        
+    for (;                      /* CENTER SECTION */
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos, y_res, x_pos, x_res)
+
+    for (; 
+         x_pos<x_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos, y_res, x_pos, x_res%x_dim)
+    } /* end MID ROWS */
+  
+  for (;                        /* BOTTOM ROWS */
+       y_pos<y_stop;
+       y_pos+=y_step) 
+    {
+    for (x_pos=x_start; 
+         x_pos<x_ctr_start;
+         x_pos+=x_step, im_pos++)
+      INPROD2(y_pos, y_res%y_dim, x_pos+x_dim, x_res%x_dim)
+        
+    for (; 
+         x_pos<x_ctr_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos, y_res%y_dim, x_pos, x_res)
+
+    for (; 
+         x_pos<x_stop;
+         x_pos+=x_step, im_pos++) 
+      INPROD2(y_pos, y_res%y_dim, x_pos, x_res%x_dim)
+    } /* end BOTTOM ROWS */
+
+  free ((image_type **) imval);
+  return(0);
+  } /* end of internal_wrap_expand */
+
+
+
+/* Local Variables: */
+/* buffer-read-only: t */
+/* End: */
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/README b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/README
new file mode 100755
index 0000000..8f339f3
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/README
@@ -0,0 +1,55 @@
+This package contains some MatLab tools for multi-scale image
+processing.  Briefly, the tools include:
+  - Recursive multi-scale image decompositions (pyramids), including
+    Laplacian pyramids, QMFs, Wavelets, and steerable pyramids.  These
+    operate on 1D or 2D signals of arbitrary dimension.  Data
+    structures are compatible with the MatLab wavelet toolbox.
+  - Fast 2D convolution routines, with subsampling and boundary-handling.
+  - Fast point-operations, histograms, histogram-matching.
+  - Fast synthetic image generation: sine gratings, zone plates, fractals, etc.
+  - Display routines for images and pyramids.  These include several
+    auto-scaling options, rounding to integer zoom factors to avoid 
+    resampling artifacts, and useful labeling (dimensions and gray-range).
+
+The package is available as a gnu-zipped UNIX "tar" file, 
+accessible from the web page: 
+  http://www.cns.nyu.edu/~lcv/software.html
+
+The code works in Matlab versions 4.2 and higher, and has been fully tested
+on Linux and Macintosh OSX platforms (it should, however, port easily to
+others).  To use the code (these lines are for UNIX):
+  1) gunzip matlabPyrTools.tar.gz       # unpack g'zipped file
+  2) tar tvf matlabPyrTools.tar         # view contents
+  3) tar xvf matlabPyrTools.tar         # extract contents
+  4) rm matlabPyrTools.tar              # delete tarfile
+  5) Run matlab, and execute:
+      path(<pathname-of-matlabPyrTools>, path);
+      help matlabPyrTools
+
+A few functions are actually MEX interfaces to C code.  These are
+contained in the subdirectory called MEX.  The MEX files have been
+tested on Sun (Solaris), LinuX on a Pentium platform, and Macintosh
+OSX on a PowerPC, but should not be difficult to compile on most other
+platforms.  Source code is included in the MEX directory, as well as
+Make files.  I've included pre-compiled versions for a number of
+platforms (Solaris,Linux,Mac,Windows).  To make sure these are in your
+matlab path, you can do *one* of the following:
+  1) Create a symbolic link (or macintosh "alias") for the relavent files 
+     in the main matlabPyrTools directory,   or
+  2) Copy the relavent files into the main matlabPyrTools directory, or 
+  3) Put the MEX subdirectory in your matlab path.
+
+Some example script files showing usage of the code are in the
+directory <dir>/TUTORIALS.  There is a README file in that directory
+describing the contents.
+
+Incremental changes to the code are documented in the ChangeLog file.
+
+Comments/Suggestions/Bugs to:
+  Eero P. Simoncelli
+  Associate Professor,
+  Center for Neural Science, and
+  Courant Institute for Mathematical Sciences
+  New York University
+  eero.simoncelli@nyu.edu
+  http://www.cns.nyu.edu/~eero/
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/README b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/README
new file mode 100755
index 0000000..06960a4
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/README
@@ -0,0 +1,18 @@
+
+This directory contains some Matlab script files that serve to give
+example usage of this code, and also to explain some of the 
+representations and algorithms.
+
+The files are NOT meant to be executed from the MatLab prompt (like many 
+of the MatLab demos).  You should instead read through the comments, 
+executing the subsequent pieces of code.  This gives you a chance to 
+explore as you go...
+
+matlabPyrTools.m - Example usage of the code in the distribution.
+
+pyramids.m - An introduction to multi-scale pyramid representations, 
+        covering Laplacian, QMF/Wavelet, and Steerable pyramids.  The
+        file assumes a knowledge of linear systems, matrix algebra, 
+        and 2D Fourier transforms.
+
+more to come....
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/matlabPyrTools.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/matlabPyrTools.m
new file mode 100755
index 0000000..44c27ce
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/matlabPyrTools.m
@@ -0,0 +1,145 @@
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%%% Some examples using the tools in this distribution.
+%%% Eero Simoncelli, 2/97.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%% Add directory to path (YOU'LL NEED TO ADJUST THIS):
+path('/lcv/matlab/lib/matlabPyrTools',path);
+
+%% Load an image, and downsample to a size appropriate for the machine speed.
+oim = pgmRead('einstein.pgm');
+tic; corrDn(oim,[1 1; 1 1]/4,'reflect1',[2 2]); time = toc;
+imSubSample = min(max(floor(log2(time)/2+3),0),2);
+im = blurDn(oim, imSubSample,'qmf9');
+clear oim;
+
+%%% ShowIm: 
+%% 3 types of automatic graylevel scaling, 2 types of automatic
+%% sizing, with or without title and Range information.
+help showIm
+clf; showIm(im,'auto1','auto','Al')
+clf; showIm('im','auto2')
+clf; showIm(im,'auto3',2)
+
+%%% Statistics:
+mean2(im)
+var2(im)
+skew2(im)
+kurt2(im)
+entropy2(im)
+imStats(im)
+
+%%% Synthetic images.  First pick some parameters:
+sz = 200;
+dir = 2*pi*rand(1)
+slope = 10*rand(1)-5
+int = 10*rand(1)-5;
+orig = round(1+(sz-1)*rand(2,1));
+expt = 0.8+rand(1)
+ampl = 1+5*rand(1)
+ph = 2*pi*rand(1)
+per = 20
+twidth = 7
+
+clf;
+showIm(mkRamp(sz,dir,slope,int,orig));
+showIm(mkImpulse(sz,orig,ampl));
+showIm(mkR(sz,expt,orig));
+showIm(mkAngle(sz,dir));
+showIm(mkDisc(sz,sz/4,orig,twidth));
+showIm(mkGaussian(sz,(sz/6)^2,orig,ampl));
+showIm(mkZonePlate(sz,ampl,ph));
+showIm(mkAngularSine(sz,3,ampl,ph,orig));
+showIm(mkSine(sz,per,dir,ampl,ph,orig));
+showIm(mkSquare(sz,per,dir,ampl,ph,orig,twidth));
+showIm(mkFract(sz,expt));
+
+
+%%% Point operations (lookup tables):
+[Xtbl,Ytbl] = rcosFn(20, 25, [-1 1]);
+plot(Xtbl,Ytbl);
+showIm(pointOp(mkR(100,1,[70,30]), Ytbl, Xtbl(1), Xtbl(2)-Xtbl(1), 0));
+
+
+%%% histogram Modification/matching:
+[N,X] = histo(im, 150);
+[mn, mx] = range2(im);
+matched = histoMatch(rand(size(im)), N, X);
+showIm(im + sqrt(-1)*matched);
+[Nm,Xm] = histo(matched,150);
+nextFig(2,1); 
+  subplot(1,2,1); plot(X,N); axis([mn mx 0 max(N)]);
+  subplot(1,2,2);  plot(Xm,Nm); axis([mn mx 0 max(N)]);
+nextFig(2,-1);
+
+%%% Convolution routines:
+
+%% Compare speed of convolution/downsampling routines:
+noise = rand(400); filt = rand(10);
+tic; res1 = corrDn(noise,filt(10:-1:1,10:-1:1),'reflect1',[2 2]); toc;
+tic; ires = rconv2(noise,filt); res2 = ires(1:2:400,1:2:400); toc;
+imStats(res1,res2)
+
+%% Display image and extension of left and top boundaries:
+fsz = [9 9];
+fmid = ceil((fsz+1)/2);
+imsz = [16 16];
+
+% pick one:
+im = eye(imsz);
+im = mkRamp(imsz,pi/6); 
+im = mkSquare(imsz,6,pi/6); 
+
+% pick one:
+edges='reflect1';
+edges='reflect2';
+edges='repeat';
+edges='extend';
+edges='zero';
+edges='circular';
+edges='dont-compute';
+
+filt = mkImpulse(fsz,[1 1]);
+showIm(corrDn(im,filt,edges));
+line([0,0,imsz(2),imsz(2),0]+fmid(2)-0.5, ...
+     [0,imsz(1),imsz(1),0,0]+fmid(1)-0.5);
+title(sprintf('Edges = %s',edges));
+
+%%% Multi-scale pyramids (see pyramids.m for more examples,
+%%% and explanations):
+
+%% A Laplacian pyramid:
+[pyr,pind] = buildLpyr(im);
+showLpyr(pyr,pind);
+
+res = reconLpyr(pyr, pind);             % full reconstruction
+imStats(im,res);                        % essentially perfect
+
+res = reconLpyr(pyr, pind, [2 3]);  %reconstruct 2nd and 3rd levels only  
+showIm(res);
+
+%% Wavelet/QMF pyramids:
+filt = 'qmf9'; edges = 'reflect1';
+filt = 'haar'; edges = 'qreflect2';
+filt = 'qmf12'; edges = 'qreflect2';
+filt = 'daub3'; edges = 'circular';
+
+[pyr,pind] = buildWpyr(im, 5-imSubSample, filt, edges);
+showWpyr(pyr,pind,'auto2');
+
+res = reconWpyr(pyr, pind, filt, edges);
+clf; showIm(im + i*res);
+imStats(im,res);
+
+res = reconWpyr(pyr, pind, filt, edges, 'all', [2]);  %vertical only
+clf; showIm(res);
+
+%% Steerable pyramid:
+[pyr,pind] = buildSpyr(im,4-imSubSample,'sp3Filters');  
+showSpyr(pyr,pind);
+
+%% Steerable pyramid, constructed in frequency domain:
+[pyr,pind] = buildSFpyr(im,5-imSubSample,4);  %5 orientation bands
+showSpyr(pyr,pind);
+res = reconSFpyr(pyr,pind);
+imStats(im,res);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/pyramids.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/pyramids.m
new file mode 100755
index 0000000..2123c69
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/TUTORIALS/pyramids.m
@@ -0,0 +1,903 @@
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%%% IMAGE PYRAMID TUTORIAL 
+%%%
+%%% A brief introduction to multi-scale pyramid decompositions for image 
+%%% processing.  You should go through this, reading the comments, and
+%%% executing the corresponding MatLab instructions.  This file assumes 
+%%% a basic familiarity with matrix algebra, with linear systems and Fourier
+%%% theory, and with MatLab.  If you don't understand a particular
+%%% function call, execute "help <functionName>" to see documentation.
+%%%
+%%% EPS, 6/96.  
+%%% Based on the original OBVIUS tutorial.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%% Determine a subsampling factor for images, based on machine speed:
+oim = pgmRead('einstein.pgm');
+tic; corrDn(oim,[1 1; 1 1]/4,'reflect1',[2 2]); time = toc;
+imSubSample = min(max(floor(log2(time)/2+3),0),2);
+im = blurDn(oim, imSubSample,'qmf9');
+clear oim;
+clf; showIm(im, 'auto2', 'auto', 'im');
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%%% LAPLACIAN PYRAMIDS: 
+
+%% Images may be decomposed into information at different scales.  
+%% Blurring eliminates the fine scales (detail):
+
+binom5 = binomialFilter(5);
+lo_filt = binom5*binom5';
+blurred = rconv2(im,lo_filt);
+subplot(1,2,1); showIm(im, 'auto2', 'auto', 'im');
+subplot(1,2,2); showIm(blurred, 'auto2', 'auto', 'blurred');
+
+%% Subtracting the blurred image from the original leaves ONLY the
+%% fine scale detail:
+fine0 = im - blurred;
+subplot(1,2,1); showIm(fine0, 'auto2', 'auto', 'fine0');
+
+%% The blurred and fine images contain all the information found in
+%% the original image.  Trivially, adding the blurred image to the
+%% fine scale detail will reconstruct the original.  We can compare
+%% the original image to the sum of blurred and fine using the
+%% "imStats" function, which reports on the statistics of the
+%% difference between it's arguments:
+imStats(im, blurred+fine0);
+
+%% Since the filter is a lowpass filter, we might want to subsample
+%% the blurred image.  This may cause some aliasing (depends on the
+%% filter), but the decomposition structure given above will still be
+%% possible.  The corrDn function correlates (same as convolution, but
+%% flipped filter) and downsamples in a single operation (for
+%% efficiency).  The string 'reflect1' tells the function to handle
+%% boundaries by reflecting the image about the edge pixels.  Notice
+%% that the blurred1 image is half the size (in each dimension) of the
+%% original image.
+lo_filt = 2*binom5*binom5';  %construct a separable 2D filter
+blurred1 = corrDn(im,lo_filt,'reflect1',[2 2]);
+subplot(1,2,2); showIm(blurred1,'auto2','auto','blurred1');
+
+%% Now, to extract fine scale detail, we must interpolate the image
+%% back up to full size before subtracting it from the original.  The
+%% upConv function does upsampling (padding with zeros between
+%% samples) followed by convolution.  This can be done using the
+%% lowpass filter that was applied before subsampling or it can be
+%% done with a different filter.
+fine1 = im - upConv(blurred1,lo_filt,'reflect1',[2 2],[1 1],size(im));
+subplot(1,2,1); showIm(fine1,'auto2','auto','fine1');
+
+%% We now have a technique that takes an image, computes two new
+%% images (blurred1 and fine1) containing the coarse scale information
+%% and the fine scale information.  We can also (trivially)
+%% reconstruct the original from these two (even if the subsampling of
+%% the blurred1 image caused aliasing):
+
+recon = fine1 + upConv(blurred1,lo_filt,'reflect1',[2 2],[1 1],size(im));
+imStats(im, recon);
+
+%% Thus, we have described an INVERTIBLE linear transform that maps an
+%% input image to the two images blurred1 and fine1.  The inverse
+%% transformation maps blurred1 and fine1 to the result.  This is
+%% depicted graphically with a system diagram:
+%%
+%% IM --> blur/down2 ---------> BLURRED1 --> up2/blur --> add --> RECON
+%%  |                   |                                  ^
+%%  |                   |                                  |
+%%  |                   V                                  |
+%%  |                up2/blur                              |
+%%  |                   |                                  |
+%%  |                   |                                  |
+%%  |                   V                                  |
+%%   --------------> subtract --> FINE1 -------------------
+%% 
+%% Note that the number of samples in the representation (i.e., total
+%% samples in BLURRED1 and FINE1) is 1.5 times the number of samples
+%% in the original IM.  Thus, this representation is OVERCOMPLETE.
+
+%% Often, we will want further subdivisions of scale.  We can
+%% decompose the (coarse-scale) BLURRED1 image into medium coarse and
+%% very coarse images by applying the same splitting technique:
+blurred2 = corrDn(blurred1,lo_filt,'reflect1',[2 2]);
+showIm(blurred2)
+
+fine2 = blurred1 - upConv(blurred2,lo_filt,'reflect1',[2 2],[1 1],size(blurred1));
+showIm(fine2)
+
+%% Since blurred2 and fine2 can be used to reconstruct blurred1, and
+%% blurred1 and fine1 can be used to reconstruct the original image,
+%% the set of THREE images (also known as "subbands") {blurred2,
+%% fine2, fine1} constitute a complete representation of the original
+%% image.  Note that the three subbands are displayed at the same size,
+%% but they are actually three different sizes.
+
+subplot(1,3,1); showIm(fine1,'auto2',2^(imSubSample-1),'fine1');
+subplot(1,3,2); showIm(fine2,'auto2',2^(imSubSample),'fine2');
+subplot(1,3,3); showIm(blurred2,'auto2',2^(imSubSample+1),'blurred2');
+
+%% It is useful to consider exactly what information is stored in each
+%% of the pyramid subbands.  The reconstruction process involves
+%% recursively interpolating these images and then adding them to the
+%% image at the next finer scale.  To see the contribution of ONE of
+%% the representation images (say blurred2) to the reconstruction, we
+%% imagine filling all the other subbands with zeros and then
+%% following our reconstruction procedure.  For the blurred2 subband,
+%% this is equivalent to simply calling upConv twice:
+blurred2_full = upConv(upConv(blurred2,lo_filt,'reflect1',[2 2],[1 1],size(blurred1)),...
+    lo_filt,'reflect1',[2 2],[1 1],size(im));
+subplot(1,3,3); showIm(blurred2_full,'auto2',2^(imSubSample-1),'blurred2-full');
+
+%% For the fine2 subband, this is equivalent to calling upConv once:
+fine2_full = upConv(fine2,lo_filt,'reflect1',[2 2],[1 1],size(im));
+subplot(1,3,2); showIm(fine2_full,'auto2',2^(imSubSample-1),'fine2-full');
+
+%% If we did everything correctly, we should be able to add together
+%% these three full-size images to reconstruct the original image:
+recon = blurred2_full + fine2_full + fine1;
+imStats(im, recon)
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%%% FUNCTIONS for CONSTRUCTING/MANIPULATING LAPLACIAN PYRAMIDS
+
+%% We can continue this process, recursively splitting off finer and
+%% finer details from the blurred image (like peeling off the outer
+%% layers of an onion).  The resulting data structure is known as a
+%% "Laplacian Pyramid".  To make things easier, we have written a
+%% MatLab function called buildLpyr to construct this object.  The
+%% function returns two items: a long vector containing the subbands
+%% of the pyramid, and an index matrix that is used to access these
+%% subbands.  The display routine showLpyr shows all the subbands of the
+%% pyramid, at the their correct relative sizes.  It should now be
+%% clearer why these data structures are called "pyramids".
+[pyr,pind] = buildLpyr(im,5-imSubSample); 
+showLpyr(pyr,pind);
+
+%% There are also "accessor" functions for pulling out a single subband:
+showIm(pyrBand(pyr,pind,2));
+
+%% The reconLpyr function allows you to reconstruct from a laplacian pyramid.
+%% The third (optional) arg allows you to select any subset of pyramid bands
+%% (default is to use ALL of them).
+clf; showIm(reconLpyr(pyr,pind,[1 3]),'auto2','auto','bands 1 and 3 only');
+
+fullres = reconLpyr(pyr,pind);
+showIm(fullres,'auto2','auto','Full reconstruction');
+imStats(im,fullres);
+
+%% buildLpyr uses 5-tap filters by default for building Laplacian
+%% pyramids.  You can specify other filters:
+namedFilter('binom3')
+[pyr3,pind3] = buildLpyr(im,5-imSubSample,'binom3');
+showLpyr(pyr3,pind3);
+fullres3 = reconLpyr(pyr3,pind3,'all','binom3');
+imStats(im,fullres3);
+
+%% Here we build a "Laplacian" pyramid using random filters.  filt1 is
+%% used with the downsampling operations and filt2 is used with the
+%% upsampling operations.  We normalize the filters for display
+%% purposes.  Of course, these filters are (almost certainly) not very
+%% "Gaussian", and the subbands of such a pyramid will be garbage!
+%% Nevertheless, it is a simple property of the Laplacian pyramid that
+%% we can use ANY filters and we will still be able to reconstruct
+%% perfectly.
+
+filt1 = rand(1,5); filt1 = sqrt(2)*filt1/sum(filt1)
+filt2 = rand(1,3); filt2 = sqrt(2)*filt2/sum(filt2)
+[pyrr,pindr] = buildLpyr(im,5-imSubSample,filt1,filt2);
+showLpyr(pyrr,pindr);
+fullresr = reconLpyr(pyrr,pindr,'all',filt2);
+imStats(im,fullresr);
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%%% ALIASING in the Gaussian and Laplacian pyramids:
+
+%% Unless one is careful, the subsampling operations will introduce aliasing
+%% artifacts in these pyramid transforms.  This is true even though the
+%% Laplacian pyramid can be used to reconstruct the original image perfectly.
+%% When reconstructing, the pyramid is designed in such a way that these
+%% aliasing artifacts cancel out.  So it's not a problem if the only thing we
+%% want to do is reconstruct.  However, it can be a serious problem if we
+%% intend to process each of the subbands independently.
+
+%% One way to see the consequences of the aliasing artifacts is by
+%% examining variations that occur when the input is shifted.  We
+%% choose an image and shift it by some number of pixels.  Then blur
+%% (filter-downsample-upsample-filter) the original image and blur the
+%% shifted image.  If there's no aliasing, then the blur and shift
+%% operations should commute (i.e.,
+%% shift-filter-downsample-upsample-filter is the same as
+%% filter-downsample-upsample-filter-shift).  Try this for 2 different
+%% filters (by replacing 'binom3' with 'binom5' or 'binom7' below),
+%% and you'll see that the aliasing is much worse for the 3 tap
+%% filter.
+
+sig = 100*randn([1 16]);
+sh = [0 7];  %shift amount
+lev = 2; % level of pyramid to look at
+flt = 'binom3';  %filter to use: 
+
+shiftIm = shift(sig,sh);
+[pyr,pind] = buildLpyr(shiftIm, lev, flt, flt, 'circular');
+shiftBlur = reconLpyr(pyr, pind, lev, flt, 'circular');
+
+[pyr,pind] = buildLpyr(sig, lev, flt, flt, 'circular');
+res = reconLpyr(pyr, pind, lev, flt, 'circular');
+blurShift = shift(res,sh);
+
+subplot(2,1,1); r = showIm(shiftBlur,'auto2','auto','shiftBlur');
+subplot(2,1,2); showIm(blurShift,r,'auto','blurShift');
+imStats(blurShift,shiftBlur);
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%%% PROJECTION and BASIS functions:
+
+%% An invertible, linear transform can be characterized in terms
+%% of a set of PROJECTION and BASIS functions.  In matlab matrix
+%% notation:
+%
+%%     c = P' * x
+%%     x = B * c
+%
+%% where x is an input, c are the transform coefficients, P and B
+%% are matrices.  The columns of P are the projection functions (the
+%% input is projected onto the the columns of P to get each successive
+%% transform coefficient).  The columns of B are the basis
+%% functions (x is a linear combination of the columns of B).
+
+%% Since the Laplacian pyramid is a linear transform, we can ask: what
+%% are its BASIS functions?  We consider these in one dimension for
+%% simplicity.  The BASIS function corresponding to a given
+%% coefficient tells us how much that coefficient contributes to each
+%% pixel in the reconstructed image.  We can construct a single basis
+%% function by setting one sample of one subband equal to 1.0 (and all
+%% others to zero) and reconstructing. To build the entire matrix, we
+%% have to do this for every sample of every subband:
+sz = min(round(48/(sqrt(2)^imSubSample)),36);
+sig = zeros(sz,1);
+[pyr,pind] = buildLpyr(sig);
+basis = zeros(sz,size(pyr,1));
+for n=1:size(pyr,1)
+  pyr = zeros(size(pyr));
+  pyr(n) = 1;
+  basis(:,n) = reconLpyr(pyr,pind);
+end
+clf; showIm(basis)
+
+%% The columns of the basis matrix are the basis functions.  The
+%% matrix is short and fat, corresponding to the fact that the
+%% representation is OVERCOMPLETE.  Below, we plot the middle one from
+%% each subband, starting with the finest scale.  Note that all of
+%% these basis functions are lowpass (Gaussian-like) functions.
+locations = round(sz * (2 - 3./2.^[1:max(4,size(pind,1))]))+1;
+for lev=1:size(locations,2)
+  subplot(2,2,lev);
+  showIm(basis(:,locations(lev)));
+  axis([0 sz 0 1.1]);
+end
+
+%% Now, we'd also like see the inverse (we'll them PROJECTION)
+%% functions. We need to ask how much of each sample of the input
+%% image contributes to a given pyramid coefficient.  Thus, the matrix
+%% is constructed by building pyramids on the set of images with
+%% impulses at each possible location.  The rows of this matrix are
+%% the projection functions.
+projection = zeros(size(pyr,1),sz);
+for pos=1:sz
+  [pyr,pind] = buildLpyr(mkImpulse([1 sz], [1 pos]));
+  projection(:,pos) = pyr;
+end
+clf; showIm(projection);
+
+%% Building a pyramid corresponds to multiplication by the projection
+%% matrix.  Reconstructing from this pyramid corresponds to
+%% multiplication by the basis matrix.  Thus, the product of the two
+%% matrices (in this order) should be the identity matrix:
+showIm(basis*projection);
+
+%% We can plot a few example projection functions at different scales.
+%% Note that all of the projection functions are bandpass functions,
+%% except for the coarsest subband which is lowpass.
+for lev=1:size(locations,2)
+  subplot(2,2,lev);
+  showIm(projection(locations(lev),:));
+  axis([0 sz -0.3 0.8]);
+end
+  
+%% Now consider the frequency response of these functions, plotted over the
+%% range [-pi,pi]:
+for lev=1:size(locations,2)
+  subplot(2,2,lev);
+  proj = projection(locations(lev),:);
+  plot(pi*[-32:31]/32,fftshift(abs(fft(proj',64))));
+  axis([-pi pi -0.1 3]);
+end
+
+%% The first projection function is highpass, and the second is bandpass.  Both
+%% of these look something like the Laplacian (2nd derivative) of a Gaussian.
+%% The last is lowpass, as are the basis functions.  Thus, the basic operation
+%% used to create each level of the pyramid involves a simple highpass/lowpass
+%% split.
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%%% QMF/WAVELET PYRAMIDS.
+
+%% Two things about Laplacian pyramids are a bit unsatisfactory.
+%% First, there are more pixels (coefficients) in the representation
+%% than in the original image. Specifically, the 1-dimensional
+%% transform is overcomplete by a factor of 4/3, and the 2-dimensional
+%% transform is overcomplete by a factor of 2.  Secondly, the
+%% "bandpass" images (fineN) do not segregate information according to
+%% orientation.
+
+%% There are other varieties of pyramid.  One type that arose in the
+%% speech coding community is based on a particular pairs of filters
+%% known as a "Quadrature Mirror Filters" or QMFs.  These are closely
+%% related to Wavelets (essentially, they are approximate wavelet
+%% filters).
+
+%% Recall that the Laplacian pyramid is formed by simple hi/low
+%% splitting at each level.  The lowpass band is subsampled by a
+%% factor of 2, but the highpass band is NOT subsampled.  In the QMF
+%% pyramid, we apply two filters (hi- and lo- pass) and subsample BOTH
+%% by a factor of 2, thus eliminating the excess coefficients of the
+%% Laplacian pyramid.
+
+%% The two filters must have a specific relationship to each
+%% other. In particular, let n be an index for the filter samples.
+%% The highpass filter may be constructed from the lowpass filter by
+%% (1) modulating (multiplying) by (-1)^n (equivalent to shifting by
+%% pi in the Fourier domain), (2) flipping (i.e., reversing the order
+%% of the taps), (3) spatially shifting by one sample.  Try to
+%% convince yourself that the resulting filters will always be
+%% orthogonal to each other (i.e., their inner products will be zero)
+%% when shifted by any multiple of two.
+
+%% The function modulateFlip performs the first two of these operations.  The
+%% third (spatial shifting) step is built into the convolution code.
+flo = namedFilter('qmf9')';
+fhi = modulateFlip(flo)';
+subplot(2,1,1); lplot(flo); axis([0 10 -0.5 1.0]); title('lowpass');
+subplot(2,1,2); lplot(fhi); axis([0 10 -0.5 1.0]); title('highpass');
+
+%% In the Fourier domain, these filters are (approximately)
+%% "power-complementary": the sum of their squared power spectra is
+%% (approximately) a constant.  But note that neither is a perfect
+%% bandlimiter (i.e., a sinc function), and thus subsampling by a
+%% factor of 2 will cause aliasing in each of the subbands.  See below
+%% for a discussion of the effect of this aliasing.
+
+%% Plot the two frequency responses:
+freq = pi*[-32:31]/32;
+subplot(2,1,1);
+plot(freq,fftshift(abs(fft(flo,64))),'--',freq,fftshift(abs(fft(fhi,64))),'-');
+axis([-pi pi 0 1.5]); title('FFT magnitudes');
+subplot(2,1,2);
+plot(freq,fftshift(abs(fft(flo,64)).^2)+fftshift(abs(fft(fhi,64)).^2));
+axis([-pi pi 0 2.2]); title('Sum of squared magnitudes');
+
+%% We can split an input signal into two bands as follows:
+sig = mkFract([1,64],1.6);
+subplot(2,1,1); showIm(sig,'auto1','auto','sig');
+lo1 = corrDn(sig,flo,'reflect1',[1 2],[1 1]);
+hi1 = corrDn(sig,fhi,'reflect1',[1 2],[1 2]);
+subplot(2,1,2); 
+showIm(lo1,'auto1','auto','low and high bands'); hold on; plot(hi1,'--r'); hold off; 
+
+%% Notice that the two subbands are half the size of the original
+%% image, due to the subsampling by a factor of 2.  One subtle point:
+%% the highpass and lowpass bands are subsampled on different
+%% lattices: the lowpass band retains the odd-numbered samples and the
+%% highpass band retains the even-numbered samples.  This was the
+%% 1-sample shift relating the high and lowpass kernels (mentioned
+%% above).  We've used the 'reflect1' to handle boundaries, which
+%% works properly for symmetric odd-length QMFs.
+
+%% We can reconstruct the original image by interpolating these two subbands
+%% USING THE SAME FILTERS:
+reconlo = upConv(lo1,flo,'reflect1',[1 2]);
+reconhi = upConv(hi1,fhi,'reflect1',[1 2],[1 2]);
+subplot(2,1,2); showIm(reconlo+reconhi,'auto1','auto','reconstructed');
+imStats(sig,reconlo+reconhi);
+
+%% We have described an INVERTIBLE linear transform that maps an input
+%% image to the two images lo1 and hi1.  The inverse transformation
+%% maps these two images to the result.  This is depicted graphically
+%% with a system diagram:
+%%
+%% IM ---> flo/down2 --> LO1 --> up2/flo --> add --> RECON
+%%     |                                      ^
+%%     |                                      |
+%%     |                                      |
+%%      -> fhi/down2 --> HI1 --> up2/fhi ----- 
+%% 
+%% Note that the number of samples in the representation (i.e., total
+%% samples in LO1 and HI1) is equal to the number of samples in the
+%% original IM.  Thus, this representation is exactly COMPLETE, or
+%% "critically sampled".
+
+%% So we've fixed one of the problems that we had with Laplacian
+%% pyramid.  But the system diagram above places strong constraints on
+%% the filters.  In particular, for these filters the reconstruction
+%% is no longer perfect.  Turns out there are NO
+%% perfect-reconstruction symmetric filters that are
+%% power-complementary, except for the trivial case [1] and the
+%% nearly-trivial case [1 1]/sqrt(2).
+
+%% Let's consider the projection functions of this 2-band splitting
+%% operation.  We can construct these by applying the transform to
+%% impulse input signals, for all possible impulse locations.  The
+%% rows of the following matrix are the projection functions for each
+%% coefficient in the transform.
+M = [corrDn(eye(32),flo','circular',[1 2]), ...
+     corrDn(eye(32),fhi','circular',[1 2],[1 2])]';
+clf; showIm(M,'auto1','auto','M');
+
+%% The transform matrix is composed of two sub-matrices.  The top half
+%% contains the lowpass kernel, shifted by increments of 2 samples.
+%% The bottom half contains the highpass.  Now we compute the inverse
+%% of this matrix: 
+M_inv = inv(M);
+showIm(M_inv,'auto1','auto','M_inv');
+
+%% The inverse is (very close to) the transpose of the original
+%% matrix!  In other words, the transform is orthonormal.
+imStats(M_inv',M);
+
+%% This also points out a nice relationship between the corrDn and
+%% upConv functions, and the matrix representation.  corrDn is
+%% equivalent to multiplication by a matrix with copies of the filter
+%% on the ROWS, translated in multiples of the downsampling factor.
+%% upConv is equivalent to multiplication by a matrix with copies of
+%% the filter on the COLUMNS, translated by the upsampling factor.
+
+%% As in the Laplacian pyramid, we can recursively apply this QMF 
+%% band-splitting operation to the lowpass band:
+lo2 = corrDn(lo1,flo,'reflect1',[1 2]);
+hi2 = corrDn(lo1,fhi,'reflect1',[1 2],[1 2]);
+
+%% The representation of the original signal is now comprised of the
+%% three subbands {hi1, hi2, lo2} (we don't hold onto lo1, because it
+%% can be reconstructed from lo2 and hi2).  Note that hi1 is at 1/2
+%% resolution, and hi2 and lo2 are at 1/4 resolution: The total number
+%% of samples in these three subbands is thus equal to the number of
+%% samples in the original signal.
+imnames=['hi1'; 'hi2'; 'lo2'];
+for bnum=1:3
+  band = eval(imnames(bnum,:));
+  subplot(3,1,bnum); showIm(band); ylabel(imnames(bnum,:));
+  axis([1 size(band,2) 1.1*min(lo2) 1.1*max(lo2)]);
+end
+
+%% Reconstruction proceeds as with the Laplacian pyramid: combine lo2 and hi2
+%% to reconstruct lo1, which is then combined with hi1 to reconstruct the
+%% original signal:
+recon_lo1 = upConv(hi2,fhi,'reflect1',[1 2],[1 2]) + ...
+            upConv(lo2,flo,'reflect1',[1 2],[1 1]);
+reconstructed = upConv(hi1,fhi,'reflect1',[1 2],[1 2]) + ...
+                upConv(recon_lo1,flo,'reflect1',[1 2],[1 1]);
+imStats(sig,reconstructed);
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%%% FUNCTIONS for CONSTRUCTING/MANIPULATING QMF/Wavelet PYRAMIDS
+
+%% To make things easier, we have bundled these qmf operations and
+%% data structures into an object in MATLAB.
+
+sig = mkFract([1 64], 1.5);
+[pyr,pind] = buildWpyr(sig);
+showWpyr(pyr,pind);
+
+nbands = size(pind,1);
+for b = 1:nbands
+  subplot(nbands,1,b); lplot(pyrBand(pyr,pind,b));
+end
+        
+res = reconWpyr(pyr,pind);
+imStats(sig,res);
+
+%% Now for 2D, we use separable filters.  There are 4 ways to apply the two 
+%% filters to the input image (followed by the relavent subsampling operation):
+%%   (1) lowpass in both x and y
+%%   (2) lowpass in x and highpass in y 
+%%   (3) lowpass in y and highpass in x
+%%   (4) highpass in both x and y.  
+%% The pyramid is built by recursively subdividing the first of these bands
+%% into four new subbands.
+
+%% First, we'll take a look at some of the basis functions.
+sz = 40;
+zim = zeros(sz);
+flo = 'qmf9'; edges = 'reflect1';
+[pyr,pind] = buildWpyr(zim);
+
+% Put an  impulse into the middle of each band:
+for lev=1:size(pind,1)
+  mid = sum(prod(pind(1:lev-1,:)'));
+  mid = mid + floor(pind(lev,2)/2)*pind(lev,1) + floor(pind(lev,1)/2) + 1;
+  pyr(mid,1) = 1;
+end
+
+% And take a look at the reconstruction of each band:
+for lnum=1:wpyrHt(pind)+1
+  for bnum=1:3
+    subplot(wpyrHt(pind)+1,3,(wpyrHt(pind)+1-lnum)*3+bnum);
+    showIm(reconWpyr(pyr, pind, flo, edges, lnum, bnum),'auto1',2,0);
+  end
+end
+
+%% Note that the first column contains horizontally oriented basis functions at
+%% different scales.  The second contains vertically oriented basis functions.
+%% The third contains both diagonals (a checkerboard pattern).  The bottom row
+%% shows (3 identical images of) a lowpass basis function.
+
+%% Now look at the corresponding Fourier transform magnitudes (these
+%% are plotted over the frequency range [-pi, pi] ):
+nextFig(2,1);
+freq = 2 * pi * [-sz/2:(sz/2-1)]/sz;
+for lnum=1:wpyrHt(pind)+1
+  for bnum=1:3
+    subplot(wpyrHt(pind)+1,3,(wpyrHt(pind)+1-lnum)*3+bnum);
+    basisFn = reconWpyr(pyr, pind, flo, edges, lnum, bnum);
+    basisFmag = fftshift(abs(fft2(basisFn,sz,sz)));
+    imagesc(freq,freq,basisFmag);
+    axis('square'); axis('xy'); colormap('gray');
+  end
+end
+nextFig(2,-1);
+
+%% The filters at a given scale sum to a squarish annular region:
+sumSpectra = zeros(sz);
+lnum = 2;
+for bnum=1:3
+  basisFn = reconWpyr(pyr, pind, flo, edges, lnum, bnum);
+  basisFmag = fftshift(abs(fft2(basisFn,sz,sz)));
+  sumSpectra = basisFmag.^2 + sumSpectra;
+end
+clf; imagesc(freq,freq,sumSpectra); axis('square'); axis('xy'); title('one scale');
+
+%% Now decompose an image:
+[pyr,pind] = buildWpyr(im);
+
+%% View all of the subbands (except lowpass), scaled to be the same size
+%% (requires a big figure window):
+nlevs = wpyrHt(pind);
+for lnum=1:nlevs
+  for bnum=1:3
+    subplot(nlevs,3,(lnum-1)*3+bnum); 
+    showIm(wpyrBand(pyr,pind,lnum,bnum), 'auto2', 2^(lnum+imSubSample-2));
+  end
+end
+
+%% In addition to the bands shown above, there's a lowpass residual:
+nextFig(2,1);
+clf; showIm(pyrLow(pyr,pind));
+nextFig(2,-1);
+
+% Alternatively, display the pyramid with the subbands shown at their
+% correct relative sizes:
+clf; showWpyr(pyr, pind);
+
+%% The reconWpyr function can be used to reconstruct the entire pyramid:
+reconstructed = reconWpyr(pyr,pind);
+imStats(im,reconstructed);
+
+%% As with Laplacian pyramids, you can specify sub-levels and subbands
+%% to be included in the reconstruction.  For example:
+clf
+showIm(reconWpyr(pyr,pind,'qmf9','reflect1',[1:wpyrHt(pind)],[1]));  %Horizontal only
+showIm(reconWpyr(pyr,pind,'qmf9','reflect1',[2,3])); %two middle scales
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%%% PERFECT RECONSTRUCTION: HAAR AND DEBAUCHIES WAVELETS
+
+%% The symmetric QMF filters used above are not perfectly orthogonal.
+%% In fact, it's impossible to construct a symmetric filter of size
+%% greater than 2 that is perfectly orthogonal to shifted copies
+%% (shifted by multiples of 2) of itself.  For example, consider a
+%% symmetric kernel of length 3.  Shift by two and the right end of
+%% the original kernel is aligned with the left end of the shifted
+%% one.  Thus, the inner product of these two will be the square of
+%% the end tap, which will be non-zero.
+
+%% However, one can easily create wavelet filters of length 2 that
+%% will do the job.  This is the oldest known wavelet, known as the
+%% "Haar".  The two kernels are [1,1]/sqrt(2) and [1,-1]/sqrt(2).
+%% These are trivially seen to be orthogonal to each other, and shifts
+%% by multiples of two are also trivially orthogonal.  The projection
+%% functions of the Haar transform are in the rows of the following
+%% matrix, constructed by applying the transform to impulse input
+%% signals, for all possible impulse locations:
+
+haarLo = namedFilter('haar')
+haarHi = modulateFlip(haarLo)
+subplot(2,1,1); lplot(haarLo); axis([0 3 -1 1]); title('lowpass');
+subplot(2,1,2); lplot(haarHi); axis([0 3 -1 1]); title('highpass');
+
+M = [corrDn(eye(32), haarLo, 'reflect1', [2 1], [2 1]); ...
+    corrDn(eye(32), haarHi, 'reflect1', [2 1], [2 1])];
+clf; showIm(M)
+showIm(M*M') %identity!
+
+%% As before, the filters are power-complementary (although the
+%% frequency isolation is rather poor, and thus the subbands will be
+%% heavily aliased):
+plot(pi*[-32:31]/32,abs(fft(haarLo,64)).^2,'--',...
+     pi*[-32:31]/32,abs(fft(haarHi,64)).^2,'-');
+
+sig = mkFract([1,64],0.5);
+[pyr,pind] = buildWpyr(sig,4,'haar','reflect1');
+showWpyr(pyr,pind);
+
+%% check perfect reconstruction:
+res = reconWpyr(pyr,pind, 'haar', 'reflect1');
+imStats(sig,res)
+
+%% If you want perfect reconstruction, but don't like the Haar
+%% transform, there's another option: drop the symmetry requirement.
+%% Ingrid Daubechies developed one of the earliest sets of such
+%% perfect-reconstruction wavelets.  The simplest of these is of
+%% length 4:
+
+daub_lo = namedFilter('daub2');
+daub_hi = modulateFlip(daub_lo);
+
+%% The daub_lo filter is constructed to be orthogonal to 2shifted
+%% copy of itself.  For example:
+[daub_lo;0;0]'*[0;0;daub_lo]
+
+M = [corrDn(eye(32), daub_lo, 'circular', [2 1], [2 1]); ...
+    corrDn(eye(32), daub_hi, 'circular', [2 1], [2 1])];
+clf; showIm(M)
+showIm(M*M') % identity!
+
+%% Again, they're power complementary:
+plot(pi*[-32:31]/32,abs(fft(daub_lo,64)).^2,'--',...
+     pi*[-32:31]/32,abs(fft(daub_hi,64)).^2,'-');
+ 
+%% The sum of the power spectra is again flat
+plot(pi*[-32:31]/32,...
+    fftshift(abs(fft(daub_lo,64)).^2)+fftshift(abs(fft(daub_hi,64)).^2));
+
+%% Make a pyramid using the same code as before (except that we can't
+%% use reflected boundaries with asymmetric filters):
+[pyr,pind] = buildWpyr(sig, maxPyrHt(size(sig),size(daub_lo)), daub_lo, 'circular');
+showWpyr(pyr,pind,'indep1');
+
+res = reconWpyr(pyr,pind, daub_lo,'circular');
+imStats(sig,res);
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%%% ALIASING IN WAVELET TRANSFORMS
+
+%% All of these orthonormal pyramid/wavelet transforms have a lot
+%% of aliasing in the subbands.  You can see that in the frequency
+%% response plots since the frequency response of each filter
+%% covers well more than half the frequency domain.  The aliasing
+%% can have serious consequences...
+
+%% Get one of the basis functions of the 2D Daubechies wavelet transform:
+[pyr,pind] = buildWpyr(zeros(1,64),4,daub_lo,'circular');
+lev = 3;
+pyr(1+sum(pind(1:lev-1,2))+pind(lev,2)/2,1) = 1;
+sig = reconWpyr(pyr,pind, daub_lo,'circular');
+clf; lplot(sig)
+
+%% Since the basis functions are orthonormal, building a pyramid using this
+%% input will yield a single non-zero coefficient.
+[pyr,pind] = buildWpyr(sig, 4, daub_lo, 'circular');
+figure(1);
+nbands = size(pind,1)
+for b=1:nbands
+  subplot(nbands,1,b); lplot(pyrBand(pyr,pind,b));
+  axis([1 size(pyrBand(pyr,pind,b),2) -0.3 1.3]);
+end
+
+%% Now shift the input by one sample and re-build the pyramid.
+shifted_sig = [0,sig(1:size(sig,2)-1)];
+[spyr,spind] = buildWpyr(shifted_sig, 4, daub_lo, 'circular');
+
+%% Plot each band of the unshifted and shifted decomposition
+nextFig(2);
+nbands = size(spind,1)
+for b=1:nbands
+  subplot(nbands,1,b); lplot(pyrBand(spyr,spind,b));
+  axis([1 size(pyrBand(spyr,spind,b),2) -0.3 1.3]);
+end
+nextFig(2,-1);
+
+%% In the third band, we expected the coefficients to move around
+%% because the signal was shifted.  But notice that in the original
+%% signal decomposition, the other bands were filled with zeros.
+%% After the shift, they have significant content.  Although these
+%% subbands are supposed to represent information at different scales,
+%% their content also depends on the relative POSITION of the input
+%% signal.
+
+%% This problem is not unique to the Daubechies transform.  The same
+%% is true for the QMF transform.  Try it...  In fact, the same kind
+%% of problem occurs for almost any orthogonal pyramid transform (the
+%% only exception is the limiting case in which the filter is a sinc
+%% function).
+
+%% Orthogonal pyramid transforms are not shift-invariant.  Although
+%% orthogonality may be an important property for some applications
+%% (e.g., data compression), orthogonal pyramid transforms are
+%% generally not so good for image analysis.
+
+%% The overcompleteness of the Laplacian pyramid turns out to be a
+%% good thing in the end.  By using an overcomplete representation
+%% (and by choosing the filters properly to avoid aliasing as much as
+%% possible), you end up with a representation that is useful for
+%% image analysis.
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%%% The "STEERABLE PYRAMID" 
+
+%% The steerable pyramid is a multi-scale representation that is
+%% translation-invariant, but that also includes representation of
+%% orientation.  Furthermore, the representation of orientation is
+%% designed to be rotation-invariant. The basis/projection functions
+%% are oriented (steerable) filters, localized in space and frequency.
+%% It is overcomplete to avoid aliasing.  And it is "self-inverting"
+%% (like the QMF/Wavelet transform): the projection functions and 
+%% basis functions are identical.  The mathematical phrase for a 
+%% transform obeying this property is "tight frame".
+
+%% The system diagram for the steerable pyramid (described in the
+%% reference given below) is as follows:
+%
+% IM ---> fhi0 -----------------> H0 ---------------- fhi0 ---> RESULT
+%     |                                                     |
+%     |                                                     |
+%     |-> flo0 ---> fl1/down2 --> L1 --> up2/fl1 ---> flo0 -|
+%               |                                 |
+%               |----> fb0 -----> B0 ----> fb0 ---|
+%               |                                 |
+%               |----> fb1 -----> B1 ----> fb1 ---|
+%               .                                 .
+%               .                                 .
+%               |----> fbK -----> BK ----> fbK ---|
+%
+%% The filters {fhi0,flo0} are used to initially split the image into
+%% a highpass residual band H0 and a lowpass subband.  This lowpass
+%% band is then split into a low(er)pass band L1 and K+1 oriented
+%% subbands {B0,B1,...,BK}.  The representatation is substantially
+%% overcomplete.  The pyramid is built by recursively splitting the
+%% lowpass band (L1) using the inner portion of the diagram (i.e.,
+%% using the filters {fl1,fb0,fb1,...,fbK}).  The resulting transform is
+%% overcomplete by a factor of 4k/3.
+
+%% The scale tuning of the filters is constrained by the recursive
+%% system diagram.  The orientation tuning is constrained by requiring
+%% the property of steerability.  A set of filters form a steerable
+%% basis if they 1) are rotated copies of each other, and 2) a copy of
+%% the filter at any orientation may be computed as a linear
+%% combination of the basis filters.  The simplest examples of
+%% steerable filters is a set of N+1 Nth-order directional
+%% derivatives.
+
+%% Choose a filter set (options are 'sp0Filters', 'sp1Filters',
+%% 'sp3Filters', 'sp5Filters'):
+filts = 'sp3Filters';
+[lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filts);
+fsz = round(sqrt(size(bfilts,1))); fsz =  [fsz fsz];
+nfilts = size(bfilts,2);
+nrows = floor(sqrt(nfilts));
+
+%% Look at the oriented bandpass filters:
+for f = 1:nfilts
+  subplot(nrows,ceil(nfilts/nrows),f);
+  showIm(conv2(reshape(bfilts(:,f),fsz),lo0filt));
+end
+
+%% Try "steering" to a new orientation (new_ori in degrees):
+new_ori = 360*rand(1)
+clf; showIm(conv2(reshape(steer(bfilts, new_ori*pi/180 ), fsz), lo0filt));
+
+%% Look at Fourier transform magnitudes:
+lo0 = fftshift(abs(fft2(lo0filt,64,64)));
+fsum = zeros(size(lo0));
+for f = 1:size(bfilts,2)
+  subplot(nrows,ceil(nfilts/nrows),f);
+  flt = reshape(bfilts(:,f),fsz);
+  freq = lo0 .* fftshift(abs(fft2(flt,64,64)));
+  fsum = fsum + freq.^2;
+  showIm(freq);
+end
+
+%% The filters sum to a smooth annular ring:
+clf; showIm(fsum);
+
+%% build a Steerable pyramid:
+[pyr,pind] = buildSpyr(im, 4-imSubSample, filts);
+ 
+%% Look at first (vertical) bands, different scales:
+for s = 1:min(4,spyrHt(pind))
+  band = spyrBand(pyr,pind,s,1);
+  subplot(2,2,s); showIm(band);
+end
+
+%% look at all orientation bands at one level (scale):
+for b = 1:spyrNumBands(pind)
+  band = spyrBand(pyr,pind,1,b);
+  subplot(nrows,ceil(nfilts/nrows),b);
+  showIm(band);
+end
+
+%% To access the high-pass and low-pass bands:
+low = pyrLow(pyr,pind);
+showIm(low);
+high = spyrHigh(pyr,pind);
+showIm(high);
+
+%% Display the whole pyramid (except for the highpass residual band),
+%% with images shown at proper relative sizes:
+showSpyr(pyr,pind);
+
+%% Spin a level of the pyramid, interpolating (steering to)
+%% intermediate orienations:
+
+[lev,lind] = spyrLev(pyr,pind,2);
+lev2 = reshape(lev,prod(lind(1,:)),size(bfilts,2));
+figure(1); subplot(1,1,1); showIm(spyrBand(pyr,pind,2,1));
+M = moviein(16);
+for frame = 1:16
+  steered_im = steer(lev2, 2*pi*(frame-1)/16, harmonics, steermtx);
+  showIm(reshape(steered_im, lind(1,:)),'auto2');
+  M(:,frame) = getframe;
+end
+
+%% Show the movie 3 times:
+movie(M,3);
+
+%% Reconstruct.  Note that the filters are not perfect, although they are good
+%% enough for most applications.
+res = reconSpyr(pyr, pind, filts); 
+showIm(im + i * res);
+imStats(im,res);
+
+%% As with previous pyramids, you can select subsets of the levels
+%% and orientation bands to be included in the reconstruction.  For example:
+
+%% All levels (including highpass and lowpass residuals), one orientation:
+clf; showIm(reconSpyr(pyr,pind,filts,'reflect1','all', [1]));
+
+%% Without the highpass and lowpass:
+clf; showIm(reconSpyr(pyr,pind,filts,'reflect1',[1:spyrHt(pind)], [1]));
+
+%% We also provide an implementation of the Steerable pyramid in the
+%% Frequency domain.  The advantages are perfect-reconstruction
+%% (within floating-point error), and any number of orientation
+%% bands.  The disadvantages are that it is typically slower, and the
+%% boundary handling is always circular.
+
+[pyr,pind] = buildSFpyr(im,4,4); % 4 levels, 5 orientation bands
+showSpyr(pyr,pind);
+res = reconSFpyr(pyr,pind);
+imStats(im,res);  % nearly perfect
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% The steerable pyramid transform given above is described in:
+%
+%   E P Simoncelli and W T Freeman. 
+%   The Steerable Pyramid: A Flexible Architecture for Multi-Scale 
+%   Derivative Computation.  IEEE Second Int'l Conf on Image Processing. 
+%   Washington DC,  October 1995.
+%
+% Online access:
+% Abstract:  http://www.cis.upenn.edu/~eero/ABSTRACTS/simoncelli95b-abstract.html
+% Full (PostScript):  ftp://ftp.cis.upenn.edu/pub/eero/simoncelli95b.ps.Z
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%% Local Variables:
+%% buffer-read-only: t 
+%% End:
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/binomialFilter.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/binomialFilter.m
new file mode 100755
index 0000000..e5670c7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/binomialFilter.m
@@ -0,0 +1,18 @@
+% KERNEL = binomialFilter(size)
+%
+% Returns a vector of binomial coefficients of order (size-1) .
+
+% Eero Simoncelli, 2/97.
+
+function [kernel] = binomialFilter(sz)
+
+if (sz < 2)
+  error('size argument must be larger than 1');
+end
+
+kernel = [0.5 0.5]';
+
+for n=1:sz-2
+  kernel = conv([0.5 0.5]', kernel);
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blur.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blur.m
new file mode 100755
index 0000000..f993d09
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blur.m
@@ -0,0 +1,28 @@
+% RES = blur(IM, LEVELS, FILT)
+%
+% Blur an image, by filtering and downsampling LEVELS times
+% (default=1), followed by upsampling and filtering LEVELS times.  The
+% blurring is done with filter kernel specified by FILT (default =
+% 'binom5'), which can be a string (to be passed to namedFilter), a
+% vector (applied separably as a 1D convolution kernel in X and Y), or
+% a matrix (applied as a 2D convolution kernel).  The downsampling is
+% always by 2 in each direction.
+
+% Eero Simoncelli, 3/04.
+
+function res = blur(im, nlevs, filt)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('nlevs') ~= 1) 
+  nlevs = 1;
+end
+
+if (exist('filt') ~= 1) 
+  filt = 'binom5';
+end
+
+%------------------------------------------------------------
+
+res = upBlur(blurDn(im,nlevs,filt));
\ No newline at end of file
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blurDn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blurDn.m
new file mode 100755
index 0000000..8120c04
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/blurDn.m
@@ -0,0 +1,59 @@
+% RES = blurDn(IM, LEVELS, FILT)
+%
+% Blur and downsample an image.  The blurring is done with filter
+% kernel specified by FILT (default = 'binom5'), which can be a string
+% (to be passed to namedFilter), a vector (applied separably as a 1D
+% convolution kernel in X and Y), or a matrix (applied as a 2D
+% convolution kernel).  The downsampling is always by 2 in each
+% direction.
+%
+% The procedure is applied recursively LEVELS times (default=1).
+
+% Eero Simoncelli, 3/97.
+
+function res = blurDn(im, nlevs, filt)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('nlevs') ~= 1) 
+  nlevs = 1;
+end
+
+if (exist('filt') ~= 1) 
+  filt = 'binom5';
+end
+
+%------------------------------------------------------------
+
+if isstr(filt)
+  filt = namedFilter(filt);
+end  
+
+filt = filt/sum(filt(:));
+
+if nlevs > 1
+  im = blurDn(im,nlevs-1,filt);
+end
+
+if (nlevs >= 1)
+  if (any(size(im)==1))
+    if (~any(size(filt)==1))
+      error('Cant  apply 2D filter to 1D signal');
+    end
+    if (size(im,2)==1)
+      filt = filt(:);
+    else
+      filt = filt(:)';
+    end
+    res = corrDn(im,filt,'reflect1',(size(im)~=1)+1);
+  elseif (any(size(filt)==1))
+    filt = filt(:);
+    res = corrDn(im,filt,'reflect1',[2 1]);
+    res = corrDn(res,filt','reflect1',[1 2]);
+  else
+    res = corrDn(im,filt,'reflect1',[2 2]);
+  end
+else
+  res = im;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildGpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildGpyr.m
new file mode 100755
index 0000000..3f3d07b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildGpyr.m
@@ -0,0 +1,82 @@
+% [PYR, INDICES] = buildGpyr(IM, HEIGHT, FILT, EDGES)
+%
+% Construct a Gaussian pyramid on matrix IM.
+%
+% HEIGHT (optional) specifies the number of pyramid levels to build. Default
+% is 1+maxPyrHt(size(IM),size(FILT)). 
+% You can also specify 'auto' to use this value.
+%
+% FILT (optional) can be a string naming a standard filter (see
+% namedFilter), or a vector which will be used for (separable)
+% convolution.  Default = 'binom5'.  EDGES specifies edge-handling, and
+% defaults to 'reflect1' (see corrDn).
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+
+% Eero Simoncelli, 6/96.
+
+function [pyr,pind] = buildGpyr(im, ht, filt, edges)
+
+if (nargin < 1)
+  error('First argument (IM) is required');
+end
+
+im_sz = size(im);
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('filt') ~= 1)
+  filt = 'binom5';
+end
+
+if isstr(filt)
+  filt = namedFilter(filt);
+end
+
+if ( (size(filt,1) > 1) & (size(filt,2) > 1) )
+  error('FILT should be a 1D filter (i.e., a vector)');
+else
+  filt = filt(:);
+end
+
+max_ht = 1 + maxPyrHt(im_sz, size(filt,1));
+if ( (exist('ht') ~= 1) | (ht == 'auto') )
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+%------------------------------------------------------------
+
+if (ht <= 1)
+
+  pyr = im(:);
+  pind = im_sz;
+
+else
+
+  if (im_sz(2) == 1)
+    lo2 = corrDn(im, filt, edges, [2 1], [1 1]);
+  elseif (im_sz(1) == 1)
+    lo2 = corrDn(im, filt', edges, [1 2], [1 1]);
+  else
+    lo = corrDn(im, filt', edges, [1 2], [1 1]);
+    lo2 = corrDn(lo, filt, edges, [2 1], [1 1]);
+  end
+  
+  [npyr,nind] = buildGpyr(lo2, ht-1, filt, edges);
+
+  pyr = [im(:); npyr];
+  pind = [im_sz; nind];
+  
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildLpyr.m
new file mode 100755
index 0000000..facb0f3
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildLpyr.m
@@ -0,0 +1,109 @@
+% [PYR, INDICES] = buildLpyr(IM, HEIGHT, FILT1, FILT2, EDGES)
+%
+% Construct a Laplacian pyramid on matrix (or vector) IM.
+%
+% HEIGHT (optional) specifies the number of pyramid levels to build. Default
+% is 1+maxPyrHt(size(IM),size(FILT)).  You can also specify 'auto' to
+% use this value.
+%
+% FILT1 (optional) can be a string naming a standard filter (see
+% namedFilter), or a vector which will be used for (separable)
+% convolution.  Default = 'binom5'.  FILT2 specifies the "expansion"
+% filter (default = filt1).  EDGES specifies edge-handling, and
+% defaults to 'reflect1' (see corrDn).
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+
+% Eero Simoncelli, 6/96.
+
+function [pyr,pind] = buildLpyr(im, ht, filt1, filt2, edges)
+
+if (nargin < 1)
+  error('First argument (IM) is required');
+end
+
+im_sz = size(im);
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('filt1') ~= 1)
+  filt1 = 'binom5';
+end
+ 
+if isstr(filt1)
+  filt1 = namedFilter(filt1);
+end
+
+if ( (size(filt1,1) > 1) & (size(filt1,2) > 1) )
+  error('FILT1 should be a 1D filter (i.e., a vector)');
+else
+  filt1 = filt1(:);
+end
+
+if (exist('filt2') ~= 1)
+  filt2 = filt1;
+end
+
+if isstr(filt2)
+  filt2 = namedFilter(filt2);
+end
+
+if ( (size(filt2,1) > 1) & (size(filt2,2) > 1) )
+  error('FILT2 should be a 1D filter (i.e., a vector)');
+else
+  filt2 = filt2(:);
+end
+
+max_ht = 1 + maxPyrHt(im_sz, max(size(filt1,1), size(filt2,1)));
+if ( (exist('ht') ~= 1) | (ht == 'auto') )
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+%------------------------------------------------------------
+
+if (ht <= 1)
+
+  pyr = im(:);
+  pind = im_sz;
+
+else
+
+  if (im_sz(2) == 1)
+    lo2 = corrDn(im, filt1, edges, [2 1], [1 1]);
+  elseif (im_sz(1) == 1)
+    lo2 = corrDn(im, filt1', edges, [1 2], [1 1]);
+  else
+    lo = corrDn(im, filt1', edges, [1 2], [1 1]);
+    int_sz = size(lo);
+    lo2 = corrDn(lo, filt1, edges, [2 1], [1 1]);
+  end
+
+  [npyr,nind] = buildLpyr(lo2, ht-1, filt1, filt2, edges);
+
+  if (im_sz(1) == 1)
+    hi2 = upConv(lo2, filt2', edges, [1 2], [1 1], im_sz);
+  elseif (im_sz(2) == 1)
+    hi2 = upConv(lo2, filt2, edges, [2 1], [1 1], im_sz);
+  else
+    hi = upConv(lo2, filt2, edges, [2 1], [1 1], int_sz);
+    hi2 = upConv(hi, filt2', edges, [1 2], [1 1], im_sz);
+  end
+
+  hi2 = im - hi2;
+
+  pyr = [hi2(:); npyr];
+  pind = [im_sz; nind];
+
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyr.m
new file mode 100755
index 0000000..101b6d2
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyr.m
@@ -0,0 +1,90 @@
+% [PYR, INDICES, STEERMTX, HARMONICS] = buildSCFpyr(IM, HEIGHT, ORDER, TWIDTH)
+%
+% This is a modified version of buildSFpyr, that constructs a
+% complex-valued steerable pyramid  using Hilbert-transform pairs
+% of filters.  Note that the imaginary parts will *not* be steerable.
+%
+% To reconstruct from this representation, either call reconSFpyr
+% on the real part of the pyramid, *or* call reconSCFpyr which will
+% use both real and imaginary parts (forcing analyticity).
+%
+% Description of this transform appears in: Portilla & Simoncelli,
+% Int'l Journal of Computer Vision, 40(1):49-71, Oct 2000.
+% Further information: http://www.cns.nyu.edu/~eero/STEERPYR/
+
+% Original code: Eero Simoncelli, 5/97.
+% Modified by Javier Portilla to return complex (quadrature pair) channels,
+% 9/97.
+
+function [pyr,pind,steermtx,harmonics] = buildSCFpyr(im, ht, order, twidth)
+
+%-----------------------------------------------------------------
+%% DEFAULTS:
+
+max_ht = floor(log2(min(size(im)))) - 2;
+
+if (exist('ht') ~= 1)
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+if (exist('order') ~= 1)
+  order = 3;
+elseif ((order > 15)  | (order < 0))
+  fprintf(1,'Warning: ORDER must be an integer in the range [0,15]. Truncating.\n');
+  order = min(max(order,0),15);
+else
+  order = round(order);
+end
+nbands = order+1;
+
+if (exist('twidth') ~= 1)
+  twidth = 1;
+elseif (twidth <= 0)
+  fprintf(1,'Warning: TWIDTH must be positive.  Setting to 1.\n');
+  twidth = 1;
+end
+
+%-----------------------------------------------------------------
+%% Steering stuff:
+
+if (mod((nbands),2) == 0)
+  harmonics = [0:(nbands/2)-1]'*2 + 1;
+else
+  harmonics = [0:(nbands-1)/2]'*2;
+end
+
+steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even');
+
+%-----------------------------------------------------------------
+
+dims = size(im);
+ctr = ceil((dims+0.5)/2);
+
+[xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ...
+    ([1:dims(1)]-ctr(1))./(dims(1)/2) );
+angle = atan2(yramp,xramp);
+log_rad = sqrt(xramp.^2 + yramp.^2);
+log_rad(ctr(1),ctr(2)) =  log_rad(ctr(1),ctr(2)-1);
+log_rad  = log2(log_rad);
+
+%% Radial transition function (a raised cosine in log-frequency):
+[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
+Yrcos = sqrt(Yrcos);
+
+YIrcos = sqrt(1.0 - Yrcos.^2);
+lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+imdft = fftshift(fft2(im));
+lo0dft =  imdft .* lo0mask;
+
+[pyr,pind] = buildSCFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands);
+
+hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+hi0dft =  imdft .* hi0mask;
+hi0 = ifft2(ifftshift(hi0dft));
+
+pyr = [real(hi0(:)) ; pyr];
+pind = [size(hi0); pind];
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyrLevs.m
new file mode 100755
index 0000000..bd75695
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSCFpyrLevs.m
@@ -0,0 +1,73 @@
+% [PYR, INDICES] = buildSCFpyrLevs(LODFT, LOGRAD, XRCOS, YRCOS, ANGLE, HEIGHT, NBANDS)
+%
+% Recursive function for constructing levels of a steerable pyramid.  This
+% is called by buildSCFpyr, and is not usually called directly.
+
+% Original code: Eero Simoncelli, 5/97.
+% Modified by Javier Portilla to generate complex bands in 9/97.
+
+function [pyr,pind] = buildSCFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands);
+
+if (ht <= 0)
+
+  lo0 = ifft2(ifftshift(lodft));
+  pyr = real(lo0(:));
+  pind = size(lo0);
+
+else
+
+  bands = zeros(prod(size(lodft)), nbands);
+  bind = zeros(nbands,2);
+
+%  log_rad = log_rad + 1;
+  Xrcos = Xrcos - log2(2);  % shift origin of lut by 1 octave.
+
+  lutsize = 1024;
+  Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize;  % [-2*pi:pi]
+  order = nbands-1;
+  %% divide by sqrt(sum_(n=0)^(N-1)  cos(pi*n/N)^(2(N-1)) )
+  %% Thanks to Patrick Teo for writing this out :)
+  const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order));
+
+%
+%  Ycosn = sqrt(const) * (cos(Xcosn)).^order;
+%
+  % analityc version: only take one lobe
+  alfa= mod(pi+Xcosn,2*pi)-pi;
+  Ycosn = 2*sqrt(const) * (cos(Xcosn).^order) .* (abs(alfa)<pi/2);
+
+  himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+
+  for b = 1:nbands
+    anglemask = pointOp(angle, Ycosn, Xcosn(1)+pi*(b-1)/nbands, Xcosn(2)-Xcosn(1));
+    banddft = ((-i)^(nbands-1)) .* lodft .* anglemask .* himask;
+    band = ifft2(ifftshift(banddft));
+
+%    bands(:,b) = real(band(:));
+    % analytic version: full complex value
+    bands(:,b)=band(:);
+    bind(b,:)  = size(band);
+  end
+
+  dims = size(lodft);
+  ctr = ceil((dims+0.5)/2);
+  lodims = ceil((dims-0.5)/2);
+  loctr = ceil((lodims+0.5)/2);
+  lostart = ctr-loctr+1;
+  loend = lostart+lodims-1;
+
+  log_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2));
+  angle = angle(lostart(1):loend(1),lostart(2):loend(2));
+  lodft = lodft(lostart(1):loend(1),lostart(2):loend(2));
+  YIrcos = abs(sqrt(1.0 - Yrcos.^2));
+  lomask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+
+  lodft = lomask .* lodft;
+
+  [npyr,nind] = buildSCFpyrLevs(lodft, log_rad, Xrcos, Yrcos, angle, ht-1, nbands);
+
+  pyr = [bands(:); npyr];
+  pind = [bind; nind];
+
+end
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyr.m
new file mode 100755
index 0000000..ae67206
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyr.m
@@ -0,0 +1,102 @@
+% [PYR, INDICES, STEERMTX, HARMONICS] = buildSFpyr(IM, HEIGHT, ORDER, TWIDTH)
+%
+% Construct a steerable pyramid on matrix IM, in the Fourier domain.
+% This is similar to buildSpyr, except that:
+%
+%    + Reconstruction is exact (within floating point errors)
+%    + It can produce any number of orientation bands.
+%    - Typically slower, especially for non-power-of-two sizes.
+%    - Boundary-handling is circular.
+%
+% HEIGHT (optional) specifies the number of pyramid levels to build. Default
+% is maxPyrHt(size(IM),size(FILT));
+%
+% The squared radial functions tile the Fourier plane, with a raised-cosine
+% falloff.  Angular functions are cos(theta-k\pi/(K+1))^K, where K is
+% the ORDER (one less than the number of orientation bands, default= 3).
+%
+% TWIDTH is the width of the transition region of the radial lowpass
+% function, in octaves (default = 1, which gives a raised cosine for
+% the bandpass filters).
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+% See the function STEER for a description of STEERMTX and HARMONICS.
+
+% Eero Simoncelli, 5/97.
+% See http://www.cns.nyu.edu/~eero/STEERPYR/ for more
+% information about the Steerable Pyramid image decomposition.
+
+function [pyr,pind,steermtx,harmonics] = buildSFpyr(im, ht, order, twidth)
+
+%-----------------------------------------------------------------
+%% DEFAULTS:
+
+max_ht = floor(log2(min(size(im)))) - 2;
+
+if (exist('ht') ~= 1)
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+if (exist('order') ~= 1)
+  order = 3;
+elseif ((order > 15)  | (order < 0))
+  fprintf(1,'Warning: ORDER must be an integer in the range [0,15]. Truncating.\n');
+  order = min(max(order,0),15);
+else
+  order = round(order);
+end
+nbands = order+1;
+
+if (exist('twidth') ~= 1)
+  twidth = 1;
+elseif (twidth <= 0)
+  fprintf(1,'Warning: TWIDTH must be positive.  Setting to 1.\n');
+  twidth = 1;
+end
+
+%-----------------------------------------------------------------
+%% Steering stuff:
+
+if (mod((nbands),2) == 0)
+  harmonics = [0:(nbands/2)-1]'*2 + 1;
+else
+  harmonics = [0:(nbands-1)/2]'*2;
+end
+
+steermtx = steer2HarmMtx(harmonics, pi*[0:nbands-1]/nbands, 'even');
+
+%-----------------------------------------------------------------
+
+dims = size(im);
+ctr = ceil((dims+0.5)/2);
+
+[xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ...
+    ([1:dims(1)]-ctr(1))./(dims(1)/2) );
+angle = atan2(yramp,xramp);
+log_rad = sqrt(xramp.^2 + yramp.^2);
+log_rad(ctr(1),ctr(2)) =  log_rad(ctr(1),ctr(2)-1);
+log_rad  = log2(log_rad);
+
+%% Radial transition function (a raised cosine in log-frequency):
+[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
+Yrcos = sqrt(Yrcos);
+
+YIrcos = sqrt(1.0 - Yrcos.^2);
+lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+imdft = fftshift(fft2(im));
+lo0dft =  imdft .* lo0mask;
+
+[pyr,pind] = buildSFpyrLevs(lo0dft, log_rad, Xrcos, Yrcos, angle, ht, nbands);
+
+hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+hi0dft =  imdft .* hi0mask;
+hi0 = ifft2(ifftshift(hi0dft));
+
+pyr = [real(hi0(:)) ; pyr];
+pind = [size(hi0); pind];
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyrLevs.m
new file mode 100755
index 0000000..472d861
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSFpyrLevs.m
@@ -0,0 +1,63 @@
+% [PYR, INDICES] = buildSFpyrLevs(LODFT, LOGRAD, XRCOS, YRCOS, ANGLE, HEIGHT, NBANDS)
+%
+% Recursive function for constructing levels of a steerable pyramid.  This
+% is called by buildSFpyr, and is not usually called directly.
+
+% Eero Simoncelli, 5/97.
+
+function [pyr,pind] = buildSFpyrLevs(lodft,log_rad,Xrcos,Yrcos,angle,ht,nbands);
+
+if (ht <= 0)
+
+  lo0 = ifft2(ifftshift(lodft));
+  pyr = real(lo0(:));
+  pind = size(lo0);
+
+else
+
+  bands = zeros(prod(size(lodft)), nbands);
+  bind = zeros(nbands,2);
+
+%  log_rad = log_rad + 1;
+  Xrcos = Xrcos - log2(2);  % shift origin of lut by 1 octave.
+
+  lutsize = 1024;
+  Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize;  % [-2*pi:pi]
+  order = nbands-1;
+  %% divide by sqrt(sum_(n=0)^(N-1)  cos(pi*n/N)^(2(N-1)) )
+  %% Thanks to Patrick Teo for writing this out :)
+  const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order));
+  Ycosn = sqrt(const) * (cos(Xcosn)).^order;
+  himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+
+  for b = 1:nbands
+    anglemask = pointOp(angle, Ycosn, Xcosn(1)+pi*(b-1)/nbands, Xcosn(2)-Xcosn(1));
+    banddft = ((-sqrt(-1))^(nbands-1)) .* lodft .* anglemask .* himask;
+    band = ifft2(ifftshift(banddft));
+
+    bands(:,b) = real(band(:));
+    bind(b,:)  = size(band);
+  end
+
+  dims = size(lodft);
+  ctr = ceil((dims+0.5)/2);
+  lodims = ceil((dims-0.5)/2);
+  loctr = ceil((lodims+0.5)/2);
+  lostart = ctr-loctr+1;
+  loend = lostart+lodims-1;
+
+  log_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2));
+  angle = angle(lostart(1):loend(1),lostart(2):loend(2));
+  lodft = lodft(lostart(1):loend(1),lostart(2):loend(2));
+  YIrcos = abs(sqrt(1.0 - Yrcos.^2));
+  lomask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+
+  lodft = lomask .* lodft;
+
+  [npyr,nind] = buildSFpyrLevs(lodft, log_rad, Xrcos, Yrcos, angle, ht-1, nbands);
+
+  pyr = [bands(:); npyr];
+  pind = [bind; nind];
+
+end
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyr.m
new file mode 100755
index 0000000..b2bead6
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyr.m
@@ -0,0 +1,61 @@
+% [PYR, INDICES, STEERMTX, HARMONICS] = buildSpyr(IM, HEIGHT, FILTFILE, EDGES)
+%
+% Construct a steerable pyramid on matrix IM.
+%
+% HEIGHT (optional) specifies the number of pyramid levels to build. Default
+% is maxPyrHt(size(IM),size(FILT)). 
+% You can also specify 'auto' to use this value.
+%
+% FILTFILE (optional) should be a string referring to an m-file that
+% returns the rfilters.  (examples: 'sp0Filters', 'sp1Filters',
+% 'sp3Filters','sp5Filters'.  default = 'sp1Filters'). EDGES specifies
+% edge-handling, and defaults to 'reflect1' (see corrDn).
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+% See the function STEER for a description of STEERMTX and HARMONICS.
+
+% Eero Simoncelli, 6/96.
+% See http://www.cis.upenn.edu/~eero/steerpyr.html for more
+% information about the Steerable Pyramid image decomposition.
+
+function [pyr,pind,steermtx,harmonics] = buildSpyr(im, ht, filtfile, edges)
+
+%-----------------------------------------------------------------
+%% DEFAULTS:
+
+if (exist('filtfile') ~= 1)
+  filtfile = 'sp1Filters';
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+if (isstr(filtfile) & (exist(filtfile) == 2))
+   [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filtfile);
+else
+  fprintf(1,'\nUse buildSFpyr for pyramids with arbitrary numbers of orientation bands.\n');
+  error('FILTFILE argument must be the name of an M-file containing SPYR filters.');
+end
+
+max_ht = maxPyrHt(size(im), size(lofilt,1));
+if ( (exist('ht') ~= 1) | (ht == 'auto') )
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+%-----------------------------------------------------------------
+
+hi0 = corrDn(im, hi0filt, edges);
+lo0 = corrDn(im, lo0filt, edges);
+
+[pyr,pind] = buildSpyrLevs(lo0, ht, lofilt, bfilts, edges);
+
+pyr = [hi0(:) ; pyr];
+pind = [size(hi0); pind];
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyrLevs.m
new file mode 100755
index 0000000..4c00077
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildSpyrLevs.m
@@ -0,0 +1,37 @@
+% [PYR, INDICES] = buildSpyrLevs(LOIM, HEIGHT, LOFILT, BFILTS, EDGES)
+%
+% Recursive function for constructing levels of a steerable pyramid.  This
+% is called by buildSpyr, and is not usually called directly.
+
+% Eero Simoncelli, 6/96.
+
+function [pyr,pind] = buildSpyrLevs(lo0,ht,lofilt,bfilts,edges);
+
+if (ht <= 0)
+
+  pyr = lo0(:);
+  pind = size(lo0);
+
+else
+
+  % Assume square filters:
+  bfiltsz =  round(sqrt(size(bfilts,1)));
+
+  bands = zeros(prod(size(lo0)),size(bfilts,2));
+  bind = zeros(size(bfilts,2),2);
+
+  for b = 1:size(bfilts,2)
+    filt = reshape(bfilts(:,b),bfiltsz,bfiltsz);
+    band = corrDn(lo0, filt, edges);
+    bands(:,b) = band(:);
+    bind(b,:)  = size(band);
+  end
+        
+  lo = corrDn(lo0, lofilt, edges, [2 2], [1 1]);
+  
+  [npyr,nind] = buildSpyrLevs(lo, ht-1, lofilt, bfilts, edges);
+
+  pyr = [bands(:); npyr];
+  pind = [bind; nind];
+        
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildWpyr.m
new file mode 100755
index 0000000..22ae32f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/buildWpyr.m
@@ -0,0 +1,100 @@
+% [PYR, INDICES] = buildWpyr(IM, HEIGHT, FILT, EDGES)
+%
+% Construct a separable orthonormal QMF/wavelet pyramid on matrix (or vector) IM.
+%
+% HEIGHT (optional) specifies the number of pyramid levels to build. Default
+% is maxPyrHt(IM,FILT).  You can also specify 'auto' to use this value.
+%
+% FILT (optional) can be a string naming a standard filter (see
+% namedFilter), or a vector which will be used for (separable)
+% convolution.  Filter can be of even or odd length, but should be symmetric. 
+% Default = 'qmf9'.  EDGES specifies edge-handling, and
+% defaults to 'reflect1' (see corrDn).
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+
+% Eero Simoncelli, 6/96.
+
+function [pyr,pind] = buildWpyr(im, ht, filt, edges)
+
+if (nargin < 1)
+  error('First argument (IM) is required');
+end
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('filt') ~= 1)
+  filt = 'qmf9';
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+if isstr(filt)
+  filt = namedFilter(filt);
+end
+
+if ( (size(filt,1) > 1) & (size(filt,2) > 1) )
+  error('FILT should be a 1D filter (i.e., a vector)');
+else
+  filt = filt(:);
+end
+
+hfilt = modulateFlip(filt);
+
+% Stagger sampling if filter is odd-length:
+if (mod(size(filt,1),2) == 0)
+  stag = 2;
+else
+  stag = 1;
+end
+
+im_sz = size(im);
+
+max_ht = maxPyrHt(im_sz, size(filt,1));
+if ( (exist('ht') ~= 1) | (ht == 'auto') )
+  ht = max_ht;
+else
+  if (ht > max_ht)
+    error(sprintf('Cannot build pyramid higher than %d levels.',max_ht));
+  end
+end
+
+if (ht <= 0)
+
+  pyr = im(:);
+  pind = im_sz;
+
+else
+
+  if (im_sz(2) == 1)
+    lolo = corrDn(im, filt, edges, [2 1], [stag 1]);
+    hihi = corrDn(im, hfilt, edges, [2 1], [2 1]);
+  elseif (im_sz(1) == 1)
+    lolo = corrDn(im, filt', edges, [1 2], [1 stag]);
+    hihi = corrDn(im, hfilt', edges, [1 2], [1 2]);
+  else
+    lo = corrDn(im, filt, edges, [2 1], [stag 1]);
+    hi = corrDn(im, hfilt, edges, [2 1], [2 1]);
+    lolo = corrDn(lo, filt', edges, [1 2], [1 stag]);
+    lohi = corrDn(hi, filt', edges, [1 2], [1 stag]); % horizontal
+    hilo = corrDn(lo, hfilt', edges, [1 2], [1 2]); % vertical
+    hihi = corrDn(hi, hfilt', edges, [1 2], [1 2]); % diagonal
+  end
+
+  [npyr,nind] = buildWpyr(lolo, ht-1, filt, edges);
+
+  if ((im_sz(1) == 1) | (im_sz(2) == 1))
+    pyr = [hihi(:); npyr];
+    pind = [size(hihi); nind];
+  else
+    pyr = [lohi(:); hilo(:); hihi(:); npyr];
+    pind = [size(lohi); size(hilo); size(hihi); nind];
+  end
+
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/cconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/cconv2.m
new file mode 100755
index 0000000..efba438
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/cconv2.m
@@ -0,0 +1,50 @@
+% RES = CCONV2(MTX1, MTX2, CTR)
+%
+% Circular convolution of two matrices.  Result will be of size of
+% LARGER vector.
+% 
+% The origin of the smaller matrix is assumed to be its center.
+% For even dimensions, the origin is determined by the CTR (optional) 
+% argument:
+%      CTR   origin
+%       0     DIM/2      (default)
+%       1     (DIM/2)+1  
+
+% Eero Simoncelli, 6/96.  Modified 2/97.
+
+function c = cconv2(a,b,ctr)
+
+if (exist('ctr') ~= 1)
+  ctr = 0;
+end
+
+if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
+    large = a; small = b;
+elseif  (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
+    large = b; small = a;
+else
+  error('one arg must be larger than the other in both dimensions!');
+end
+
+ly = size(large,1);
+lx = size(large,2);
+sy = size(small,1);
+sx = size(small,2);
+
+%% These values are the index of the small mtx that falls on the
+%% border pixel of the large matrix when computing the first
+%% convolution response sample:
+sy2 = floor((sy+ctr+1)/2);
+sx2 = floor((sx+ctr+1)/2);
+
+% pad:
+clarge = [ ...
+    large(ly-sy+sy2+1:ly,lx-sx+sx2+1:lx), large(ly-sy+sy2+1:ly,:), ...
+        large(ly-sy+sy2+1:ly,1:sx2-1); ...
+    large(:,lx-sx+sx2+1:lx), large, large(:,1:sx2-1); ...
+    large(1:sy2-1,lx-sx+sx2+1:lx), ...
+        large(1:sy2-1,:), ...
+        large(1:sy2-1,1:sx2-1) ];
+
+c = conv2(clarge,small,'valid');
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/clip.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/clip.m
new file mode 100755
index 0000000..28804f3
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/clip.m
@@ -0,0 +1,32 @@
+% [RES] = clip(IM, MINVALorRANGE, MAXVAL)
+%
+% Clip values of matrix IM to lie between minVal and maxVal:
+%      RES = max(min(IM,MAXVAL),MINVAL)
+% The first argument can also specify both min and max, as a 2-vector.
+% If only one argument is passed, the range defaults to [0,1].
+
+function res = clip(im, minValOrRange, maxVal)
+
+if (exist('minValOrRange') ~= 1) 
+  minVal = 0; 
+  maxVal = 1;
+elseif (length(minValOrRange) == 2)
+  minVal = minValOrRange(1);
+  maxVal = minValOrRange(2);
+elseif (length(minValOrRange) == 1)
+  minVal = minValOrRange;
+  if (exist('maxVal') ~= 1)
+    maxVal=minVal+1;
+  end
+else
+  error('MINVAL must be  a scalar or a 2-vector');
+end
+
+if ( maxVal < minVal )
+  error('MAXVAL should be less than MINVAL');
+end
+
+res = im;
+res(find(im < minVal)) = minVal;
+res(find(im > maxVal)) = maxVal;
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/corrDn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/corrDn.m
new file mode 100755
index 0000000..afe09d2
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/corrDn.m
@@ -0,0 +1,63 @@
+% RES = corrDn(IM, FILT, EDGES, STEP, START, STOP)
+%
+% Compute correlation of matrices IM with FILT, followed by
+% downsampling.  These arguments should be 1D or 2D matrices, and IM
+% must be larger (in both dimensions) than FILT.  The origin of filt
+% is assumed to be floor(size(filt)/2)+1.
+% 
+% EDGES is a string determining boundary handling:
+%    'circular' - Circular convolution
+%    'reflect1' - Reflect about the edge pixels
+%    'reflect2' - Reflect, doubling the edge pixels
+%    'repeat'   - Repeat the edge pixels
+%    'zero'     - Assume values of zero outside image boundary
+%    'extend'   - Reflect and invert
+%    'dont-compute' - Zero output when filter overhangs input boundaries
+%
+% Downsampling factors are determined by STEP (optional, default=[1 1]), 
+% which should be a 2-vector [y,x].
+% 
+% The window over which the convolution occurs is specfied by START 
+% (optional, default=[1,1], and STOP (optional, default=size(IM)).
+% 
+% NOTE: this operation corresponds to multiplication of a signal
+% vector by a matrix whose rows contain copies of the FILT shifted by
+% multiples of STEP.  See upConv.m for the operation corresponding to
+% the transpose of this matrix.
+
+% Eero Simoncelli, 6/96, revised 2/97.
+
+function res = corrDn(im, filt, edges, step, start, stop)
+
+%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
+
+fprintf(1,'WARNING: You should compile the MEX version of "corrDn.c",\n         found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path.  It is MUCH faster, and provides more boundary-handling options.\n');
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('edges') == 1) 
+  if (strcmp(edges,'reflect1') ~= 1)
+    warning('Using REFLECT1 edge-handling (use MEX code for other options).');
+  end
+end
+
+if (exist('step') ~= 1)
+        step = [1,1];
+end     
+
+if (exist('start') ~= 1)
+        start = [1,1];
+end     
+
+if (exist('stop') ~= 1)
+        stop = size(im);
+end     
+
+%------------------------------------------------------------
+
+% Reverse order of taps in filt, to do correlation instead of convolution
+filt = filt(size(filt,1):-1:1,size(filt,2):-1:1);
+
+tmp = rconv2(im,filt);
+res = tmp(start(1):step(1):stop(1),start(2):step(2):stop(2));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/einstein.pgm b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/einstein.pgm
new file mode 100755
index 0000000..99b974c
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/einstein.pgm
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/entropy2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/entropy2.m
new file mode 100755
index 0000000..68a2a9f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/entropy2.m
@@ -0,0 +1,31 @@
+% E = ENTROPY2(MTX,BINSIZE) 
+% 
+% Compute the first-order sample entropy of MTX.  Samples of VEC are
+% first discretized.  Optional argument BINSIZE controls the
+% discretization, and defaults to 256/(max(VEC)-min(VEC)).
+%
+% NOTE: This is a heavily  biased estimate of entropy when you
+% don't have much data.
+
+% Eero Simoncelli, 6/96.
+
+function res = entropy2(mtx,binsize)
+
+%% Ensure it's a vector, not a matrix.
+vec = mtx(:);
+[mn,mx] = range2(vec);
+
+if (exist('binsize') == 1)
+  nbins = max((mx-mn)/binsize, 1);
+else
+  nbins = 256;
+end
+  
+[bincount,bins] = histo(vec,nbins);
+
+%% Collect non-zero bins:
+H = bincount(find(bincount));
+H = H/sum(H);
+
+res = -sum(H .* log2(H));
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/factorial.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/factorial.m
new file mode 100755
index 0000000..9255f43
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/factorial.m
@@ -0,0 +1,16 @@
+%% RES = factorial(NUM)
+%
+% Factorial function that works on matrices (matlab's does not).
+
+% EPS, 11/02
+
+function res = factorial(num)
+
+res = ones(size(num));
+
+ind = find(num > 0);
+if ( ~isempty(ind) )
+  subNum = num(ind);
+  res(ind) = subNum .* factorial(subNum-1);
+end
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/feynman.pgm b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/feynman.pgm
new file mode 100755
index 0000000..7d14101
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/feynman.pgm
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histo.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histo.m
new file mode 100755
index 0000000..3366301
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histo.m
@@ -0,0 +1,58 @@
+% [N,X] = histo(MTX, nbinsOrBinsize, binCenter);
+%
+% Compute a histogram of (all) elements of MTX.  N contains the histogram
+% counts, X is a vector containg the centers of the histogram bins.
+%
+% nbinsOrBinsize (optional, default = 101) specifies either
+% the number of histogram bins, or the negative of the binsize.
+%
+% binCenter (optional, default = mean2(MTX)) specifies a center position
+% for (any one of) the histogram bins.
+%
+% How does this differ from MatLab's HIST function?  This function:
+%   - allows uniformly spaced bins only.
+%   +/- operates on all elements of MTX, instead of columnwise.
+%   + is much faster (approximately a factor of 80 on my machine).
+%   + allows specification of number of bins OR binsize.  Default=101 bins.
+%   + allows (optional) specification of binCenter.
+
+% Eero Simoncelli, 3/97.
+
+function [N, X] = histo(mtx, nbins, binCtr)
+
+%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
+
+fprintf(1,'WARNING: You should compile the MEX version of "histo.c",\n         found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path.  It is MUCH faster.\n');
+
+mtx = mtx(:);
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+[mn,mx] = range2(mtx);
+
+if (exist('binCtr') ~= 1) 
+  binCtr =  mean(mtx);
+end
+
+if (exist('nbins') == 1) 
+  if (nbins < 0)
+    binSize = -nbins;
+  else
+    binSize = ((mx-mn)/nbins);
+    tmpNbins = round((mx-binCtr)/binSize) - round((mn-binCtr)/binSize);
+    if (tmpNbins ~= nbins)
+      warning('Using %d bins instead of requested number (%d)',tmpNbins,nbins);
+    end
+  end
+else
+  binSize = ((mx-mn)/101);
+end
+
+firstBin = binCtr + binSize*round( (mn-binCtr)/binSize );
+
+tmpNbins = round((mx-binCtr)/binSize) - round((mn-binCtr)/binSize);
+
+bins = firstBin + binSize*[0:tmpNbins];
+
+[N, X] = hist(mtx, bins);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histoMatch.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histoMatch.m
new file mode 100755
index 0000000..ab82782
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/histoMatch.m
@@ -0,0 +1,35 @@
+% RES = histoMatch(MTX, N, X)
+%
+% Modify elements of MTX so that normalized histogram matches that
+% specified by vectors X and N, where N contains the histogram counts
+% and X the histogram bin positions (see histo).
+
+% Eero Simoncelli, 7/96.
+
+function res = histoMatch(mtx, N, X)
+
+if ( exist('histo') == 3 )
+  [oN, oX] = histo(mtx(:), size(X(:),1));
+else
+  [oN, oX] = hist(mtx(:), size(X(:),1));
+end
+
+oStep = oX(2) - oX(1);
+oC = [0, cumsum(oN)]/sum(oN);
+oX = [oX(1)-oStep/2, oX+oStep/2];
+
+N = N(:)';
+X = X(:)';
+N = N + mean(N)/(1e8);   %% HACK: no empty bins ensures nC strictly monotonic
+
+nStep = X(2) - X(1);
+nC = [0, cumsum(N)]/sum(N);
+nX = [X(1)-nStep/2, X+nStep/2];
+
+nnX = interp1(nC, nX, oC, 'linear');
+
+if ( exist('pointOp') == 3 )
+  res = pointOp(mtx, nnX, oX(1), oStep);
+else
+  res = reshape(interp1(oX, nnX, mtx(:)),size(mtx,1),size(mtx,2));
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ifftshift.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ifftshift.m
new file mode 100755
index 0000000..2ade297
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/ifftshift.m
@@ -0,0 +1,15 @@
+% [RES] = ifftshift (MTX)
+%
+% Inverse of MatLab's FFTSHIFT.  That is,
+%     ifftshift(fftshift(MTX)) = MTX
+%   for any size MTX.
+
+% Eero Simoncelli, 2/97.
+
+function [res]  = ifftshift(mtx)
+
+sz = size(mtx);
+DC = ceil((sz+1)./2);                   % location of DC term in a matlab fft.
+
+res = [mtx(DC(1):sz(1), DC(2):sz(2)) , mtx(DC(1):sz(1), 1:DC(2)-1); ...
+       mtx(1:DC(1)-1, DC(2):sz(2)) , mtx(1:DC(1)-1, 1:DC(2)-1)];
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imGradient.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imGradient.m
new file mode 100755
index 0000000..23187e3
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imGradient.m
@@ -0,0 +1,48 @@
+% [dx, dy] = imGradient(im, edges) 
+%
+% Compute the gradient of the image using smooth derivative filters
+% optimized for accurate direction estimation.  Coordinate system
+% corresponds to standard pixel indexing: X axis points rightward.  Y
+% axis points downward.  EDGES specify boundary handling (see corrDn
+% for options).
+
+% EPS, 1997.
+% original filters from Int'l Conf Image Processing, 1994.
+% updated filters 10/2003.
+% Added to matlabPyrTools 10/2004.
+
+function [dx, dy] = imGradient(im, edges) 
+
+%% 1D smoothing and differentiation kernels.
+%% See Farid & Simoncelli, IEEE Trans Image Processing, 13(4):496-508, April 2004.
+
+if (exist('edges') ~= 1)
+    edges = 'dont-compute';
+end
+
+gp = [0.037659 0.249153 0.426375 0.249153 0.037659]';
+gd = [-0.109604 -0.276691 0.000000 0.276691 0.109604]';
+
+dx = corrDn(corrDn(im, gp, edges), gd', edges);
+dy = corrDn(corrDn(im, gd, edges), gp', edges);
+
+return 
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%%% TEST:
+
+%%Make a ramp with random slope and direction 
+dir = 2*pi*rand - pi;
+slope = 10*rand;
+
+sz = 32
+im = mkRamp(sz, dir, slope);
+[dx,dy] = imGradient(im);
+showIm(dx + sqrt(-1)*dy);
+
+ctr = (sz*sz/2)+sz/2;
+slopeEst = sqrt(dx(ctr).^2 + dy(ctr).^2);
+dirEst = atan2(dy(ctr), dx(ctr));
+
+[slope, slopeEst]
+[dir, dirEst]
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imStats.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imStats.m
new file mode 100755
index 0000000..3d79b4c
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/imStats.m
@@ -0,0 +1,41 @@
+% imStats(IM1,IM2)
+%
+% Report image (matrix) statistics.
+% When called on a single image IM1, report min, max, mean, stdev, 
+% and kurtosis.
+% When called on two images (IM1 and IM2), report min, max, mean, 
+% stdev of the difference, and also SNR (relative to IM1).
+
+% Eero Simoncelli, 6/96.
+
+function [] = imStats(im1,im2)
+
+if (~isreal(im1))
+  error('Args must be real-valued matrices');  
+end
+
+if (exist('im2') == 1)
+  difference = im1 - im2;
+  [mn,mx] = range2(difference);
+  mean = mean2(difference);
+  v = var2(difference,mean);
+  if (v < realmin) 
+    snr = Inf;
+  else
+    snr = 10 * log10(var2(im1)/v);
+  end
+  fprintf(1, 'Difference statistics:\n');
+  fprintf(1, '  Range: [%c, %c]\n',mn,mx);
+  fprintf(1, '  Mean: %f,  Stdev (rmse): %f,  SNR (dB): %f\n',...
+      mean,sqrt(v),snr);
+else
+  [mn,mx] = range2(im1);
+  mean = mean2(im1);
+  var = var2(im1);  
+  stdev = sqrt(real(var))+sqrt(imag(var));
+  kurt = kurt2(im1, mean, stdev^2);
+  fprintf(1, 'Image statistics:\n');
+  fprintf(1, '  Range: [%f, %f]\n',mn,mx);
+  fprintf(1, '  Mean: %f,  Stdev: %f,  Kurtosis: %f\n',mean,stdev,kurt);
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/innerProd.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/innerProd.m
new file mode 100755
index 0000000..da82321
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/innerProd.m
@@ -0,0 +1,12 @@
+% RES = innerProd(MTX)
+%
+% Compute (MTX' * MTX) efficiently (i.e., without copying the matrix)
+
+function res = innerProd(mtx)
+
+fprintf(1,['WARNING: You should compile the MEX version of' ...
+           ' "innerProd.c",\n         found in the MEX subdirectory' ...
+           ' of matlabPyrTools, and put it in your matlab path.' ...
+           ' It is MUCH faster and requires less memory.\n']);
+
+res = mtx' * mtx;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/kurt2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/kurt2.m
new file mode 100755
index 0000000..8351eb4
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/kurt2.m
@@ -0,0 +1,24 @@
+% K = KURT2(MTX,MEAN,VAR)
+%
+% Sample kurtosis (fourth moment divided by squared variance) 
+% of a matrix.  Kurtosis of a Gaussian distribution is 3.
+%  MEAN (optional) and VAR (optional) make the computation faster.
+
+% Eero Simoncelli, 6/96.
+
+function res = kurt2(mtx, mn, v)
+
+if (exist('mn') ~= 1)
+        mn =  mean(mean(mtx));
+end
+
+if (exist('v') ~= 1)
+        v =  var2(mtx,mn);
+end
+
+if (isreal(mtx))
+  res = mean(mean(abs(mtx-mn).^4)) / (v^2);
+else
+  res = mean(mean(real(mtx-mn).^4)) / (real(v)^2) + ...
+      i*mean(mean(imag(mtx-mn).^4)) / (imag(v)^2);
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lplot.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lplot.m
new file mode 100755
index 0000000..3c67d8b
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lplot.m
@@ -0,0 +1,43 @@
+% lplot(VEC, XRANGE)
+%
+% Plot VEC, a vector, in  "lollipop" format.  
+% XRANGE (optional, default = [1,length(VEC)]), should be a 2-vector 
+% specifying the X positions (for labeling purposes) of the first and 
+% last sample of VEC.
+
+% Mark Liberman, Linguistics Dept, UPenn, 1994.
+
+function lplot(x,xrange)
+
+if (exist('xrange') ~= 1)
+  xrange = [1,length(x)];
+end
+
+msize = size(x);
+if ( msize(2) == 1)
+  x = x';
+elseif (msize(1) ~= 1)
+  error('First arg must be a vector');
+end
+
+if (~isreal(x))
+  fprintf(1,'Warning: Imaginary part of signal ignored\n');
+  x = abs(x);
+end
+
+N = length(x);
+index = xrange(1) + (xrange(2)-xrange(1))*[0:(N-1)]/(N-1)
+xinc = index(2)-index(1);
+
+xx = [zeros(1,N);x;zeros(1,N)];
+indexis = [index;index;index];
+xdiscrete = [0 xx(:)' 0];
+idiscrete = [index(1)-xinc indexis(:)' index(N)+xinc];
+
+[mn,mx] = range2(xdiscrete);
+ypad = (mx-mn)/12;                      % MAGIC NUMBER: graph padding
+
+plot(idiscrete, xdiscrete, index, x, 'o');
+axis([index(1)-xinc, index(N)+xinc, mn-ypad, mx+ypad]);
+
+return
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lpyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lpyrHt.m
new file mode 100755
index 0000000..d6834d7
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/lpyrHt.m
@@ -0,0 +1,11 @@
+% [HEIGHT] = lpyrHt(INDICES)
+%
+% Compute height of Laplacian pyramid with given its INDICES matrix.
+% See buildLpyr.m
+
+% Eero Simoncelli, 6/96.
+
+function [ht] =  lpyrHt(pind)
+
+% Don't count lowpass residual band
+ht = size(pind,1)-1;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/maxPyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/maxPyrHt.m
new file mode 100755
index 0000000..84bcf29
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/maxPyrHt.m
@@ -0,0 +1,25 @@
+% HEIGHT = maxPyrHt(IMSIZE, FILTSIZE)
+%
+% Compute maximum pyramid height for given image and filter sizes.
+% Specifically: the number of corrDn operations that can be sequentially
+% performed when subsampling by a factor of 2.
+
+% Eero Simoncelli, 6/96.
+
+function height = maxPyrHt(imsz, filtsz)
+
+imsz = imsz(:);
+filtsz = filtsz(:);
+
+if any(imsz == 1) % 1D image
+  imsz = prod(imsz);
+  filtsz = prod(filtsz);
+elseif any(filtsz == 1)              % 2D image, 1D filter
+  filtsz = [filtsz(1); filtsz(1)];
+end
+
+if any(imsz < filtsz)
+  height = 0;
+else
+  height = 1 + maxPyrHt( floor(imsz/2), filtsz ); 
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mean2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mean2.m
new file mode 100755
index 0000000..177f7ac
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mean2.m
@@ -0,0 +1,7 @@
+% M = MEAN2(MTX)
+%
+% Sample mean of a matrix.
+
+function res = mean2(mtx)
+
+res = mean(mean(mtx));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngle.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngle.m
new file mode 100755
index 0000000..bd54f8d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngle.m
@@ -0,0 +1,32 @@
+% IM = mkAngle(SIZE, PHASE, ORIGIN)
+%
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing samples of the polar angle (in radians, CW from the
+% X-axis, ranging from -pi to pi), relative to angle PHASE (default =
+% 0), about ORIGIN pixel (default = (size+1)/2).
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkAngle(sz, phase, origin)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+
+% -----------------------------------------------------------------
+% OPTIONAL args:
+
+if (exist('origin') ~= 1)
+  origin = (sz+1)/2;
+end
+
+% -----------------------------------------------------------------
+
+[xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) );
+
+res = atan2(yramp,xramp);
+
+if (exist('phase') == 1)
+  res = mod(res+(pi-phase),2*pi)-pi;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngularSine.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngularSine.m
new file mode 100755
index 0000000..f5238cc
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkAngularSine.m
@@ -0,0 +1,42 @@
+% IM = mkAngularSine(SIZE, HARMONIC, AMPL, PHASE, ORIGIN)
+%
+% Make an angular sinusoidal image:
+%     AMPL * sin( HARMONIC*theta + PHASE),
+% where theta is the angle about the origin.
+% SIZE specifies the matrix size, as for zeros().  
+% AMPL (default = 1) and PHASE (default = 0) are optional.
+
+% Eero Simoncelli, 2/97.
+
+function [res] = mkAngularSine(sz, harmonic, ampl, ph, origin)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+
+mxsz = max(sz(1),sz(2));
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('harmonic') ~= 1)
+  harmonic = 1;
+end
+
+if (exist('ampl') ~= 1)
+  ampl = 1;
+end
+
+if (exist('ph') ~= 1)
+  ph = 0;
+end
+
+if (exist('origin') ~= 1)
+  origin = (sz+1)/2;
+end
+
+%------------------------------------------------------------
+
+res = ampl * sin(harmonic*mkAngle(sz,ph,origin) + ph);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkDisc.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkDisc.m
new file mode 100755
index 0000000..33e7d6d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkDisc.m
@@ -0,0 +1,61 @@
+% IM = mkDisc(SIZE, RADIUS, ORIGIN, TWIDTH, VALS)
+%
+% Make a "disk" image.  SIZE specifies the matrix size, as for
+% zeros().  RADIUS (default = min(size)/4) specifies the radius of 
+% the disk.  ORIGIN (default = (size+1)/2) specifies the 
+% location of the disk center.  TWIDTH (in pixels, default = 2) 
+% specifies the width over which a soft threshold transition is made.
+% VALS (default = [0,1]) should be a 2-vector containing the
+% intensity value inside and outside the disk.  
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkDisc(sz, rad, origin, twidth, vals)
+
+if (nargin < 1)
+  error('Must pass at least a size argument');
+end
+  
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz sz];
+end
+ 
+%------------------------------------------------------------
+% OPTIONAL ARGS:
+
+if (exist('rad') ~= 1)
+  rad = min(sz(1),sz(2))/4;
+end
+
+if (exist('origin') ~= 1)
+  origin = (sz+1)./2;
+end
+
+if (exist('twidth') ~= 1)
+  twidth = 2;
+end
+
+if (exist('vals') ~= 1)
+  vals = [1,0];
+end
+
+%------------------------------------------------------------
+
+res = mkR(sz,1,origin);
+
+if (abs(twidth) < realmin)
+  res = vals(2) + (vals(1) - vals(2)) * (res <= rad);
+else
+  [Xtbl,Ytbl] = rcosFn(twidth, rad, [vals(1), vals(2)]);
+  res = pointOp(res, Ytbl, Xtbl(1), Xtbl(2)-Xtbl(1), 0);
+% 
+% OLD interp1 VERSION:
+%  res = res(:);
+%  Xtbl(1) = min(res);
+%  Xtbl(size(Xtbl,2)) = max(res);
+%  res = reshape(interp1(Xtbl,Ytbl,res), sz(1), sz(2));
+% 
+end
+  
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkFract.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkFract.m
new file mode 100755
index 0000000..af95cd5
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkFract.m
@@ -0,0 +1,36 @@
+% IM = mkFract(SIZE, FRACT_DIM)
+%
+% Make a matrix of dimensions SIZE (a [Y X] 2-vector, or a scalar)
+% containing fractal (pink) noise with power spectral density of the
+% form: 1/f^(5-2*FRACT_DIM).  Image variance is normalized to 1.0.
+% FRACT_DIM defaults to 1.0
+
+% Eero Simoncelli, 6/96.
+
+%% TODO: Verify that this  matches Mandelbrot defn of fractal dimension.
+%%       Make this more efficient!
+
+function res = mkFract(dims, fract_dim)
+
+if (exist('fract_dim') ~= 1)
+  fract_dim = 1.0;
+end
+
+res = randn(dims);
+fres = fft2(res);
+
+sz = size(res);
+ctr = ceil((sz+1)./2);
+
+shape = ifftshift(mkR(sz, -(2.5-fract_dim), ctr));
+shape(1,1) = 1;  %%DC term
+
+fres = shape .* fres;
+fres = ifft2(fres);
+
+if (max(max(abs(imag(fres)))) > 1e-10)
+  error('Symmetry error in creating fractal');
+else
+  res = real(fres);
+  res = res / sqrt(var2(res));
+end  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkGaussian.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkGaussian.m
new file mode 100755
index 0000000..fa8a554
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkGaussian.m
@@ -0,0 +1,58 @@
+% IM = mkGaussian(SIZE, COVARIANCE, MEAN, AMPLITUDE)
+% 
+% Compute a matrix with dimensions SIZE (a [Y X] 2-vector, or a
+% scalar) containing a Gaussian function, centered at pixel position
+% specified by MEAN (default = (size+1)/2), with given COVARIANCE (can
+% be a scalar, 2-vector, or 2x2 matrix.  Default = (min(size)/6)^2),
+% and AMPLITUDE.  AMPLITUDE='norm' (default) will produce a
+% probability-normalized function.  All but the first argument are
+% optional.
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkGaussian(sz, cov, mn, ampl)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('cov') ~= 1)
+  cov = (min(sz(1),sz(2))/6)^2;
+end
+
+if (exist('mn') ~= 1)
+  mn = (sz+1)/2;
+end
+
+if (exist('ampl') ~= 1)
+  ampl = 'norm';
+end
+
+%------------------------------------------------------------
+
+[xramp,yramp] = meshgrid([1:sz(2)]-mn(2),[1:sz(1)]-mn(1));
+
+if (sum(size(cov)) == 2)  % scalar
+  if (strcmp(ampl,'norm'))  
+    ampl = 1/(2*pi*cov(1));
+  end
+  e = (xramp.^2 + yramp.^2)/(-2 * cov);
+elseif (sum(size(cov)) == 3) % a 2-vector
+  if (strcmp(ampl,'norm'))  
+    ampl = 1/(2*pi*sqrt(cov(1)*cov(2)));
+  end
+  e = xramp.^2/(-2 * cov(2)) + yramp.^2/(-2 * cov(1));
+else
+  if (strcmp(ampl,'norm'))  
+    ampl = 1/(2*pi*sqrt(det(cov)));
+  end
+  cov = -inv(cov)/2;
+  e = cov(2,2)*xramp.^2 + (cov(1,2)+cov(2,1))*(xramp.*yramp) ...
+      + cov(1,1)*yramp.^2;
+end
+  
+res = ampl .* exp(e);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkImpulse.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkImpulse.m
new file mode 100755
index 0000000..9844ee8
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkImpulse.m
@@ -0,0 +1,25 @@
+% IM = mkImpulse(SIZE, ORIGIN, AMPLITUDE)
+%
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing a single non-zero entry, at position ORIGIN (defaults to
+% ceil(size/2)), of value AMPLITUDE (defaults to 1).
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkImpulse(sz, origin, amplitude)
+
+sz = sz(:)';
+if (size(sz,2) == 1)
+  sz = [sz sz];
+end
+
+if (exist('origin') ~= 1)
+  origin = ceil(sz/2);
+end
+
+if (exist('amplitude') ~= 1)
+  amplitude = 1;
+end
+
+res = zeros(sz);
+res(origin(1),origin(2)) = amplitude;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkR.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkR.m
new file mode 100755
index 0000000..a1e8448
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkR.m
@@ -0,0 +1,32 @@
+% IM = mkR(SIZE, EXPT, ORIGIN)
+% 
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing samples of a radial ramp function, raised to power EXPT
+% (default = 1), with given ORIGIN (default = (size+1)/2, [1 1] =
+% upper left).  All but the first argument are optional.
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkR(sz, expt, origin)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+ 
+% -----------------------------------------------------------------
+% OPTIONAL args:
+
+if (exist('expt') ~= 1)
+  expt = 1;
+end
+
+if (exist('origin') ~= 1)
+  origin = (sz+1)/2;
+end
+
+% -----------------------------------------------------------------
+
+[xramp,yramp] = meshgrid( [1:sz(2)]-origin(2), [1:sz(1)]-origin(1) );
+
+res = (xramp.^2 + yramp.^2).^(expt/2);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkRamp.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkRamp.m
new file mode 100755
index 0000000..dd37164
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkRamp.m
@@ -0,0 +1,47 @@
+% IM = mkRamp(SIZE, DIRECTION, SLOPE, INTERCEPT, ORIGIN)
+%
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing samples of a ramp function, with given gradient DIRECTION
+% (radians, CW from X-axis, default = 0), SLOPE (per pixel, default =
+% 1), and a value of INTERCEPT (default = 0) at the ORIGIN (default =
+% (size+1)/2, [1 1] = upper left).  All but the first argument are
+% optional.
+
+% Eero Simoncelli, 6/96. 2/97: adjusted coordinate system.
+
+function [res] = mkRamp(sz, dir, slope, intercept, origin)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+
+% -----------------------------------------------------------------
+% OPTIONAL args:
+
+if (exist('dir') ~= 1)
+  dir = 0;
+end
+ 
+if (exist('slope') ~= 1)
+  slope = 1;
+end
+ 
+if (exist('intercept') ~= 1)
+  intercept = 0;
+end
+
+if (exist('origin') ~= 1)
+  origin = (sz+1)/2;
+end
+
+% -----------------------------------------------------------------
+
+xinc = slope*cos(dir);
+yinc = slope*sin(dir);
+
+[xramp,yramp] = meshgrid( xinc*([1:sz(2)]-origin(2)), ...
+    yinc*([1:sz(1)]-origin(1)) );
+ 
+res = intercept + xramp + yramp;
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSine.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSine.m
new file mode 100755
index 0000000..147eb01
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSine.m
@@ -0,0 +1,67 @@
+% IM = mkSine(SIZE, PERIOD, DIRECTION, AMPLITUDE, PHASE, ORIGIN)
+%      or
+% IM = mkSine(SIZE, FREQ, AMPLITUDE, PHASE, ORIGIN)
+% 
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing samples of a 2D sinusoid, with given PERIOD (in pixels),
+% DIRECTION (radians, CW from X-axis, default = 0), AMPLITUDE (default
+% = 1), and PHASE (radians, relative to ORIGIN, default = 0).  ORIGIN
+% defaults to the center of the image.
+% 
+% In the second form, FREQ is a 2-vector of frequencies (radians/pixel).
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkSine(sz, per_freq, dir_amp, amp_phase, phase_orig, orig)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (prod(size(per_freq)) == 2)
+  frequency = norm(per_freq);
+  direction = atan2(per_freq(1),per_freq(2));
+  if (exist('dir_amp') == 1)
+    amplitude = dir_amp;
+  else
+    amplitude = 1;
+  end
+  if (exist('amp_phase') == 1)
+    phase = amp_phase;
+  else
+    phase = 0;
+  end
+  if (exist('phase_orig') == 1)
+    origin = phase_orig;
+  end
+  if (exist('orig') == 1)
+    error('Too many arguments for (second form) of mkSine');
+  end
+else
+  frequency = 2*pi/per_freq;
+  if (exist('dir_amp') == 1)
+    direction = dir_amp;
+  else
+    direction = 0;
+  end
+  if (exist('amp_phase') == 1)
+    amplitude = amp_phase;
+  else
+    amplitude = 1;
+  end
+  if (exist('phase_orig') == 1)
+    phase = phase_orig;
+  else
+    phase = 0;
+  end
+  if (exist('orig') == 1)
+    origin = orig;
+  end
+end
+
+%------------------------------------------------------------
+ 
+if (exist('origin') == 1)
+  res = amplitude*sin(mkRamp(sz, direction, frequency, phase, origin));
+else
+ res = amplitude*sin(mkRamp(sz, direction, frequency, phase));
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSquare.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSquare.m
new file mode 100755
index 0000000..84ef466
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkSquare.m
@@ -0,0 +1,89 @@
+% IM = mkSquare(SIZE, PERIOD, DIRECTION, AMPLITUDE, PHASE, ORIGIN, TWIDTH)
+%      or
+% IM = mkSine(SIZE, FREQ, AMPLITUDE, PHASE, ORIGIN, TWIDTH)
+% 
+% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
+% containing samples of a 2D square wave, with given PERIOD (in
+% pixels), DIRECTION (radians, CW from X-axis, default = 0), AMPLITUDE
+% (default = 1), and PHASE (radians, relative to ORIGIN, default = 0).
+% ORIGIN defaults to the center of the image.  TWIDTH specifies width
+% of raised-cosine edges on the bars of the grating (default =
+% min(2,period/3)).
+% 
+% In the second form, FREQ is a 2-vector of frequencies (radians/pixel).
+
+% Eero Simoncelli, 6/96.
+
+% TODO: Add duty cycle.  
+
+function [res] = mkSquare(sz, per_freq, dir_amp, amp_phase, phase_orig, orig_twidth, twidth)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (prod(size(per_freq)) == 2)
+  frequency = norm(per_freq);
+  direction = atan2(per_freq(1),per_freq(2));
+  if (exist('dir_amp') == 1)
+    amplitude = dir_amp;
+  else
+    amplitude = 1;
+  end
+  if (exist('amp_phase') == 1)
+    phase = amp_phase;
+  else
+    phase = 0;
+  end
+  if (exist('phase_orig') == 1)
+    origin = phase_orig;
+  end
+  if (exist('orig_twidth') == 1)
+    transition = orig_twidth;
+  else
+    transition = min(2,2*pi/(3*frequency));
+  end
+  if (exist('twidth') == 1)
+    error('Too many arguments for (second form) of mkSine');
+  end
+else
+  frequency = 2*pi/per_freq;
+  if (exist('dir_amp') == 1)
+    direction = dir_amp;
+  else
+    direction = 0;
+  end
+  if (exist('amp_phase') == 1)
+    amplitude = amp_phase;
+  else
+    amplitude = 1;
+  end
+  if (exist('phase_orig') == 1)
+    phase = phase_orig;
+  else
+    phase = 0;
+  end
+  if (exist('orig_twidth') == 1)
+    origin = orig_twidth;
+  end
+  if (exist('twidth') == 1)
+    transition = twidth;
+  else
+    transition = min(2,2*pi/(3*frequency));
+  end
+
+end
+
+%------------------------------------------------------------
+  
+if (exist('origin') == 1)
+  res = mkRamp(sz, direction, frequency, phase, origin) - pi/2;
+else
+  res = mkRamp(sz, direction, frequency, phase) - pi/2;
+end
+
+[Xtbl,Ytbl] = rcosFn(transition*frequency,pi/2,[-amplitude amplitude]);
+
+res = pointOp(abs(mod(res+pi, 2*pi)-pi),Ytbl,Xtbl(1),Xtbl(2)-Xtbl(1),0);
+
+% OLD threshold version: 
+%res = amplitude * (mod(res,2*pi) < pi);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkZonePlate.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkZonePlate.m
new file mode 100755
index 0000000..2b6a4a5
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mkZonePlate.m
@@ -0,0 +1,33 @@
+% IM = mkZonePlate(SIZE, AMPL, PHASE)
+%
+% Make a "zone plate" image:
+%     AMPL * cos( r^2 + PHASE)
+% SIZE specifies the matrix size, as for zeros().  
+% AMPL (default = 1) and PHASE (default = 0) are optional.
+
+% Eero Simoncelli, 6/96.
+
+function [res] = mkZonePlate(sz, ampl, ph)
+
+sz = sz(:);
+if (size(sz,1) == 1)
+  sz = [sz,sz];
+end
+
+mxsz = max(sz(1),sz(2));
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('ampl') ~= 1)
+  ampl = 1;
+end
+
+if (exist('ph') ~= 1)
+  ph = 0;
+end
+
+%------------------------------------------------------------
+
+res = ampl * cos( (pi/mxsz) * mkR(sz,2) + ph );
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mod.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mod.m
new file mode 100755
index 0000000..21167e5
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/mod.m
@@ -0,0 +1,14 @@
+% M = mod(A,B)
+% 
+% Modulus operator: returns A mod B.
+% Works on matrics, vectors or scalars.
+% 
+% NOTE: This function is a Matlab-5 builtin, but was missing from Matlab-4.
+
+% Eero Simoncelli, 7/96.
+
+function m = mod(a,n)
+
+m = a - n .* floor(a./n);
+return;
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/modulateFlip.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/modulateFlip.m
new file mode 100755
index 0000000..eb27303
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/modulateFlip.m
@@ -0,0 +1,19 @@
+% [HFILT] = modulateFlipShift(LFILT)
+%
+% QMF/Wavelet highpass filter construction: modulate by (-1)^n,
+% reverse order (and shift by one, which is handled by the convolution
+% routines).  This is an extension of the original definition of QMF's
+% (e.g., see Simoncelli90).
+
+% Eero Simoncelli, 7/96.
+
+function [hfilt] = modulateFlipShift(lfilt)
+
+lfilt = lfilt(:);
+
+sz = size(lfilt,1);
+sz2 = ceil(sz/2);
+
+ind = [sz:-1:1]';
+
+hfilt = lfilt(ind) .* (-1).^(ind-sz2);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/namedFilter.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/namedFilter.m
new file mode 100755
index 0000000..0689dbc
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/namedFilter.m
@@ -0,0 +1,71 @@
+% KERNEL = NAMED_FILTER(NAME)
+%
+% Some standard 1D filter kernels.  These are scaled such that
+% their L2-norm is 1.0.
+%
+%  binomN             - binomial coefficient filter of order N-1
+%  haar:              - Haar wavelet.
+%  qmf8, qmf12, qmf16 - Symmetric Quadrature Mirror Filters [Johnston80]
+%  daub2,daub3,daub4  - Daubechies wavelet [Daubechies88].
+%  qmf5, qmf9, qmf13: - Symmetric Quadrature Mirror Filters [Simoncelli88,Simoncelli90]
+%
+%  See bottom of file for full citations.
+
+% Eero Simoncelli, 6/96.
+
+function [kernel] = named_filter(name)
+
+if strcmp(name(1:min(5,size(name,2))), 'binom')
+  kernel = sqrt(2) * binomialFilter(str2num(name(6:size(name,2))));
+elseif strcmp(name,'qmf5')
+  kernel = [-0.076103 0.3535534 0.8593118 0.3535534 -0.076103]';
+elseif strcmp(name,'qmf9')
+  kernel = [0.02807382 -0.060944743 -0.073386624 0.41472545 0.7973934 ...
+      0.41472545 -0.073386624 -0.060944743 0.02807382]';
+elseif strcmp(name,'qmf13')
+  kernel = [-0.014556438 0.021651438 0.039045125 -0.09800052 ...
+          -0.057827797 0.42995453 0.7737113 0.42995453 -0.057827797 ...
+          -0.09800052 0.039045125 0.021651438 -0.014556438]';
+elseif strcmp(name,'qmf8')
+  kernel = sqrt(2) * [0.00938715 -0.07065183 0.06942827 0.4899808 ...
+    0.4899808 0.06942827 -0.07065183 0.00938715 ]';
+elseif strcmp(name,'qmf12')
+  kernel = sqrt(2) * [-0.003809699 0.01885659 -0.002710326 -0.08469594 ...
+        0.08846992 0.4843894 0.4843894 0.08846992 -0.08469594 -0.002710326 ...
+        0.01885659 -0.003809699 ]';
+elseif strcmp(name,'qmf16')
+  kernel = sqrt(2) * [0.001050167 -0.005054526 -0.002589756 0.0276414 -0.009666376 ...
+        -0.09039223 0.09779817 0.4810284 0.4810284 0.09779817 -0.09039223 -0.009666376 ...
+        0.0276414 -0.002589756 -0.005054526 0.001050167 ]';
+elseif strcmp(name,'haar')
+  kernel = [1 1]' / sqrt(2);
+elseif strcmp(name,'daub2')
+  kernel = [0.482962913145 0.836516303738 0.224143868042 -0.129409522551]';
+elseif strcmp(name,'daub3')
+  kernel = [0.332670552950 0.806891509311 0.459877502118 -0.135011020010 ...
+        -0.085441273882  0.035226291882]';
+elseif strcmp(name,'daub4')
+  kernel = [0.230377813309 0.714846570553 0.630880767930 -0.027983769417 ...
+        -0.187034811719 0.030841381836 0.032883011667 -0.010597401785]';
+elseif strcmp(name,'gauss5')  % for backward-compatibility
+  kernel = sqrt(2) * [0.0625 0.25 0.375 0.25 0.0625]';
+elseif strcmp(name,'gauss3')  % for backward-compatibility
+  kernel = sqrt(2) * [0.25 0.5 0.25]';
+else
+  error(sprintf('Bad filter name: %s\n',name));
+end
+  
+% [Johnston80] - J D Johnston, "A filter family designed for use in quadrature 
+%    mirror filter banks", Proc. ICASSP, pp 291-294, 1980.
+%
+% [Daubechies88] - I Daubechies, "Orthonormal bases of compactly supported wavelets",
+%    Commun. Pure Appl. Math, vol. 42, pp 909-996, 1988.
+%
+% [Simoncelli88] - E P Simoncelli,  "Orthogonal sub-band image transforms",
+%     PhD Thesis, MIT Dept. of Elec. Eng. and Comp. Sci. May 1988.
+%     Also available as: MIT Media Laboratory Vision and Modeling Technical 
+%     Report #100.
+%
+% [Simoncelli90] -  E P Simoncelli and E H Adelson, "Subband image coding",
+%    Subband Transforms, chapter 4, ed. John W Woods, Kluwer Academic 
+%    Publishers,  Norwell, MA, 1990, pp 143--192.
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/nextFig.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/nextFig.m
new file mode 100755
index 0000000..e0ac73f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/nextFig.m
@@ -0,0 +1,19 @@
+% nextFig (MAXFIGS, SKIP)
+% 
+% Make figure number mod((GCF+SKIP), MAXFIGS) the current figure.
+% MAXFIGS is optional, and defaults to 2.
+% SKIP is optional, and defaults to 1.
+
+% Eero Simoncelli, 2/97.
+
+function nextFig(maxfigs, skip)
+
+if (exist('maxfigs') ~= 1)
+  maxfigs = 2;
+end
+  
+if (exist('skip') ~= 1)
+  skip = 1;
+end
+  
+figure(1+mod(gcf-1+skip,maxfigs));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmRead.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmRead.m
new file mode 100755
index 0000000..86c3b62
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmRead.m
@@ -0,0 +1,59 @@
+% IM = pgmRead( FILENAME )
+%
+% Load a pgm image into a MatLab matrix.  
+%   This format is accessible from the XV image browsing utility.
+%   Only works for 8bit gray images (raw or ascii)
+
+% Hany Farid, Spring '96.  Modified by Eero Simoncelli, 6/96.
+
+function im = pgmRead( fname );
+
+[fid,msg] = fopen( fname, 'r' );
+
+if (fid == -1)
+  error(msg);
+end
+
+%%% First line contains ID string:
+%%% "P1" = ascii bitmap, "P2" = ascii greymap,
+%%% "P3" = ascii pixmap, "P4" = raw bitmap, 
+%%% "P5" = raw greymap, "P6" = raw pixmap
+TheLine = fgetl(fid);
+format  = TheLine;              
+
+if ~((format(1:2) == 'P2') | (format(1:2) == 'P5'))
+  error('PGM file must be of type P2 or P5');
+end
+
+%%% Any number of comment lines
+TheLine  = fgetl(fid);
+while TheLine(1) == '#' 
+        TheLine = fgetl(fid);
+end
+
+%%% dimensions
+sz = sscanf(TheLine,'%d',2);
+xdim = sz(1);
+ydim = sz(2);
+sz = xdim * ydim;
+
+%%% Maximum pixel value
+TheLine  = fgetl(fid);
+maxval = sscanf(TheLine, '%d',1);
+
+%%im  = zeros(dim,1);
+if (format(2) == '2')
+  [im,count]  = fscanf(fid,'%d',sz);
+else
+  [im,count]  = fread(fid,sz,'uchar');
+end
+
+fclose(fid);
+
+if (count == sz)
+  im = reshape( im, xdim, ydim )';
+else
+  fprintf(1,'Warning: File ended early!');
+  im = reshape( [im ; zeros(sz-count,1)], xdim, ydim)';
+end
+          
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmWrite.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmWrite.m
new file mode 100755
index 0000000..09c14c9
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pgmWrite.m
@@ -0,0 +1,120 @@
+% RANGE = pgmWrite(MTX, FILENAME, RANGE, TYPE, COMMENT)
+%
+% Write a MatLab matrix to a pgm (graylevel image) file.
+% This format is accessible from the XV image browsing utility.
+%
+% RANGE (optional) is a 2-vector specifying the values that map to
+% black and white, respectively.  Passing a value of 'auto' (default)
+% sets RANGE=[min,max] (as in MatLab's imagesc).  'auto2' sets
+% RANGE=[mean-2*stdev, mean+2*stdev].  'auto3' sets
+% RANGE=[p1-(p2-p1)/8, p2+(p2-p1)/8], where p1 is the 10th percentile
+% value of the sorted MATRIX samples, and p2 is the 90th percentile
+% value.
+%
+% TYPE (optional) should be 'raw' or 'ascii'.  Defaults to 'raw'.
+
+% Hany Farid,  Spring '96.  Modified by Eero Simoncelli, 6/96.
+
+function range = pgmWrite(mtx, fname, range, type, comment );
+
+[fid,msg] = fopen( fname, 'w' );
+
+if (fid == -1)
+  error(msg);
+end
+
+%------------------------------------------------------------
+%% optional ARGS:
+
+if (exist('range') ~= 1)
+  range = 'auto';
+end
+
+if (exist('type') ~= 1)
+  type = 'raw';
+end
+%------------------------------------------------------------
+
+%% Automatic range calculation: 
+if (strcmp(range,'auto1') | strcmp(range,'auto'))
+  [mn,mx] = range2(mtx);
+  range = [mn,mx];
+
+elseif strcmp(range,'auto2')
+  stdev = sqrt(var2(mtx));
+  av = mean2(mtx);
+  range = [av-2*stdev,av+2*stdev];      % MAGIC NUMBER: 2 stdevs
+
+elseif strcmp(range, 'auto3')
+  percentile = 0.1;                     % MAGIC NUMBER: 0<p<0.5
+  [N,X] = histo(mtx);
+  binsz = X(2)-X(1);
+  N = N+1e-10;  % Ensure cumsum will be monotonic for call to interp1
+  cumN = [0, cumsum(N)]/sum(N);
+  cumX = [X(1)-binsz, X] + (binsz/2);
+  ctrRange = interp1(cumN,cumX, [percentile, 1-percentile]);
+  range = mean(ctrRange) + (ctrRange-mean(ctrRange))/(1-2*percentile);
+
+elseif isstr(range)
+  error(sprintf('Bad RANGE argument: %s',range))
+
+end
+
+if ((range(2) - range(1)) <= eps)
+  range(1) = range(1) - 0.5;
+  range(2) = range(2) + 0.5;
+end
+
+
+%%% First line contains ID string:
+%%% "P1" = ascii bitmap, "P2" = ascii greymap,
+%%% "P3" = ascii pixmap, "P4" = raw bitmap, 
+%%% "P5" = raw greymap, "P6" = raw pixmap
+if strcmp(type,'raw')
+  fprintf(fid,'P5\n');
+  format = 5;
+elseif strcmp(type,'ascii')
+  fprintf(fid,'P2\n');
+  format = 2;
+else
+  error(sprintf('PGMWRITE: Bad type argument: %s',type));
+end
+
+fprintf(fid,'# MatLab PGMWRITE file, saved %s\n',date);
+
+if (exist('comment') == 1)
+  fprintf(fid,'# %s\n', comment);
+end
+
+%%% dimensions
+fprintf(fid,'%d %d\n',size(mtx,2),size(mtx,1));
+
+%%% Maximum pixel value
+fprintf(fid,'255\n');
+
+
+%% MatLab's "fprintf" floors when writing floats, so we compute
+%% (mtx-r1)*255/(r2-r1)+0.5
+mult = (255 / (range(2)-range(1)));
+mtx = (mult * mtx) + (0.5 - mult * range(1));
+
+mtx = max(-0.5+eps,min(255.5-eps,mtx));
+
+if (format == 2)
+  count  = fprintf(fid,'%d ',mtx');
+elseif (format == 5)
+  count  = fwrite(fid,mtx','uchar');
+end
+
+fclose(fid);
+
+if (count ~= size(mtx,1)*size(mtx,2))
+  fprintf(1,'Warning: File output terminated early!');
+end
+          
+%%% TEST:
+% foo = 257*rand(100)-1;
+% pgmWrite(foo,'foo.pgm',[0 255]);
+% foo2=pgmRead('foo.pgm');
+% size(find((foo2-round(foo))~=0))
+% foo(find((foo2-round(foo))~=0))
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pixelAxes.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pixelAxes.m
new file mode 100755
index 0000000..f88210d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pixelAxes.m
@@ -0,0 +1,70 @@
+% [ZOOM] = pixelAxes(DIMS, ZOOM)
+%
+% Set the axes of the current plot to cover a multiple of DIMS pixels,
+% thereby eliminating screen aliasing artifacts when displaying an
+% image of size DIMS.  
+% 
+% ZOOM (optional, default='same') expresses the desired number of
+% samples displayed per screen pixel.  It should be a scalar, which
+% will be rounded to the nearest integer, or 1 over an integer.  It
+% may also be the string 'same' or 'auto', in which case the value is chosen so
+% as to produce an image closest in size to the currently displayed
+% image.  It may also be the string 'full', in which case the image is
+% made as large as possible while still fitting in the window.
+
+% Eero Simoncelli, 2/97.
+
+function [zoom] = pixelAxes(dims, zoom)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('zoom') ~= 1)
+  zoom = 'same';
+end
+
+%% Reverse  dimension order, since Figure Positions reported as (x,y).
+dims = dims(2:-1:1);
+
+%% Use MatLab's axis function to force square pixels, etc:
+axis('image');
+ax = gca;
+
+oldunits = get(ax,'Units');
+
+if strcmp(zoom,'full');
+  set(ax,'Units','normalized');
+  set(ax,'Position',[0 0 1 1]);
+  zoom = 'same';
+end
+
+set(ax,'Units','pixels');
+pos = get(ax,'Position');
+ctr = pos(1:2)+pos(3:4)/2;
+
+if (strcmp(zoom,'same') | strcmp(zoom,'auto'))
+  %% HACK: enlarge slightly so that floor doesn't round down 
+  zoom = min( pos(3:4) ./ (dims - 1) );
+elseif isstr(zoom)
+  error(sprintf('Bad ZOOM argument: %s',zoom));
+end
+
+%% Force zoom value to be an integer, or inverse integer.
+if (zoom < 0.75)
+  zoom = 1/ceil(1/zoom);
+  %% Round upward, subtracting 0.5 to avoid floating point errors.
+  newsz = ceil(zoom*(dims-0.5));
+else
+  zoom = floor(zoom + 0.001);           % Avoid floating pt errors
+  if (zoom < 1.5)                       % zoom=1
+    zoom = 1;
+    newsz = dims + 0.5;
+  else
+    newsz = zoom*(dims-1) + mod(zoom,2);
+  end
+end 
+
+set(ax,'Position', [floor(ctr-newsz/2)+0.5, newsz] )
+
+% Restore units
+set(ax,'Units',oldunits);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pointOp.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pointOp.m
new file mode 100755
index 0000000..890e60a
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pointOp.m
@@ -0,0 +1,28 @@
+% RES = pointOp(IM, LUT, ORIGIN, INCREMENT, WARNINGS)
+%
+% Apply a point operation, specified by lookup table LUT, to image IM.
+% LUT must be a row or column vector, and is assumed to contain
+% (equi-spaced) samples of the function.  ORIGIN specifies the
+% abscissa associated with the first sample, and INCREMENT specifies the
+% spacing between samples.  Between-sample values are estimated via
+% linear interpolation.  If WARNINGS is non-zero, the function prints
+% a warning whenever the lookup table is extrapolated.
+%
+% This function is much faster than MatLab's interp1, and allows
+% extrapolation beyond the lookup table domain.  The drawbacks are
+% that the lookup table must be equi-spaced, and the interpolation is
+% linear.
+
+% Eero Simoncelli, 8/96.
+
+function res = pointOp(im, lut, origin, increment, warnings)
+
+%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
+
+fprintf(1,'WARNING: You should compile the MEX version of "pointOp.c",\n         found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path.  It is MUCH faster.\n');
+
+X = origin + increment*[0:size(lut(:),1)-1];
+Y = lut(:);
+
+res = reshape(interp1(X, Y, im(:), 'linear', 'extrap'),size(im));
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pwd2path.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pwd2path.m
new file mode 100755
index 0000000..15aecf0
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pwd2path.m
@@ -0,0 +1,6 @@
+% PWD2PATH()
+%
+% add current working directory (pwd) to path.
+
+P = path;
+path(pwd,P);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBand.m
new file mode 100755
index 0000000..1fb6461
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBand.m
@@ -0,0 +1,11 @@
+% RES = pyrBand(PYR, INDICES, BAND_NUM)
+%
+% Access a subband from a pyramid (gaussian, laplacian, QMF/wavelet, 
+% or steerable).  Subbands are numbered consecutively, from finest
+% (highest spatial frequency) to coarsest (lowest spatial frequency).
+
+% Eero Simoncelli, 6/96.
+
+function res =  pyrBand(pyr, pind, band)
+
+res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) );
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBandIndices.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBandIndices.m
new file mode 100755
index 0000000..f94c217
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrBandIndices.m
@@ -0,0 +1,24 @@
+% RES = pyrBandIndices(INDICES, BAND_NUM)
+%
+% Return indices for accessing a subband from a pyramid 
+% (gaussian, laplacian, QMF/wavelet, steerable).
+
+% Eero Simoncelli, 6/96.
+
+function indices =  pyrBandIndices(pind,band)
+
+if ((band > size(pind,1)) | (band < 1))
+  error(sprintf('BAND_NUM must be between 1 and number of pyramid bands (%d).', ...
+      size(pind,1)));
+end
+
+if (size(pind,2) ~= 2)
+  error('INDICES must be an Nx2 matrix indicating the size of the pyramid subbands');
+end
+
+ind = 1;
+for l=1:band-1
+  ind = ind + prod(pind(l,:));
+end
+
+indices = ind:ind+prod(pind(band,:))-1;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrLow.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrLow.m
new file mode 100755
index 0000000..290e806
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/pyrLow.m
@@ -0,0 +1,12 @@
+% RES = pyrLow(PYR, INDICES)
+%
+% Access the lowpass subband from a pyramid 
+%   (gaussian, laplacian, QMF/wavelet, steerable).
+
+% Eero Simoncelli, 6/96.
+
+function res =  pyrLow(pyr,pind)
+
+band = size(pind,1);
+
+res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) );
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/range2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/range2.m
new file mode 100755
index 0000000..1709a0e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/range2.m
@@ -0,0 +1,18 @@
+% [MIN, MAX] = range2(MTX)
+%
+% Compute minimum and maximum values of MTX, returning them as a 2-vector.
+
+% Eero Simoncelli, 3/97.
+
+function [mn, mx] = range2(mtx)
+
+%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
+
+fprintf(1,'WARNING: You should compile the MEX version of "range2.c",\n         found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path.  It is MUCH faster.\n');
+
+if (~isreal(mtx))
+  error('MTX must be real-valued');  
+end
+
+mn = min(min(mtx));
+mx = max(max(mtx));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rconv2.m
new file mode 100755
index 0000000..0c12490
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rconv2.m
@@ -0,0 +1,50 @@
+% RES = RCONV2(MTX1, MTX2, CTR)
+%
+% Convolution of two matrices, with boundaries handled via reflection
+% about the edge pixels.  Result will be of size of LARGER matrix.
+% 
+% The origin of the smaller matrix is assumed to be its center.
+% For even dimensions, the origin is determined by the CTR (optional) 
+% argument:
+%      CTR   origin
+%       0     DIM/2      (default)
+%       1     (DIM/2)+1  
+
+% Eero Simoncelli, 6/96.
+
+function c = rconv2(a,b,ctr)
+
+if (exist('ctr') ~= 1)
+  ctr = 0;
+end
+
+if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
+    large = a; small = b;
+elseif  (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
+    large = b; small = a;
+else
+  error('one arg must be larger than the other in both dimensions!');
+end
+
+ly = size(large,1);
+lx = size(large,2);
+sy = size(small,1);
+sx = size(small,2);
+
+%% These values are one less than the index of the small mtx that falls on 
+%% the border pixel of the large matrix when computing the first 
+%% convolution response sample:
+sy2 = floor((sy+ctr-1)/2);
+sx2 = floor((sx+ctr-1)/2);
+
+% pad with reflected copies
+clarge = [ 
+    large(sy-sy2:-1:2,sx-sx2:-1:2), large(sy-sy2:-1:2,:), ...
+        large(sy-sy2:-1:2,lx-1:-1:lx-sx2); ...
+    large(:,sx-sx2:-1:2),    large,   large(:,lx-1:-1:lx-sx2); ...
+    large(ly-1:-1:ly-sy2,sx-sx2:-1:2), ...
+      large(ly-1:-1:ly-sy2,:), ...
+      large(ly-1:-1:ly-sy2,lx-1:-1:lx-sx2) ];
+
+c = conv2(clarge,small,'valid');
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rcosFn.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rcosFn.m
new file mode 100755
index 0000000..5dac344
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/rcosFn.m
@@ -0,0 +1,45 @@
+% [X, Y] = rcosFn(WIDTH, POSITION, VALUES)
+%
+% Return a lookup table (suitable for use by INTERP1) 
+% containing a "raised cosine" soft threshold function:
+% 
+%    Y =  VALUES(1) + (VALUES(2)-VALUES(1)) *
+%              cos^2( PI/2 * (X - POSITION + WIDTH)/WIDTH )
+%
+% WIDTH is the width of the region over which the transition occurs
+% (default = 1). POSITION is the location of the center of the
+% threshold (default = 0).  VALUES (default = [0,1]) specifies the
+% values to the left and right of the transition.
+
+% Eero Simoncelli, 7/96.
+
+function [X, Y] = rcosFn(width,position,values)
+
+%------------------------------------------------------------
+% OPTIONAL ARGS:
+
+if (exist('width') ~= 1)
+  width = 1;
+end
+
+if (exist('position') ~= 1)
+  position = 0;
+end
+
+if (exist('values') ~= 1)
+  values = [0,1];
+end
+
+%------------------------------------------------------------
+
+sz = 256;  %% arbitrary!
+
+X    = pi * [-sz-1:1] / (2*sz);
+
+Y = values(1) + (values(2)-values(1)) * cos(X).^2;
+
+%    Make sure end values are repeated, for extrapolation...
+Y(1) = Y(2);
+Y(sz+3) = Y(sz+2);
+
+X = position + (2*width/pi) * (X + pi/4);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconLpyr.m
new file mode 100755
index 0000000..cddcc12
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconLpyr.m
@@ -0,0 +1,83 @@
+% RES = reconLpyr(PYR, INDICES, LEVS, FILT2, EDGES)
+%
+% Reconstruct image from Laplacian pyramid, as created by buildLpyr.
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+%
+% LEVS (optional) should be a list of levels to include, or the string
+% 'all' (default).  The finest scale is number 1.  The lowpass band
+% corresponds to lpyrHt(INDICES)+1.
+%
+% FILT2 (optional) can be a string naming a standard filter (see
+% namedFilter), or a vector which will be used for (separable)
+% convolution.  Default = 'binom5'.  EDGES specifies edge-handling,
+% and defaults to 'reflect1' (see corrDn).
+
+% Eero Simoncelli, 6/96
+
+function res = reconLpyr(pyr, ind, levs, filt2, edges)
+
+if (nargin < 2)
+  error('First two arguments (PYR, INDICES) are required');
+end
+  
+%%------------------------------------------------------------
+%% DEFAULTS:
+
+if (exist('levs') ~= 1)
+  levs = 'all';
+end
+
+if (exist('filt2') ~= 1)
+  filt2 = 'binom5';
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+%%------------------------------------------------------------
+
+maxLev =  1+lpyrHt(ind);
+if strcmp(levs,'all')
+  levs = [1:maxLev]';
+else
+  if (any(levs > maxLev))
+    error(sprintf('Level numbers must be in the range [1, %d].', maxLev));
+  end
+  levs = levs(:);
+end
+
+if isstr(filt2)
+  filt2 = namedFilter(filt2);
+end
+
+filt2 = filt2(:);
+res_sz = ind(1,:);
+
+if any(levs > 1)
+
+  int_sz = [ind(1,1), ind(2,2)];
+  
+  nres = reconLpyr( pyr(prod(res_sz)+1:size(pyr,1)), ...
+      ind(2:size(ind,1),:), levs-1, filt2, edges);
+  
+  if (res_sz(1) == 1)
+    res = upConv(nres, filt2', edges, [1 2], [1 1], res_sz);
+  elseif (res_sz(2) == 1)
+    res = upConv(nres, filt2, edges, [2 1], [1 1], res_sz);
+  else
+    hi = upConv(nres, filt2, edges, [2 1], [1 1], int_sz);
+    res = upConv(hi, filt2', edges, [1 2], [1 1], res_sz);
+  end
+
+else
+  
+  res = zeros(res_sz);
+
+end
+
+if any(levs == 1)
+  res = res + pyrBand(pyr,ind,1);
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSCFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSCFpyr.m
new file mode 100755
index 0000000..a86f03d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSCFpyr.m
@@ -0,0 +1,87 @@
+% RES = reconSCFpyr(PYR, INDICES, LEVS, BANDS, TWIDTH)
+%
+% The inverse of buildSCFpyr: Reconstruct image from its complex steerable pyramid representation,
+% in the Fourier domain.
+%
+% The image is reconstructed by forcing the complex subbands to be analytic
+% (zero on half of the 2D Fourier plane, as they are supossed to be unless
+% they have being modified), and reconstructing from the real part of those
+% analytic subbands. That is equivalent to compute the Hilbert transforms of
+% the imaginary parts of the subbands, average them with their real
+% counterparts, and then reconstructing from the resulting real subbands.
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+%
+% LEVS (optional) should be a list of levels to include, or the string
+% 'all' (default).  0 corresonds to the residual highpass subband.
+% 1 corresponds to the finest oriented scale.  The lowpass band
+% corresponds to number spyrHt(INDICES)+1.
+%
+% BANDS (optional) should be a list of bands to include, or the string
+% 'all' (default).  1 = vertical, rest proceeding anti-clockwise.
+%
+% TWIDTH is the width of the transition region of the radial lowpass
+% function, in octaves (default = 1, which gives a raised cosine for
+% the bandpass filters).
+                                                                                                                        
+% Javier Portilla, 7/04, basing on Eero Simoncelli's Matlab Pyrtools code
+% and our common code on texture synthesis (textureSynthesis.m).
+                                                                                                                        
+function res = reconSCFpyr(pyr, indices, levs, bands, twidth)
+                                                                                                                        
+%%------------------------------------------------------------
+%% DEFAULTS:
+                                                                                                                        
+if ~exist('levs'),
+  levs = 'all';
+end
+                                                                                                                        
+if ~exist('bands')
+  bands = 'all';
+end
+                                                                                                                        
+if ~exist('twidth'),
+  twidth = 1;
+elseif (twidth <= 0)
+  fprintf(1,'Warning: TWIDTH must be positive.  Setting to 1.\n');
+  twidth = 1;
+end
+                                                                                                                        
+%%------------------------------------------------------------
+                                                                                                                        
+                                                                                                                        
+pind = indices;
+Nsc = log2(pind(1,1)/pind(end,1));
+Nor = (size(pind,1)-2)/Nsc;
+                                                                                                                        
+for nsc = 1:Nsc,
+    firstBnum = (nsc-1)*Nor+2;
+                                                                                                                        
+%% Re-create analytic subbands
+    dims = pind(firstBnum,:);
+    ctr = ceil((dims+0.5)/2);
+    ang = mkAngle(dims, 0, ctr);
+    ang(ctr(1),ctr(2)) = -pi/2;
+    for nor = 1:Nor,
+      nband = (nsc-1)*Nor+nor+1;
+      ind = pyrBandIndices(pind,nband);
+      ch = pyrBand(pyr, pind, nband);
+      ang0 = pi*(nor-1)/Nor;
+      xang = mod(ang-ang0+pi, 2*pi) - pi;
+      amask = 2*(abs(xang) < pi/2) + (abs(xang) == pi/2);
+      amask(ctr(1),ctr(2)) = 1;
+      amask(:,1) = 1;
+      amask(1,:) = 1;
+      amask = fftshift(amask);
+      ch = ifft2(amask.*fft2(ch));    % "Analytic" version
+      %f = 1.000008;  % With this factor the reconstruction SNR goes up around 6 dB!
+      f = 1;
+      ch = f*0.5*real(ch); % real part
+      pyr(ind) = ch;
+    end     % nor
+end         % nsc
+                                                                                                                        
+res = reconSFpyr(pyr, indices, levs, bands, twidth);
+                                                                                                                        
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyr.m
new file mode 100755
index 0000000..0e3109e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyr.m
@@ -0,0 +1,108 @@
+% RES = reconSFpyr(PYR, INDICES, LEVS, BANDS, TWIDTH)
+%
+% Reconstruct image from its steerable pyramid representation, in the Fourier
+% domain, as created by buildSFpyr.
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+%
+% LEVS (optional) should be a list of levels to include, or the string
+% 'all' (default).  0 corresonds to the residual highpass subband.  
+% 1 corresponds to the finest oriented scale.  The lowpass band
+% corresponds to number spyrHt(INDICES)+1.
+%
+% BANDS (optional) should be a list of bands to include, or the string
+% 'all' (default).  1 = vertical, rest proceeding anti-clockwise.
+%
+% TWIDTH is the width of the transition region of the radial lowpass
+% function, in octaves (default = 1, which gives a raised cosine for
+% the bandpass filters).
+
+%%% MODIFIED VERSION, 7/04, uses different lookup table for radial frequency!
+
+% Eero Simoncelli, 5/97.
+
+function res = reconSFpyr(pyr, pind, levs, bands, twidth)
+
+%%------------------------------------------------------------
+%% DEFAULTS:
+
+if (exist('levs') ~= 1)
+  levs = 'all';
+end
+
+if (exist('bands') ~= 1)
+  bands = 'all';
+end
+
+if (exist('twidth') ~= 1)
+  twidth = 1;
+elseif (twidth <= 0)
+  fprintf(1,'Warning: TWIDTH must be positive.  Setting to 1.\n');
+  twidth = 1;
+end
+
+%%------------------------------------------------------------
+
+nbands = spyrNumBands(pind);
+
+maxLev =  1+spyrHt(pind);
+if strcmp(levs,'all')
+  levs = [0:maxLev]';
+else
+  if (any(levs > maxLev) | any(levs < 0))
+    error(sprintf('Level numbers must be in the range [0, %d].', maxLev));
+  end
+  levs = levs(:);
+end
+
+if strcmp(bands,'all')
+  bands = [1:nbands]';
+else
+  if (any(bands < 1) | any(bands > nbands))
+    error(sprintf('Band numbers must be in the range [1,3].', nbands));
+  end
+  bands = bands(:);
+end
+
+%----------------------------------------------------------------------
+
+dims = pind(1,:);
+ctr = ceil((dims+0.5)/2);
+
+[xramp,yramp] = meshgrid( ([1:dims(2)]-ctr(2))./(dims(2)/2), ...
+    ([1:dims(1)]-ctr(1))./(dims(1)/2) );
+angle = atan2(yramp,xramp);
+log_rad = sqrt(xramp.^2 + yramp.^2);
+log_rad(ctr(1),ctr(2)) =  log_rad(ctr(1),ctr(2)-1);
+log_rad  = log2(log_rad);
+
+%% Radial transition function (a raised cosine in log-frequency):
+[Xrcos,Yrcos] = rcosFn(twidth,(-twidth/2),[0 1]);
+Yrcos = sqrt(Yrcos);
+YIrcos = sqrt(abs(1.0 - Yrcos.^2));
+
+if (size(pind,1) == 2)
+  if (any(levs==1))
+    resdft = fftshift(fft2(pyrBand(pyr,pind,2)));
+  else
+    resdft = zeros(pind(2,:));
+  end
+else
+  resdft = reconSFpyrLevs(pyr(1+prod(pind(1,:)):size(pyr,1)), ...
+      pind(2:size(pind,1),:), ...
+      log_rad, Xrcos, Yrcos, angle, nbands, levs, bands);
+end
+
+lo0mask = pointOp(log_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+resdft = resdft .* lo0mask;
+
+%% residual highpass subband
+if any(levs == 0)
+  hi0mask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+  hidft = fftshift(fft2(subMtx(pyr, pind(1,:))));
+  resdft = resdft + hidft .* hi0mask;
+end
+ 
+res = real(ifft2(ifftshift(resdft)));
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyrLevs.m
new file mode 100755
index 0000000..420f278
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSFpyrLevs.m
@@ -0,0 +1,69 @@
+% RESDFT = reconSFpyrLevs(PYR,INDICES,LOGRAD,XRCOS,YRCOS,ANGLE,NBANDS,LEVS,BANDS)
+%
+% Recursive function for reconstructing levels of a steerable pyramid
+% representation.  This is called by reconSFpyr, and is not usually
+% called directly.
+
+% Eero Simoncelli, 5/97.
+
+function resdft = reconSFpyrLevs(pyr,pind,log_rad,Xrcos,Yrcos,angle,nbands,levs,bands);
+
+lo_ind = nbands+1;
+dims = pind(1,:);
+ctr = ceil((dims+0.5)/2);
+
+%  log_rad = log_rad + 1;
+Xrcos = Xrcos - log2(2);  % shift origin of lut by 1 octave.
+
+if any(levs > 1)
+
+  lodims = ceil((dims-0.5)/2);
+  loctr = ceil((lodims+0.5)/2);
+  lostart = ctr-loctr+1;
+  loend = lostart+lodims-1;
+  nlog_rad = log_rad(lostart(1):loend(1),lostart(2):loend(2));
+  nangle = angle(lostart(1):loend(1),lostart(2):loend(2));
+
+  if  (size(pind,1) > lo_ind)
+    nresdft = reconSFpyrLevs( pyr(1+sum(prod(pind(1:lo_ind-1,:)')):size(pyr,1)),...
+        pind(lo_ind:size(pind,1),:), ...
+        nlog_rad, Xrcos, Yrcos, nangle, nbands,levs-1, bands);
+  else
+    nresdft = fftshift(fft2(pyrBand(pyr,pind,lo_ind)));
+  end
+
+  YIrcos = sqrt(abs(1.0 - Yrcos.^2));
+  lomask = pointOp(nlog_rad, YIrcos, Xrcos(1), Xrcos(2)-Xrcos(1), 0);
+
+  resdft = zeros(dims);
+  resdft(lostart(1):loend(1),lostart(2):loend(2)) = nresdft .* lomask;
+
+else
+
+  resdft = zeros(dims);
+
+end
+
+        
+if any(levs == 1)
+
+  lutsize = 1024;
+  Xcosn = pi*[-(2*lutsize+1):(lutsize+1)]/lutsize;  % [-2*pi:pi]
+  order = nbands-1;
+  %% divide by sqrt(sum_(n=0)^(N-1)  cos(pi*n/N)^(2(N-1)) )
+  const = (2^(2*order))*(factorial(order)^2)/(nbands*factorial(2*order));
+  Ycosn = sqrt(const) * (cos(Xcosn)).^order;
+  himask = pointOp(log_rad, Yrcos, Xrcos(1), Xrcos(2)-Xrcos(1),0);
+
+  ind = 1;
+  for b = 1:nbands
+    if any(bands == b)
+      anglemask = pointOp(angle,Ycosn,Xcosn(1)+pi*(b-1)/nbands,Xcosn(2)-Xcosn(1));
+      band = reshape(pyr(ind:ind+prod(dims)-1), dims(1), dims(2));
+      banddft = fftshift(fft2(band));
+      resdft = resdft + (sqrt(-1))^(nbands-1) * banddft.*anglemask.*himask;
+    end
+    ind = ind + prod(dims);
+  end
+end
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyr.m
new file mode 100755
index 0000000..270009d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyr.m
@@ -0,0 +1,96 @@
+% RES = reconSpyr(PYR, INDICES, FILTFILE, EDGES, LEVS, BANDS)
+%
+% Reconstruct image from its steerable pyramid representation, as created
+% by buildSpyr.
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+%
+% FILTFILE (optional) should be a string referring to an m-file that returns
+% the rfilters.  examples: sp0Filters, sp1Filters, sp3Filters 
+% (default = 'sp1Filters'). 
+% EDGES specifies edge-handling, and defaults to 'reflect1' (see
+% corrDn).
+% 
+% LEVS (optional) should be a list of levels to include, or the string
+% 'all' (default).  0 corresonds to the residual highpass subband.  
+% 1 corresponds to the finest oriented scale.  The lowpass band
+% corresponds to number spyrHt(INDICES)+1.
+%
+% BANDS (optional) should be a list of bands to include, or the string
+% 'all' (default).  1 = vertical, rest proceeding anti-clockwise.
+
+% Eero Simoncelli, 6/96.
+
+function res = reconSpyr(pyr, pind, filtfile, edges, levs, bands)
+
+%%------------------------------------------------------------
+%% DEFAULTS:
+
+if (exist('filtfile') ~= 1)
+  filtfile = 'sp1Filters';
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+if (exist('levs') ~= 1)
+  levs = 'all';
+end
+
+if (exist('bands') ~= 1)
+  bands = 'all';
+end
+
+%%------------------------------------------------------------
+
+if (isstr(filtfile) & (exist(filtfile) == 2))
+   [lo0filt,hi0filt,lofilt,bfilts,steermtx,harmonics] = eval(filtfile);
+   nbands = spyrNumBands(pind);
+   if ((nbands > 0) & (size(bfilts,2) ~= nbands))
+     error('Number of pyramid bands is inconsistent with filter file');
+   end
+else
+  error('filtfile argument must be the name of an M-file containing SPYR filters.');
+end
+
+maxLev =  1+spyrHt(pind);
+if strcmp(levs,'all')
+  levs = [0:maxLev]';
+else
+  if (any(levs > maxLev) | any(levs < 0))
+    error(sprintf('Level numbers must be in the range [0, %d].', maxLev));
+  end
+  levs = levs(:);
+end
+
+if strcmp(bands,'all')
+  bands = [1:nbands]';
+else
+  if (any(bands < 1) | any(bands > nbands))
+    error(sprintf('Band numbers must be in the range [1,3].', nbands));
+  end
+  bands = bands(:);
+end
+
+if (spyrHt(pind) == 0)
+  if (any(levs==1))
+    res1 = pyrBand(pyr,pind,2);
+  else
+    res1 = zeros(pind(2,:));
+  end
+else
+  res1 = reconSpyrLevs(pyr(1+prod(pind(1,:)):size(pyr,1)), ...
+      pind(2:size(pind,1),:), ...
+      lofilt, bfilts, edges, levs, bands);
+end
+
+res = upConv(res1, lo0filt, edges);
+
+%% residual highpass subband
+if any(levs == 0)
+   upConv( subMtx(pyr, pind(1,:)), hi0filt, edges, [1 1], [1 1], size(res), res);
+end
+ 
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyrLevs.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyrLevs.m
new file mode 100755
index 0000000..f8e456c
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconSpyrLevs.m
@@ -0,0 +1,46 @@
+% RES = reconSpyrLevs(PYR,INDICES,LOFILT,BFILTS,EDGES,LEVS,BANDS)
+%
+% Recursive function for reconstructing levels of a steerable pyramid
+% representation.  This is called by reconSpyr, and is not usually
+% called directly.
+
+% Eero Simoncelli, 6/96.
+
+function res = reconSpyrLevs(pyr,pind,lofilt,bfilts,edges,levs,bands);
+
+nbands = size(bfilts,2);
+lo_ind = nbands+1;
+res_sz = pind(1,:);
+
+% Assume square filters:
+bfiltsz =  round(sqrt(size(bfilts,1)));
+
+if any(levs > 1)
+
+  if  (size(pind,1) > lo_ind)
+    nres = reconSpyrLevs( pyr(1+sum(prod(pind(1:lo_ind-1,:)')):size(pyr,1)),  ...
+        pind(lo_ind:size(pind,1),:), ...
+        lofilt, bfilts, edges, levs-1, bands);
+  else
+    nres = pyrBand(pyr,pind,lo_ind);    % lowpass subband
+  end
+
+  res = upConv(nres, lofilt, edges, [2 2], [1 1], res_sz);
+
+else
+
+  res = zeros(res_sz);
+
+end
+        
+if any(levs == 1)
+  ind = 1;
+  for b = 1:nbands
+    if any(bands == b)
+      bfilt = reshape(bfilts(:,b), bfiltsz, bfiltsz);
+      upConv(reshape(pyr(ind:ind+prod(res_sz)-1), res_sz(1), res_sz(2)), ...
+                  bfilt, edges, [1 1], [1 1], res_sz, res);
+    end
+    ind = ind + prod(res_sz);
+  end
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconWpyr.m
new file mode 100755
index 0000000..fc31226
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/reconWpyr.m
@@ -0,0 +1,148 @@
+% RES = reconWpyr(PYR, INDICES, FILT, EDGES, LEVS, BANDS)
+%
+% Reconstruct image from its separable orthonormal QMF/wavelet pyramid
+% representation, as created by buildWpyr.
+%
+% PYR is a vector containing the N pyramid subbands, ordered from fine
+% to coarse.  INDICES is an Nx2 matrix containing the sizes of
+% each subband.  This is compatible with the MatLab Wavelet toolbox.
+%
+% FILT (optional) can be a string naming a standard filter (see
+% namedFilter), or a vector which will be used for (separable)
+% convolution.  Default = 'qmf9'.  EDGES specifies edge-handling,
+% and defaults to 'reflect1' (see corrDn).
+%
+% LEVS (optional) should be a vector of levels to include, or the string
+% 'all' (default).  1 corresponds to the finest scale.  The lowpass band
+% corresponds to wpyrHt(INDICES)+1.
+%
+% BANDS (optional) should be a vector of bands to include, or the string
+% 'all' (default).   1=horizontal, 2=vertical, 3=diagonal.  This is only used
+% for pyramids of 2D images.
+
+% Eero Simoncelli, 6/96.
+
+function res = reconWpyr(pyr, ind, filt, edges, levs, bands)
+
+if (nargin < 2)
+  error('First two arguments (PYR INDICES) are required');
+end
+
+%%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('filt') ~= 1)
+  filt = 'qmf9';
+end
+
+if (exist('edges') ~= 1)
+  edges= 'reflect1';
+end
+
+if (exist('levs') ~= 1)
+  levs = 'all';
+end
+
+if (exist('bands') ~= 1)
+  bands = 'all';
+end
+
+%%------------------------------------------------------------
+
+maxLev = 1+wpyrHt(ind);
+if strcmp(levs,'all')
+  levs = [1:maxLev]';
+else
+  if (any(levs > maxLev))
+    error(sprintf('Level numbers must be in the range [1, %d].', maxLev));
+  end
+  levs = levs(:);
+end
+
+if strcmp(bands,'all')
+  bands = [1:3]';
+else
+  if (any(bands < 1) | any(bands > 3))
+    error('Band numbers must be in the range [1,3].');
+  end
+  bands = bands(:);
+end
+
+if isstr(filt)
+  filt = namedFilter(filt);
+end
+
+filt = filt(:);
+hfilt = modulateFlip(filt);
+
+%% For odd-length filters, stagger the sampling lattices:
+if (mod(size(filt,1),2) == 0)
+        stag = 2;
+else
+        stag = 1;
+end
+
+%% Compute size of result image: assumes critical sampling (boundaries correct)
+res_sz = ind(1,:);
+if (res_sz(1) == 1)
+  loind = 2;
+  res_sz(2) = sum(ind(:,2));
+elseif (res_sz(2) == 1) 
+  loind = 2;
+  res_sz(1) = sum(ind(:,1));
+else
+  loind = 4;
+  res_sz = ind(1,:) + ind(2,:);  %%horizontal + vertical bands.
+  hres_sz = [ind(1,1), res_sz(2)];
+  lres_sz = [ind(2,1), res_sz(2)];
+end
+        
+
+%% First, recursively collapse coarser scales:
+if any(levs > 1)  
+
+  if (size(ind,1) > loind)
+    nres = reconWpyr( pyr(1+sum(prod(ind(1:loind-1,:)')):size(pyr,1)), ...
+        ind(loind:size(ind,1),:), filt, edges, levs-1, bands);
+  else
+    nres = pyrBand(pyr, ind, loind);    % lowpass subband
+  end
+
+  if (res_sz(1) == 1)
+    res = upConv(nres, filt', edges, [1 2], [1 stag], res_sz);
+  elseif (res_sz(2) == 1)
+    res = upConv(nres, filt, edges, [2 1], [stag 1], res_sz);
+  else
+    ires = upConv(nres, filt', edges, [1 2], [1 stag], lres_sz); 
+    res = upConv(ires, filt, edges, [2 1], [stag 1], res_sz);
+  end
+  
+else
+
+  res = zeros(res_sz);
+
+end
+
+        
+%% Add  in reconstructed bands from this level:
+if any(levs == 1)
+  if (res_sz(1) == 1)
+    upConv(pyrBand(pyr,ind,1), hfilt', edges, [1 2], [1 2], res_sz, res);
+  elseif (res_sz(2) == 1)
+    upConv(pyrBand(pyr,ind,1), hfilt, edges, [2 1], [2 1], res_sz, res);
+  else
+    if any(bands == 1) % horizontal
+      ires = upConv(pyrBand(pyr,ind,1),filt',edges,[1 2],[1 stag],hres_sz);
+      upConv(ires,hfilt,edges,[2 1],[2 1],res_sz,res);  %destructively modify res
+    end
+    if any(bands == 2) % vertical
+      ires = upConv(pyrBand(pyr,ind,2),hfilt',edges,[1 2],[1 2],lres_sz);
+      upConv(ires,filt,edges,[2 1],[stag 1],res_sz,res);  %destructively modify res
+    end
+    if any(bands == 3) % diagonal
+      ires =  upConv(pyrBand(pyr,ind,3),hfilt',edges,[1 2],[1 2],hres_sz);
+      upConv(ires,hfilt,edges,[2 1],[2 1],res_sz,res);  %destructively modify res
+    end
+  end
+end
+  
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/setPyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/setPyrBand.m
new file mode 100755
index 0000000..baa9f77
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/setPyrBand.m
@@ -0,0 +1,32 @@
+% NEWPYR = setPyrBand(PYR, INDICES, BAND, BAND_NUM)
+%
+% Insert an image (BAND) into a pyramid (gaussian, laplacian, QMF/wavelet, 
+% or steerable).  Subbands are numbered consecutively, from finest
+% (highest spatial frequency) to coarsest (lowest spatial frequency).
+
+% Eero Simoncelli, 1/03.
+
+function pyr =  pyrBand(pyr, pind, band, bandNum)
+
+%% Check: PIND a valid index matrix?
+if ( ~(ndims(pind) == 2) | ~(size(pind,2) == 2) | ~all(pind==round(pind)) )
+  pind
+  error('pyrTools:badArg',...
+      'PIND argument is not an Nbands X 2 matrix of integers');
+end
+
+%% Check: PIND consistent with size of PYR?
+if ( length(pyr) ~= sum(prod(pind,2)) )
+  error('pyrTools:badPyr',...
+      'Pyramid data vector length is inconsistent with index matrix PIND');
+end
+
+%% Check: size of BAND  consistent with desired BANDNUM?
+if (~all(size(band) == pind(bandNum,:)))
+  size(band)
+  pind(bandNum,:)
+  error('pyrTools:badArg',...
+      'size of BAND to be inserted is inconsistent with BAND_NUM');
+end
+
+pyr(pyrBandIndices(pind,bandNum)) = vectify(band); 
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/shift.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/shift.m
new file mode 100755
index 0000000..497297e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/shift.m
@@ -0,0 +1,15 @@
+% [RES] = shift(MTX, OFFSET)
+% 
+% Circular shift 2D matrix samples by OFFSET (a [Y,X] 2-vector),
+% such that  RES(POS) = MTX(POS-OFFSET).
+
+function res = shift(mtx, offset)
+
+dims = size(mtx);
+
+offset = mod(-offset,dims);
+
+res = [ mtx(offset(1)+1:dims(1), offset(2)+1:dims(2)),  ...
+          mtx(offset(1)+1:dims(1), 1:offset(2));        ...
+        mtx(1:offset(1), offset(2)+1:dims(2)),          ...
+          mtx(1:offset(1), 1:offset(2)) ];
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showIm.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showIm.m
new file mode 100755
index 0000000..a9e2bd1
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showIm.m
@@ -0,0 +1,221 @@
+% RANGE = showIm (MATRIX, RANGE, ZOOM, LABEL, NSHADES )
+% 
+% Display a MatLab MATRIX as a grayscale image in the current figure,
+% inside the current axes.  If MATRIX is complex, the real and imaginary 
+% parts are shown side-by-side, with the same grayscale mapping.
+% 
+% If MATRIX is a string, it should be the name of a variable bound to a 
+% MATRIX in the base (global) environment.  This matrix is displayed as an 
+% image, with the title set to the string.
+% 
+% RANGE (optional) is a 2-vector specifying the values that map to
+% black and white, respectively.  Passing a value of 'auto' (default)
+% sets RANGE=[min,max] (as in MatLab's imagesc).  'auto2' sets
+% RANGE=[mean-2*stdev, mean+2*stdev].  'auto3' sets
+% RANGE=[p1-(p2-p1)/8, p2+(p2-p1)/8], where p1 is the 10th percentile
+% value of the sorted MATRIX samples, and p2 is the 90th percentile
+% value.
+% 
+% ZOOM specifies the number of matrix samples per screen pixel.  It
+% will be rounded to an integer, or 1 divided by an integer.  A value
+% of 'same' or 'auto' (default) causes the zoom value to be chosen
+% automatically to fit the image into the current axes.  A value of
+% 'full' fills the axis region (leaving no room for labels).  See
+% pixelAxes.m.
+% 
+% If LABEL (optional, default = 1, unless zoom='full') is non-zero, the range 
+% of values that are mapped into the gray colormap and the dimensions 
+% (size) of the matrix and zoom factor are printed below the image.  If label 
+% is a string, it is used as a title.
+% 
+% NSHADES (optional) specifies the number of gray shades, and defaults
+% to the size of the current colormap.
+
+% Eero Simoncelli, 6/96.
+
+%%TODO: should use "newplot"
+
+function range = showIm( im, range, zoom, label, nshades );
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (nargin < 1)
+  error('Requires at least one input argument.'); 
+end
+
+MLv = version;
+
+if isstr(im)
+  if (strcmp(MLv(1),'4'))
+    error('Cannot pass string arg for MATRIX in MatLab version 4.x');
+  end
+  label = im;
+  im = evalin('base',im);
+end
+
+if (exist('range') ~= 1)
+  range = 'auto1';
+end
+
+if (exist('nshades') ~= 1)
+  nshades = size(colormap,1);
+end
+nshades = max( nshades, 2 );
+
+if (exist('zoom') ~= 1)
+  zoom = 'auto';
+end
+
+if (exist('label') ~= 1)
+  if strcmp(zoom,'full')
+    label = 0;                          % no labeling
+  else                                  
+    label = 1;                          % just print grayrange & dims
+  end
+end
+
+%------------------------------------------------------------
+
+%% Automatic range calculation: 
+if (strcmp(range,'auto1') | strcmp(range,'auto'))
+  if isreal(im)
+    [mn,mx] = range2(im);
+  else
+    [mn1,mx1] = range2(real(im));
+    [mn2,mx2] =  range2(imag(im));
+    mn = min(mn1,mn2);
+    mx = max(mx1,mx2);
+  end
+  if any(size(im)==1)
+    pad = (mx-mn)/12;                   % MAGIC NUMBER: graph padding
+    range = [mn-pad, mx+pad];
+  else
+    range = [mn,mx];
+  end
+
+elseif strcmp(range,'auto2')
+  if isreal(im)
+    stdev = sqrt(var2(im));
+    av = mean2(im);
+  else
+    stdev = sqrt((var2(real(im)) + var2(imag(im)))/2);
+    av = (mean2(real(im)) + mean2(imag(im)))/2;
+  end
+  range = [av-2*stdev,av+2*stdev];      % MAGIC NUMBER: 2 stdevs
+
+elseif strcmp(range, 'auto3')
+  percentile = 0.1;                     % MAGIC NUMBER: 0<p<0.5
+  [N,X] = histo(im);
+  binsz = X(2)-X(1);
+  N = N+1e-10;  % Ensure cumsum will be monotonic for call to interp1
+  cumN = [0, cumsum(N)]/sum(N);
+  cumX = [X(1)-binsz, X] + (binsz/2);
+  ctrRange = interp1(cumN,cumX, [percentile, 1-percentile]);
+  range = mean(ctrRange) + (ctrRange-mean(ctrRange))/(1-2*percentile);
+
+elseif isstr(range)
+  error(sprintf('Bad RANGE argument: %s',range))
+
+end
+
+if ((range(2) - range(1)) <= eps)
+  range(1) = range(1) - 0.5;
+  range(2) = range(2) + 0.5;
+end
+
+
+if isreal(im)
+  factor=1;
+else
+  factor = 1+sqrt(-1);
+end
+
+xlbl_offset = 0; % default value
+
+if (~any(size(im)==1))
+  %% MatLab's "image" rounds when mapping to the colormap, so we compute
+  %%      (im-r1)*(nshades-1)/(r2-r1) + 1.5 
+  mult = ((nshades-1) / (range(2)-range(1)));
+  d_im = (mult * im) + factor*(1.5 - range(1)*mult);
+end
+
+if isreal(im)
+  if (any(size(im)==1))
+    hh = plot( im);
+    axis([1, prod(size(im)), range]);
+  else
+    hh = image( d_im );
+    axis('off');
+    zoom = pixelAxes(size(d_im),zoom);
+  end
+else
+  if (any(size(im)==1))
+    subplot(2,1,1);
+    hh = plot(real(im));
+    axis([1, prod(size(im)), range]);
+    subplot(2,1,2);
+    hh = plot(imag(im));
+    axis([1, prod(size(im)), range]);
+  else
+    subplot(1,2,1);
+    hh = image(real(d_im));
+    axis('off'); zoom = pixelAxes(size(d_im),zoom);
+    ax = gca; orig_units = get(ax,'Units');
+    set(ax,'Units','points');
+    pos1 = get(ax,'Position');
+    set(ax,'Units',orig_units);
+    subplot(1,2,2);
+    hh = image(imag(d_im));
+    axis('off'); zoom = pixelAxes(size(d_im),zoom);
+    ax = gca; orig_units = get(ax,'Units');
+    set(ax,'Units','points');
+    pos2 = get(ax,'Position');
+    set(ax,'Units',orig_units);
+    xlbl_offset = (pos1(1)-pos2(1))/2;
+  end
+end  
+
+if ~any(size(im)==1)
+  colormap(gray(nshades));
+end
+
+if ((label ~= 0))
+  if isstr(label)
+    title(label);
+    h = get(gca,'Title');
+    orig_units = get(h,'Units');
+    set(h,'Units','points');
+    pos = get(h,'Position');
+    pos(1:2) = pos(1:2) + [xlbl_offset, -3]; % MAGIC NUMBER: y pixel offset
+    set(h,'Position',pos);
+    set(h,'Units',orig_units);
+  end
+
+  if (~any(size(im)==1))
+    if (zoom > 1)
+      zformat = sprintf('* %d',round(zoom));
+    else
+      zformat = sprintf('/ %d',round(1/zoom));
+    end
+    if isreal(im) 
+      format=[' Range: [%.3g, %.3g] \n Dims: [%d, %d] ', zformat];
+        else
+      format=['Range: [%.3g, %.3g]  ----  Dims: [%d, %d]', zformat];
+    end
+    xlabel(sprintf(format, range(1), range(2), size(im,1), size(im,2)));
+    h = get(gca,'Xlabel');
+    set(h,'FontSize', 9);               % MAGIC NUMBER: font size!!!
+
+    orig_units = get(h,'Units');
+    set(h,'Units','points');  
+    pos = get(h,'Position');
+    pos(1:2) = pos(1:2) + [xlbl_offset, 10]; % MAGIC NUMBER: y offset in points
+    set(h,'Position',pos);
+    set(h,'Units',orig_units);
+
+    set(h,'Visible','on');              % axis('image') turned the  xlabel  off...
+  end
+end
+
+return;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showLpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showLpyr.m
new file mode 100755
index 0000000..0d85f9d
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showLpyr.m
@@ -0,0 +1,202 @@
+% RANGE = showLpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR)
+% 
+% Display a Laplacian (or Gaussian) pyramid, specified by PYR and
+% INDICES (see buildLpyr), in the current figure.
+% 
+% RANGE is a 2-vector specifying the values that map to black and
+% white, respectively.  These values are scaled by
+% LEVEL_SCALE_FACTOR^(lev-1) for bands at each level.  Passing a value
+% of 'auto1' sets RANGE to the min and max values of MATRIX.  'auto2'
+% sets RANGE to 3 standard deviations below and above 0.0.  In both of
+% these cases, the lowpass band is independently scaled.  A value of
+% 'indep1' sets the range of each subband independently, as in a call
+% to showIm(subband,'auto1').  Similarly, 'indep2' causes each subband
+% to be scaled independently as if by showIm(subband,'indep2').
+% The default value for RANGE is 'auto1' for 1D images, and 'auto2' for
+% 2D images.
+% 
+% GAP (optional, default=1) specifies the gap in pixels to leave
+% between subbands (2D images only).  
+% 
+% LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid
+% levels.  This should be set to the sum of the kernel taps of the
+% lowpass filter used to construct the pyramid (default assumes
+% L2-normalalized filters, using a value of 2 for 2D images, sqrt(2) for
+% 1D images).
+
+% Eero Simoncelli, 2/97.
+
+function [range] = showLpyr(pyr, pind, range, gap, scale);
+
+% Determine 1D or 2D pyramid:
+if ((pind(1,1) == 1) | (pind(1,2) ==1))
+  oned = 1;
+else
+  oned = 0;
+end
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('range') ~= 1)  
+  if (oned==1)
+    range = 'auto1';
+  else
+    range = 'auto2';
+  end
+end
+                
+if (exist('gap') ~= 1)
+  gap = 1;
+end
+
+if (exist('scale') ~= 1)
+  if (oned == 1)
+    scale = sqrt(2);
+  else
+    scale = 2;
+  end
+end
+
+%------------------------------------------------------------
+
+nind = size(pind,1);
+
+%% Auto range calculations:
+if strcmp(range,'auto1')
+  range = zeros(nind,1);
+  mn = 0.0; mx = 0.0;
+  for bnum = 1:(nind-1)
+    band = pyrBand(pyr,pind,bnum)/(scale^(bnum-1));
+    range(bnum) = scale^(bnum-1);
+    [bmn,bmx] = range2(band);
+    mn = min(mn, bmn);  mx = max(mx, bmx);
+  end    
+  if (oned == 1)
+    pad = (mx-mn)/12;                   % *** MAGIC NUMBER!!
+    mn = mn-pad;  mx = mx+pad;
+  end
+  range = range * [mn mx];              % outer product
+  band = pyrLow(pyr,pind);
+  [mn,mx] = range2(band);
+  if (oned == 1)
+    pad = (mx-mn)/12;                   % *** MAGIC NUMBER!!
+    mn = mn-pad;  mx = mx+pad;
+  end
+  range(nind,:) = [mn, mx];
+
+elseif strcmp(range,'indep1')
+  range = zeros(nind,2);
+  for bnum = 1:nind
+    band = pyrBand(pyr,pind,bnum);
+    [mn,mx] = range2(band);
+    if (oned == 1)
+      pad = (mx-mn)/12;                 % *** MAGIC NUMBER!!
+      mn = mn-pad;  mx = mx+pad;
+    end
+    range(bnum,:) =  [mn mx];
+  end
+
+elseif strcmp(range,'auto2')
+  range = zeros(nind,1);
+  sqsum = 0;  numpixels = 0;
+  for bnum = 1:(nind-1)
+    band = pyrBand(pyr,pind,bnum)/(scale^(bnum-1));
+    sqsum = sqsum + sum(sum(band.^2));
+    numpixels = numpixels + prod(size(band));
+    range(bnum) = scale^(bnum-1);
+  end    
+  stdev = sqrt(sqsum/(numpixels-1));
+  range = range * [ -3*stdev 3*stdev ]; % outer product
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+
+elseif strcmp(range,'indep2')
+  range = zeros(nind,2);
+  for bnum = 1:(nind-1)
+    band = pyrBand(pyr,pind,bnum);
+    stdev = sqrt(var2(band));
+    range(bnum,:) =  [ -3*stdev 3*stdev ];
+  end
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+  
+elseif isstr(range)
+  error(sprintf('Bad RANGE argument: %s',range))
+
+elseif ((size(range,1) == 1) & (size(range,2) == 2))
+  scales = scale.^[0:nind-1];
+  range = scales(:) * range;            % outer product
+  band = pyrLow(pyr,pind);
+  range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:));
+
+end
+
+%% Clear Figure
+clf;
+
+if (oned == 1)
+
+  %%%%%  1D signal:
+  for bnum=1:nind
+    band = pyrBand(pyr,pind,bnum);
+    subplot(nind,1,nind-bnum+1);
+    plot(band);
+    axis([1, prod(size(band)), range(bnum,:)]);
+  end
+
+else  
+
+  %%%%% 2D signal:
+  colormap(gray);
+  cmap = get(gcf,'Colormap');
+  nshades = size(cmap,1);
+
+  %  Find background color index:
+  clr = get(gcf,'Color');
+  bg = 1;
+  dist = norm(cmap(bg,:)-clr);
+  for n = 1:nshades
+    ndist = norm(cmap(n,:)-clr);
+    if (ndist < dist)
+      dist = ndist;
+      bg = n;
+    end
+  end  
+
+  %% Compute positions of subbands:
+  llpos = ones(nind,2);
+  dir = [-1 -1];
+  ctr = [pind(1,1)+1+gap 1];
+  sz = [0 0];
+  for bnum = 1:nind
+    prevsz = sz;
+    sz = pind(bnum,:);
+
+    % Determine center position of new band:
+    ctr = ctr + gap*dir/2 + dir.* floor((prevsz+(dir>0))/2);
+    dir = dir * [0 -1; 1 0];  % ccw rotation
+    ctr = ctr + gap*dir/2 + dir.* floor((sz+(dir<0))/2);
+    llpos(bnum,:) = ctr - floor(sz./2);
+  end
+   
+  %% Make position list positive, and allocate appropriate image:
+  llpos = llpos - ones(nind,1)*min(llpos) + 1;
+  urpos = llpos + pind - 1;
+  d_im = bg + zeros(max(urpos));
+
+  %% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 
+  for bnum=1:nind
+    mult = (nshades-1) / (range(bnum,2)-range(bnum,1));
+    d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ...
+        mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1));
+  end
+    
+  hh = image(d_im);
+  axis('off');
+  pixelAxes(size(d_im),'full');
+  set(hh,'UserData',range);
+
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showSpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showSpyr.m
new file mode 100755
index 0000000..da85715
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showSpyr.m
@@ -0,0 +1,188 @@
+% RANGE = showSpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR)
+% 
+% Display a steerable pyramid, specified by PYR and INDICES
+% (see buildSpyr), in the current figure.  The highpass band is not shown.
+% 
+% RANGE is a 2-vector specifying the values that map to black and
+% white, respectively.  These values are scaled by
+% LEVEL_SCALE_FACTOR^(lev-1) for bands at each level.  Passing a value
+% of 'auto1' sets RANGE to the min and max values of MATRIX.  'auto2'
+% sets RANGE to 3 standard deviations below and above 0.0.  In both of
+% these cases, the lowpass band is independently scaled.  A value of
+% 'indep1' sets the range of each subband independently, as in a call
+% to showIm(subband,'auto1').  Similarly, 'indep2' causes each subband
+% to be scaled independently as if by showIm(subband,'indep2').
+% The default value for RANGE is 'auto2'.
+% 
+% GAP (optional, default=1) specifies the gap in pixels to leave
+% between subbands.  
+% 
+% LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid
+% levels.  This should be set to the sum of the kernel taps of the
+% lowpass filter used to construct the pyramid (default is 2, which is 
+% correct for L2-normalized filters.
+
+% Eero Simoncelli, 2/97.
+
+function [range] = showSpyr(pyr, pind, range, gap, scale);
+
+nbands = spyrNumBands(pind);
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('range') ~= 1)  
+  range = 'auto2';
+end
+                
+if (exist('gap') ~= 1)
+  gap = 1;
+end
+
+if (exist('scale') ~= 1)
+  scale = 2;
+end
+
+%------------------------------------------------------------
+
+ht = spyrHt(pind);
+nind = size(pind,1);
+
+%% Auto range calculations:
+if strcmp(range,'auto1')
+  range = ones(nind,1);
+  band = spyrHigh(pyr,pind);
+  [mn,mx] = range2(band);
+  for lnum = 1:ht
+    for bnum = 1:nbands
+      band = spyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1));
+      range((lnum-1)*nbands+bnum+1) = scale^(lnum-1);
+      [bmn,bmx] = range2(band);
+      mn = min(mn, bmn);
+      mx = max(mx, bmx);
+    end    
+  end
+  range = range * [mn mx];              % outer product
+  band = pyrLow(pyr,pind);
+  [mn,mx] = range2(band);
+  range(nind,:) = [mn, mx];
+
+elseif strcmp(range,'indep1')
+  range = zeros(nind,2);
+  for bnum = 1:nind
+    band = pyrBand(pyr,pind,bnum);
+    [mn,mx] = range2(band);
+    range(bnum,:) =  [mn mx];
+  end
+
+elseif strcmp(range,'auto2')
+  range = ones(nind,1);
+  band = spyrHigh(pyr,pind);
+  sqsum = sum(sum(band.^2));  numpixels = prod(size(band));
+  for lnum = 1:ht
+    for bnum = 1:nbands
+      band = spyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1));
+      sqsum = sqsum + sum(sum(band.^2));
+      numpixels = numpixels + prod(size(band));
+      range((lnum-1)*nbands+bnum+1) = scale^(lnum-1);
+    end    
+  end
+  stdev = sqrt(sqsum/(numpixels-1));
+  range = range * [ -3*stdev 3*stdev ]; % outer product
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+
+elseif strcmp(range,'indep2')
+  range = zeros(nind,2);
+  for bnum = 1:(nind-1)
+    band = pyrBand(pyr,pind,bnum);
+    stdev = sqrt(var2(band));
+    range(bnum,:) =  [ -3*stdev 3*stdev ];
+  end
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+  
+elseif isstr(range)
+  error(sprintf('Bad RANGE argument: %s',range))
+  
+elseif ((size(range,1) == 1) & (size(range,2) == 2))
+  scales = scale.^[0:(ht-1)];
+  scales = ones(nbands,1) * scales;   %outer product
+  scales = [1; scales(:); scale^ht];  %tack on highpass and lowpass
+  range = scales * range;               % outer product
+  band = pyrLow(pyr,pind);
+  range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:));
+
+end
+
+% CLEAR FIGURE:
+clf;
+
+colormap(gray);
+cmap = get(gcf,'Colormap');
+nshades = size(cmap,1);
+
+%  Find background color index:
+clr = get(gcf,'Color');
+bg = 1;
+dist = norm(cmap(bg,:)-clr);
+for n = 1:nshades
+  ndist = norm(cmap(n,:)-clr);
+  if (ndist < dist)
+    dist = ndist;
+    bg = n;
+  end
+end  
+
+%% Compute positions of subbands:
+llpos = ones(nind,2);
+
+if (nbands == 2)
+  ncols = 1;  nrows = 2;
+else
+  ncols = ceil((nbands+1)/2);   nrows = ceil(nbands/2);
+end
+relpos = [ (1-nrows):0, zeros(1,(ncols-1)); ...
+           zeros(1,nrows), -1:-1:(1-ncols) ]';
+if (nbands > 1)
+  mvpos = [-1 -1];
+else
+  mvpos = [0 -1];
+end
+basepos = [0 0];
+
+for lnum = 1:ht
+  ind1 = (lnum-1)*nbands + 2;
+  sz = pind(ind1,:)+gap;
+  basepos = basepos + mvpos .* sz;
+  if (nbands < 5)                       % to align edges...
+    sz = sz + gap*(ht-lnum+1);
+  end
+  llpos(ind1:ind1+nbands-1,:) = relpos * diag(sz) + ones(nbands,1)*basepos;
+end
+
+% lowpass band
+sz = pind(nind-1,:)+gap;
+basepos = basepos + mvpos .* sz;
+llpos(nind,:) = basepos;
+
+%% Make position list positive, and allocate appropriate image:
+llpos = llpos - ones(nind,1)*min(llpos) + 1;
+llpos(1,:) = [1 1];
+urpos = llpos + pind - 1;
+d_im = bg + zeros(max(urpos));
+
+%% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 
+for bnum=2:nind
+  mult = (nshades-1) / (range(bnum,2)-range(bnum,1));
+  d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ...
+      mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1));
+end
+  
+hh = image(d_im);
+axis('off');
+pixelAxes(size(d_im),'full');
+set(hh,'UserData',range);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showWpyr.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showWpyr.m
new file mode 100755
index 0000000..510e395
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/showWpyr.m
@@ -0,0 +1,204 @@
+% RANGE = showWpyr (PYR, INDICES, RANGE, GAP, LEVEL_SCALE_FACTOR)
+% 
+% Display a separable QMF/wavelet pyramid, specified by PYR and INDICES
+% (see buildWpyr), in the current figure.
+% 
+% RANGE is a 2-vector specifying the values that map to black and
+% white, respectively.  These values are scaled by
+% LEVEL_SCALE_FACTOR^(lev-1) for bands at each level.  Passing a value
+% of 'auto1' sets RANGE to the min and max values of MATRIX.  'auto2'
+% sets RANGE to 3 standard deviations below and above 0.0.  In both of
+% these cases, the lowpass band is independently scaled.  A value of
+% 'indep1' sets the range of each subband independently, as in a call
+% to showIm(subband,'auto1').  Similarly, 'indep2' causes each subband
+% to be scaled independently as if by showIm(subband,'indep2').
+% The default value for RANGE is 'auto1' for 1D images, and 'auto2' for
+% 2D images.
+% 
+% GAP (optional, default=1) specifies the gap in pixels to leave
+% between subbands (2D images only).  
+% 
+% LEVEL_SCALE_FACTOR indicates the relative scaling between pyramid
+% levels.  This should be set to the sum of the kernel taps of the
+% lowpass filter used to construct the pyramid (default assumes
+% L2-normalized filters, using a value of 2 for 2D images, sqrt(2) for
+% 1D images).
+
+% Eero Simoncelli, 2/97.
+
+function [range] = showWpyr(pyr, pind, range, gap, scale);
+
+% Determine 1D or 2D pyramid:
+if ((pind(1,1) == 1) | (pind(1,2) ==1))
+  nbands = 1;
+else
+  nbands = 3;
+end
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('range') ~= 1)  
+  if (nbands==1)
+    range = 'auto1';
+  else
+    range = 'auto2';
+  end
+end
+                
+if (exist('gap') ~= 1)
+  gap = 1;
+end
+
+if (exist('scale') ~= 1)
+  if (nbands == 1)
+    scale = sqrt(2);
+  else
+    scale = 2;
+  end
+end
+
+%------------------------------------------------------------
+
+ht = wpyrHt(pind);
+nind = size(pind,1);
+
+%% Auto range calculations:
+if strcmp(range,'auto1')
+  range = zeros(nind,1);
+  mn = 0.0; mx = 0.0;
+  for lnum = 1:ht
+    for bnum = 1:nbands
+      band = wpyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1));
+      range((lnum-1)*nbands+bnum) = scale^(lnum-1);
+      [bmn,bmx] = range2(band);
+      mn = min(mn, bmn);  mx = max(mx, bmx);
+    end    
+  end
+  if (nbands == 1)
+    pad = (mx-mn)/12;                   % *** MAGIC NUMBER!!
+    mn = mn-pad;  mx = mx+pad;
+  end
+  range = range * [mn mx];              % outer product
+  band = pyrLow(pyr,pind);
+  [mn,mx] = range2(band);
+  if (nbands == 1)
+    pad = (mx-mn)/12;                   % *** MAGIC NUMBER!!
+    mn = mn-pad;  mx = mx+pad;
+  end
+  range(nind,:) = [mn, mx];
+
+elseif strcmp(range,'indep1')
+  range = zeros(nind,2);
+  for bnum = 1:nind
+    band = pyrBand(pyr,pind,bnum);
+    [mn,mx] = range2(band);
+    if (nbands == 1)
+      pad = (mx-mn)/12;                 % *** MAGIC NUMBER!!
+      mn = mn-pad;  mx = mx+pad;
+    end
+    range(bnum,:) =  [mn mx];
+  end
+
+elseif strcmp(range,'auto2')
+  range = zeros(nind,1);
+  sqsum = 0;  numpixels = 0;
+  for lnum = 1:ht
+    for bnum = 1:nbands
+      band = wpyrBand(pyr,pind,lnum,bnum)/(scale^(lnum-1));
+      sqsum = sqsum + sum(sum(band.^2));
+      numpixels = numpixels + prod(size(band));
+      range((lnum-1)*nbands+bnum) = scale^(lnum-1);
+    end    
+  end
+  stdev = sqrt(sqsum/(numpixels-1));
+  range = range * [ -3*stdev 3*stdev ]; % outer product
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+
+elseif strcmp(range,'indep2')
+  range = zeros(nind,2);
+  for bnum = 1:(nind-1)
+    band = pyrBand(pyr,pind,bnum);
+    stdev = sqrt(var2(band));
+    range(bnum,:) =  [ -3*stdev 3*stdev ];
+  end
+  band = pyrLow(pyr,pind);
+  av = mean2(band);   stdev = sqrt(var2(band));
+  range(nind,:) = [av-2*stdev,av+2*stdev];
+  
+elseif isstr(range)
+  error(sprintf('Bad RANGE argument: %s',range))
+  
+elseif ((size(range,1) == 1) & (size(range,2) == 2))
+  scales = scale.^[0:ht];
+  if (nbands ~= 1)
+    scales = [scales; scales; scales];
+  end
+  range = scales(:) * range;            % outer product
+  band = pyrLow(pyr,pind);
+  range(nind,:) = range(nind,:) + mean2(band) - mean(range(nind,:));
+
+end
+
+% CLEAR FIGURE:
+clf;
+
+if (nbands == 1)
+
+  %%%%%  1D signal:
+  for bnum=1:nind
+    band = pyrBand(pyr,pind,bnum);
+    subplot(nind,1,nind-bnum+1);
+    plot(band);
+    axis([1, prod(size(band)), range(bnum,:)]);
+  end
+
+else  
+
+  %%%%% 2D signal:
+  colormap(gray);
+  cmap = get(gcf,'Colormap');
+  nshades = size(cmap,1);
+
+  %  Find background color index:
+  clr = get(gcf,'Color');
+  bg = 1;
+  dist = norm(cmap(bg,:)-clr);
+  for n = 1:nshades
+    ndist = norm(cmap(n,:)-clr);
+    if (ndist < dist)
+      dist = ndist;
+      bg = n;
+    end
+  end  
+
+  %% Compute positions of subbands:
+  llpos = ones(nind,2);
+  for lnum = 1:ht
+    ind1 = nbands*(lnum-1) + 1;
+    xpos = pind(ind1,2) + 1 + gap*(ht-lnum+1);
+    ypos = pind(ind1+1,1) + 1 + gap*(ht-lnum+1);
+    llpos(ind1:ind1+2,:) = [ypos 1; 1 xpos; ypos xpos];
+  end
+  llpos(nind,:) = [1 1];  %lowpass
+
+  %% Make position list positive, and allocate appropriate image:
+  llpos = llpos - ones(nind,1)*min(llpos) + 1;
+  urpos = llpos + pind - 1;
+  d_im = bg + zeros(max(urpos));
+
+  %% Paste bands into image, (im-r1)*(nshades-1)/(r2-r1) + 1.5 
+  for bnum=1:nind
+    mult = (nshades-1) / (range(bnum,2)-range(bnum,1));
+    d_im(llpos(bnum,1):urpos(bnum,1), llpos(bnum,2):urpos(bnum,2)) = ...
+        mult*pyrBand(pyr,pind,bnum) + (1.5-mult*range(bnum,1));
+  end
+    
+  hh = image(d_im);
+  axis('off');
+  pixelAxes(size(d_im),'full');
+  set(hh,'UserData',range);
+
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/skew2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/skew2.m
new file mode 100755
index 0000000..623d6ca
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/skew2.m
@@ -0,0 +1,21 @@
+% S = SKEW2(MTX,MEAN,VAR)
+%
+% Sample skew (third moment divided by variance^3/2) of a matrix.
+%  MEAN (optional) and VAR (optional) make the computation faster.
+
+function res = skew2(mtx, mn, v)
+
+if (exist('mn') ~= 1)
+  mn =  mean2(mtx);
+end
+
+if (exist('v') ~= 1)
+  v =  var2(mtx,mn);
+end
+
+if (isreal(mtx))
+  res = mean(mean((mtx-mn).^3)) / (v^(3/2));
+else
+  res = mean(mean(real(mtx-mn).^3)) / (real(v)^(3/2)) + ...
+      i * mean(mean(imag(mtx-mn).^3)) / (imag(v)^(3/2));
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp0Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp0Filters.m
new file mode 100755
index 0000000..6b25e36
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp0Filters.m
@@ -0,0 +1,72 @@
+% Steerable pyramid filters.  Transform described  in:
+%
+% @INPROCEEDINGS{Simoncelli95b,
+%       TITLE = "The Steerable Pyramid: A Flexible Architecture for
+%                Multi-Scale Derivative Computation",
+%       AUTHOR = "E P Simoncelli and W T Freeman",
+%       BOOKTITLE = "Second Int'l Conf on Image Processing",
+%       ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 }
+%
+% Filter kernel design described in:
+%
+%@INPROCEEDINGS{Karasaridis96,
+%       TITLE = "A Filter Design Technique for 
+%               Steerable Pyramid Image Transforms",
+%       AUTHOR = "A Karasaridis and E P Simoncelli",
+%       BOOKTITLE = "ICASSP",   ADDRESS = "Atlanta, GA",
+%       MONTH = "May",  YEAR = 1996 }
+
+% Eero Simoncelli, 6/96.
+
+function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp0Filters();
+
+harmonics = [ 0 ];
+
+lo0filt = [ ...
+-4.514000e-04 -1.137100e-04 -3.725800e-04 -3.743860e-03 -3.725800e-04 -1.137100e-04 -4.514000e-04
+-1.137100e-04 -6.119520e-03 -1.344160e-02 -7.563200e-03 -1.344160e-02 -6.119520e-03 -1.137100e-04
+-3.725800e-04 -1.344160e-02 6.441488e-02 1.524935e-01 6.441488e-02 -1.344160e-02 -3.725800e-04 
+-3.743860e-03 -7.563200e-03 1.524935e-01 3.153017e-01 1.524935e-01 -7.563200e-03 -3.743860e-03 
+-3.725800e-04 -1.344160e-02 6.441488e-02 1.524935e-01 6.441488e-02 -1.344160e-02 -3.725800e-04 
+-1.137100e-04 -6.119520e-03 -1.344160e-02 -7.563200e-03 -1.344160e-02 -6.119520e-03 -1.137100e-04 
+-4.514000e-04 -1.137100e-04 -3.725800e-04 -3.743860e-03 -3.725800e-04 -1.137100e-04 -4.514000e-04];
+
+lofilt = [ ...
+-2.257000e-04 -8.064400e-04 -5.686000e-05 8.741400e-04 -1.862800e-04 -1.031640e-03 -1.871920e-03 -1.031640e-03 -1.862800e-04 8.741400e-04 -5.686000e-05 -8.064400e-04 -2.257000e-04 
+-8.064400e-04 1.417620e-03 -1.903800e-04 -2.449060e-03 -4.596420e-03 -7.006740e-03 -6.948900e-03 -7.006740e-03 -4.596420e-03 -2.449060e-03 -1.903800e-04 1.417620e-03 -8.064400e-04 
+-5.686000e-05 -1.903800e-04 -3.059760e-03 -6.401000e-03 -6.720800e-03 -5.236180e-03 -3.781600e-03 -5.236180e-03 -6.720800e-03 -6.401000e-03 -3.059760e-03 -1.903800e-04 -5.686000e-05 
+8.741400e-04 -2.449060e-03 -6.401000e-03 -5.260020e-03 3.938620e-03 1.722078e-02 2.449600e-02 1.722078e-02 3.938620e-03 -5.260020e-03 -6.401000e-03 -2.449060e-03 8.741400e-04 
+-1.862800e-04 -4.596420e-03 -6.720800e-03 3.938620e-03 3.220744e-02 6.306262e-02 7.624674e-02 6.306262e-02 3.220744e-02 3.938620e-03 -6.720800e-03 -4.596420e-03 -1.862800e-04 
+-1.031640e-03 -7.006740e-03 -5.236180e-03 1.722078e-02 6.306262e-02 1.116388e-01 1.348999e-01 1.116388e-01 6.306262e-02 1.722078e-02 -5.236180e-03 -7.006740e-03 -1.031640e-03 
+-1.871920e-03 -6.948900e-03 -3.781600e-03 2.449600e-02 7.624674e-02 1.348999e-01 1.576508e-01 1.348999e-01 7.624674e-02 2.449600e-02 -3.781600e-03 -6.948900e-03 -1.871920e-03 
+-1.031640e-03 -7.006740e-03 -5.236180e-03 1.722078e-02 6.306262e-02 1.116388e-01 1.348999e-01 1.116388e-01 6.306262e-02 1.722078e-02 -5.236180e-03 -7.006740e-03 -1.031640e-03 
+-1.862800e-04 -4.596420e-03 -6.720800e-03 3.938620e-03 3.220744e-02 6.306262e-02 7.624674e-02 6.306262e-02 3.220744e-02 3.938620e-03 -6.720800e-03 -4.596420e-03 -1.862800e-04
+8.741400e-04 -2.449060e-03 -6.401000e-03 -5.260020e-03 3.938620e-03 1.722078e-02 2.449600e-02 1.722078e-02 3.938620e-03 -5.260020e-03 -6.401000e-03 -2.449060e-03 8.741400e-04 
+-5.686000e-05 -1.903800e-04 -3.059760e-03 -6.401000e-03 -6.720800e-03 -5.236180e-03 -3.781600e-03 -5.236180e-03 -6.720800e-03 -6.401000e-03 -3.059760e-03 -1.903800e-04 -5.686000e-05 
+-8.064400e-04 1.417620e-03 -1.903800e-04 -2.449060e-03 -4.596420e-03 -7.006740e-03 -6.948900e-03 -7.006740e-03 -4.596420e-03 -2.449060e-03 -1.903800e-04 1.417620e-03 -8.064400e-04 
+-2.257000e-04 -8.064400e-04 -5.686000e-05 8.741400e-04 -1.862800e-04 -1.031640e-03 -1.871920e-03 -1.031640e-03 -1.862800e-04 8.741400e-04 -5.686000e-05 -8.064400e-04 -2.257000e-04]; 
+
+mtx = [ 1.000000 ];
+
+hi0filt = [...
+5.997200e-04 -6.068000e-05 -3.324900e-04 -3.325600e-04 -2.406600e-04 -3.325600e-04 -3.324900e-04 -6.068000e-05 5.997200e-04
+-6.068000e-05 1.263100e-04 4.927100e-04 1.459700e-04 -3.732100e-04 1.459700e-04 4.927100e-04 1.263100e-04 -6.068000e-05 
+-3.324900e-04 4.927100e-04 -1.616650e-03 -1.437358e-02 -2.420138e-02 -1.437358e-02 -1.616650e-03 4.927100e-04 -3.324900e-04 
+-3.325600e-04 1.459700e-04 -1.437358e-02 -6.300923e-02 -9.623594e-02 -6.300923e-02 -1.437358e-02 1.459700e-04 -3.325600e-04 
+-2.406600e-04 -3.732100e-04 -2.420138e-02 -9.623594e-02 8.554893e-01 -9.623594e-02 -2.420138e-02 -3.732100e-04 -2.406600e-04 
+-3.325600e-04 1.459700e-04 -1.437358e-02 -6.300923e-02 -9.623594e-02 -6.300923e-02 -1.437358e-02 1.459700e-04 -3.325600e-04 
+-3.324900e-04 4.927100e-04 -1.616650e-03 -1.437358e-02 -2.420138e-02 -1.437358e-02 -1.616650e-03 4.927100e-04 -3.324900e-04 
+-6.068000e-05 1.263100e-04 4.927100e-04 1.459700e-04 -3.732100e-04 1.459700e-04 4.927100e-04 1.263100e-04 -6.068000e-05 
+5.997200e-04 -6.068000e-05 -3.324900e-04 -3.325600e-04 -2.406600e-04 -3.325600e-04 -3.324900e-04 -6.068000e-05 5.997200e-04 ];
+
+bfilts = [ ...
+-9.066000e-05 -1.738640e-03 -4.942500e-03 -7.889390e-03 -1.009473e-02 -7.889390e-03 -4.942500e-03 -1.738640e-03 -9.066000e-05 ...
+-1.738640e-03 -4.625150e-03 -7.272540e-03 -7.623410e-03 -9.091950e-03 -7.623410e-03 -7.272540e-03 -4.625150e-03 -1.738640e-03 ...
+-4.942500e-03 -7.272540e-03 -2.129540e-02 -2.435662e-02 -3.487008e-02 -2.435662e-02 -2.129540e-02 -7.272540e-03 -4.942500e-03  ...
+-7.889390e-03 -7.623410e-03 -2.435662e-02 -1.730466e-02 -3.158605e-02 -1.730466e-02 -2.435662e-02 -7.623410e-03 -7.889390e-03  ...
+-1.009473e-02 -9.091950e-03 -3.487008e-02 -3.158605e-02 9.464195e-01 -3.158605e-02 -3.487008e-02 -9.091950e-03 -1.009473e-02  ...
+-7.889390e-03 -7.623410e-03 -2.435662e-02 -1.730466e-02 -3.158605e-02 -1.730466e-02 -2.435662e-02 -7.623410e-03 -7.889390e-03 ...
+-4.942500e-03 -7.272540e-03 -2.129540e-02 -2.435662e-02 -3.487008e-02 -2.435662e-02 -2.129540e-02 -7.272540e-03 -4.942500e-03  ...
+-1.738640e-03 -4.625150e-03 -7.272540e-03 -7.623410e-03 -9.091950e-03 -7.623410e-03 -7.272540e-03 -4.625150e-03 -1.738640e-03  ...
+-9.066000e-05 -1.738640e-03 -4.942500e-03 -7.889390e-03 -1.009473e-02 -7.889390e-03 -4.942500e-03 -1.738640e-03 -9.066000e-05 ]';
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp1Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp1Filters.m
new file mode 100755
index 0000000..215e651
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp1Filters.m
@@ -0,0 +1,91 @@
+% Steerable pyramid filters.  Transform described  in:
+%
+% @INPROCEEDINGS{Simoncelli95b,
+%       TITLE = "The Steerable Pyramid: A Flexible Architecture for
+%                Multi-Scale Derivative Computation",
+%       AUTHOR = "E P Simoncelli and W T Freeman",
+%       BOOKTITLE = "Second Int'l Conf on Image Processing",
+%       ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 }
+%
+% Filter kernel design described in:
+%
+%@INPROCEEDINGS{Karasaridis96,
+%       TITLE = "A Filter Design Technique for 
+%               Steerable Pyramid Image Transforms",
+%       AUTHOR = "A Karasaridis and E P Simoncelli",
+%       BOOKTITLE = "ICASSP",   ADDRESS = "Atlanta, GA",
+%       MONTH = "May",  YEAR = 1996 }
+
+% Eero Simoncelli, 6/96.
+
+function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp1Filters();
+
+harmonics = [ 1 ];
+
+%% filters only contain first harmonic.
+mtx = eye(2);
+
+lo0filt = [ ...
+-8.701000e-05 -1.354280e-03 -1.601260e-03 -5.033700e-04 2.524010e-03 -5.033700e-04 -1.601260e-03 -1.354280e-03 -8.701000e-05
+-1.354280e-03 2.921580e-03 7.522720e-03 8.224420e-03 1.107620e-03 8.224420e-03 7.522720e-03 2.921580e-03 -1.354280e-03 
+-1.601260e-03 7.522720e-03 -7.061290e-03 -3.769487e-02 -3.297137e-02 -3.769487e-02 -7.061290e-03 7.522720e-03 -1.601260e-03  
+-5.033700e-04 8.224420e-03 -3.769487e-02 4.381320e-02 1.811603e-01 4.381320e-02 -3.769487e-02 8.224420e-03 -5.033700e-04 
+2.524010e-03 1.107620e-03 -3.297137e-02 1.811603e-01 4.376250e-01 1.811603e-01 -3.297137e-02 1.107620e-03 2.524010e-03  
+-5.033700e-04 8.224420e-03 -3.769487e-02 4.381320e-02 1.811603e-01 4.381320e-02 -3.769487e-02 8.224420e-03 -5.033700e-04  
+-1.601260e-03 7.522720e-03 -7.061290e-03 -3.769487e-02 -3.297137e-02 -3.769487e-02 -7.061290e-03 7.522720e-03 -1.601260e-03  
+-1.354280e-03 2.921580e-03 7.522720e-03 8.224420e-03 1.107620e-03 8.224420e-03 7.522720e-03 2.921580e-03 -1.354280e-03  
+-8.701000e-05 -1.354280e-03 -1.601260e-03 -5.033700e-04 2.524010e-03 -5.033700e-04 -1.601260e-03 -1.354280e-03 -8.701000e-05 
+];
+
+lofilt = [ ...
+-4.350000e-05 1.207800e-04 -6.771400e-04 -1.243400e-04 -8.006400e-04 -1.597040e-03 -2.516800e-04 -4.202000e-04 1.262000e-03 -4.202000e-04 -2.516800e-04 -1.597040e-03 -8.006400e-04 -1.243400e-04 -6.771400e-04 1.207800e-04 -4.350000e-05  ; ...
+1.207800e-04 4.460600e-04 -5.814600e-04 5.621600e-04 -1.368800e-04 2.325540e-03 2.889860e-03 4.287280e-03 5.589400e-03 4.287280e-03 2.889860e-03 2.325540e-03 -1.368800e-04 5.621600e-04 -5.814600e-04 4.460600e-04 1.207800e-04  ; ...
+-6.771400e-04 -5.814600e-04 1.460780e-03 2.160540e-03 3.761360e-03 3.080980e-03 4.112200e-03 2.221220e-03 5.538200e-04 2.221220e-03 4.112200e-03 3.080980e-03 3.761360e-03 2.160540e-03 1.460780e-03 -5.814600e-04 -6.771400e-04  ; ...
+-1.243400e-04 5.621600e-04 2.160540e-03 3.175780e-03 3.184680e-03 -1.777480e-03 -7.431700e-03 -9.056920e-03 -9.637220e-03 -9.056920e-03 -7.431700e-03 -1.777480e-03 3.184680e-03 3.175780e-03 2.160540e-03 5.621600e-04 -1.243400e-04  ; ...
+-8.006400e-04 -1.368800e-04 3.761360e-03 3.184680e-03 -3.530640e-03 -1.260420e-02 -1.884744e-02 -1.750818e-02 -1.648568e-02 -1.750818e-02 -1.884744e-02 -1.260420e-02 -3.530640e-03 3.184680e-03 3.761360e-03 -1.368800e-04 -8.006400e-04  ; ...
+-1.597040e-03 2.325540e-03 3.080980e-03 -1.777480e-03 -1.260420e-02 -2.022938e-02 -1.109170e-02 3.955660e-03 1.438512e-02 3.955660e-03 -1.109170e-02 -2.022938e-02 -1.260420e-02 -1.777480e-03 3.080980e-03 2.325540e-03 -1.597040e-03  ; ...
+-2.516800e-04 2.889860e-03 4.112200e-03 -7.431700e-03 -1.884744e-02 -1.109170e-02 2.190660e-02 6.806584e-02 9.058014e-02 6.806584e-02 2.190660e-02 -1.109170e-02 -1.884744e-02 -7.431700e-03 4.112200e-03 2.889860e-03 -2.516800e-04  ; ...
+-4.202000e-04 4.287280e-03 2.221220e-03 -9.056920e-03 -1.750818e-02 3.955660e-03 6.806584e-02 1.445500e-01 1.773651e-01 1.445500e-01 6.806584e-02 3.955660e-03 -1.750818e-02 -9.056920e-03 2.221220e-03 4.287280e-03 -4.202000e-04  ; ...
+1.262000e-03 5.589400e-03 5.538200e-04 -9.637220e-03 -1.648568e-02 1.438512e-02 9.058014e-02 1.773651e-01 2.120374e-01 1.773651e-01 9.058014e-02 1.438512e-02 -1.648568e-02 -9.637220e-03 5.538200e-04 5.589400e-03 1.262000e-03  ; ...
+-4.202000e-04 4.287280e-03 2.221220e-03 -9.056920e-03 -1.750818e-02 3.955660e-03 6.806584e-02 1.445500e-01 1.773651e-01 1.445500e-01 6.806584e-02 3.955660e-03 -1.750818e-02 -9.056920e-03 2.221220e-03 4.287280e-03 -4.202000e-04  ; ...
+-2.516800e-04 2.889860e-03 4.112200e-03 -7.431700e-03 -1.884744e-02 -1.109170e-02 2.190660e-02 6.806584e-02 9.058014e-02 6.806584e-02 2.190660e-02 -1.109170e-02 -1.884744e-02 -7.431700e-03 4.112200e-03 2.889860e-03 -2.516800e-04  ; ...
+-1.597040e-03 2.325540e-03 3.080980e-03 -1.777480e-03 -1.260420e-02 -2.022938e-02 -1.109170e-02 3.955660e-03 1.438512e-02 3.955660e-03 -1.109170e-02 -2.022938e-02 -1.260420e-02 -1.777480e-03 3.080980e-03 2.325540e-03 -1.597040e-03  ; ...
+-8.006400e-04 -1.368800e-04 3.761360e-03 3.184680e-03 -3.530640e-03 -1.260420e-02 -1.884744e-02 -1.750818e-02 -1.648568e-02 -1.750818e-02 -1.884744e-02 -1.260420e-02 -3.530640e-03 3.184680e-03 3.761360e-03 -1.368800e-04 -8.006400e-04  ; ...
+-1.243400e-04 5.621600e-04 2.160540e-03 3.175780e-03 3.184680e-03 -1.777480e-03 -7.431700e-03 -9.056920e-03 -9.637220e-03 -9.056920e-03 -7.431700e-03 -1.777480e-03 3.184680e-03 3.175780e-03 2.160540e-03 5.621600e-04 -1.243400e-04  ; ...
+-6.771400e-04 -5.814600e-04 1.460780e-03 2.160540e-03 3.761360e-03 3.080980e-03 4.112200e-03 2.221220e-03 5.538200e-04 2.221220e-03 4.112200e-03 3.080980e-03 3.761360e-03 2.160540e-03 1.460780e-03 -5.814600e-04 -6.771400e-04  ; ...
+1.207800e-04 4.460600e-04 -5.814600e-04 5.621600e-04 -1.368800e-04 2.325540e-03 2.889860e-03 4.287280e-03 5.589400e-03 4.287280e-03 2.889860e-03 2.325540e-03 -1.368800e-04 5.621600e-04 -5.814600e-04 4.460600e-04 1.207800e-04  ; ...
+-4.350000e-05 1.207800e-04 -6.771400e-04 -1.243400e-04 -8.006400e-04 -1.597040e-03 -2.516800e-04 -4.202000e-04 1.262000e-03 -4.202000e-04 -2.516800e-04 -1.597040e-03 -8.006400e-04 -1.243400e-04 -6.771400e-04 1.207800e-04 -4.350000e-05 ];
+
+hi0filt = [...
+-9.570000e-04 -2.424100e-04 -1.424720e-03 -8.742600e-04 -1.166810e-03 -8.742600e-04 -1.424720e-03 -2.424100e-04 -9.570000e-04 ; ...
+-2.424100e-04 -4.317530e-03 8.998600e-04 9.156420e-03 1.098012e-02 9.156420e-03 8.998600e-04 -4.317530e-03 -2.424100e-04  ; ...
+-1.424720e-03 8.998600e-04 1.706347e-02 1.094866e-02 -5.897780e-03 1.094866e-02 1.706347e-02 8.998600e-04 -1.424720e-03  ; ...
+-8.742600e-04 9.156420e-03 1.094866e-02 -7.841370e-02 -1.562827e-01 -7.841370e-02 1.094866e-02 9.156420e-03 -8.742600e-04  ; ...
+-1.166810e-03 1.098012e-02 -5.897780e-03 -1.562827e-01 7.282593e-01 -1.562827e-01 -5.897780e-03 1.098012e-02 -1.166810e-03  ; ...
+-8.742600e-04 9.156420e-03 1.094866e-02 -7.841370e-02 -1.562827e-01 -7.841370e-02 1.094866e-02 9.156420e-03 -8.742600e-04  ; ...
+-1.424720e-03 8.998600e-04 1.706347e-02 1.094866e-02 -5.897780e-03 1.094866e-02 1.706347e-02 8.998600e-04 -1.424720e-03  ; ...
+-2.424100e-04 -4.317530e-03 8.998600e-04 9.156420e-03 1.098012e-02 9.156420e-03 8.998600e-04 -4.317530e-03 -2.424100e-04  ; ...
+-9.570000e-04 -2.424100e-04 -1.424720e-03 -8.742600e-04 -1.166810e-03 -8.742600e-04 -1.424720e-03 -2.424100e-04 -9.570000e-04 ];
+
+bfilts = -[ ...
+6.125880e-03 -8.052600e-03 -2.103714e-02 -1.536890e-02 -1.851466e-02 -1.536890e-02 -2.103714e-02 -8.052600e-03 6.125880e-03  ...
+-1.287416e-02 -9.611520e-03 1.023569e-02 6.009450e-03 1.872620e-03 6.009450e-03 1.023569e-02 -9.611520e-03 -1.287416e-02  ...
+-5.641530e-03 4.168400e-03 -2.382180e-02 -5.375324e-02 -2.076086e-02 -5.375324e-02 -2.382180e-02 4.168400e-03 -5.641530e-03  ...
+-8.957260e-03 -1.751170e-03 -1.836909e-02 1.265655e-01 2.996168e-01 1.265655e-01 -1.836909e-02 -1.751170e-03 -8.957260e-03  ...
+0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00  ...
+8.957260e-03 1.751170e-03 1.836909e-02 -1.265655e-01 -2.996168e-01 -1.265655e-01 1.836909e-02 1.751170e-03 8.957260e-03  ...
+5.641530e-03 -4.168400e-03 2.382180e-02 5.375324e-02 2.076086e-02 5.375324e-02 2.382180e-02 -4.168400e-03 5.641530e-03  ...
+1.287416e-02 9.611520e-03 -1.023569e-02 -6.009450e-03 -1.872620e-03 -6.009450e-03 -1.023569e-02 9.611520e-03 1.287416e-02  ...
+-6.125880e-03 8.052600e-03 2.103714e-02 1.536890e-02 1.851466e-02 1.536890e-02 2.103714e-02 8.052600e-03 -6.125880e-03; ...
+...
+-6.125880e-03 1.287416e-02 5.641530e-03 8.957260e-03 0.000000e+00 -8.957260e-03 -5.641530e-03 -1.287416e-02 6.125880e-03  ...
+8.052600e-03 9.611520e-03 -4.168400e-03 1.751170e-03 0.000000e+00 -1.751170e-03 4.168400e-03 -9.611520e-03 -8.052600e-03  ...
+2.103714e-02 -1.023569e-02 2.382180e-02 1.836909e-02 0.000000e+00 -1.836909e-02 -2.382180e-02 1.023569e-02 -2.103714e-02  ...
+1.536890e-02 -6.009450e-03 5.375324e-02 -1.265655e-01 0.000000e+00 1.265655e-01 -5.375324e-02 6.009450e-03 -1.536890e-02  ...
+1.851466e-02 -1.872620e-03 2.076086e-02 -2.996168e-01 0.000000e+00 2.996168e-01 -2.076086e-02 1.872620e-03 -1.851466e-02  ...
+1.536890e-02 -6.009450e-03 5.375324e-02 -1.265655e-01 0.000000e+00 1.265655e-01 -5.375324e-02 6.009450e-03 -1.536890e-02  ...
+2.103714e-02 -1.023569e-02 2.382180e-02 1.836909e-02 0.000000e+00 -1.836909e-02 -2.382180e-02 1.023569e-02 -2.103714e-02  ...
+8.052600e-03 9.611520e-03 -4.168400e-03 1.751170e-03 0.000000e+00 -1.751170e-03 4.168400e-03 -9.611520e-03 -8.052600e-03  ...
+-6.125880e-03 1.287416e-02 5.641530e-03 8.957260e-03 0.000000e+00 -8.957260e-03 -5.641530e-03 -1.287416e-02 6.125880e-03 ...
+]';
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp3Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp3Filters.m
new file mode 100755
index 0000000..c9cfaaf
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp3Filters.m
@@ -0,0 +1,121 @@
+% Steerable pyramid filters.  Transform described  in:
+%
+% @INPROCEEDINGS{Simoncelli95b,
+%       TITLE = "The Steerable Pyramid: A Flexible Architecture for
+%                Multi-Scale Derivative Computation",
+%       AUTHOR = "E P Simoncelli and W T Freeman",
+%       BOOKTITLE = "Second Int'l Conf on Image Processing",
+%       ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 }
+%
+% Filter kernel design described in:
+%
+%@INPROCEEDINGS{Karasaridis96,
+%       TITLE = "A Filter Design Technique for 
+%               Steerable Pyramid Image Transforms",
+%       AUTHOR = "A Karasaridis and E P Simoncelli",
+%       BOOKTITLE = "ICASSP",   ADDRESS = "Atlanta, GA",
+%       MONTH = "May",  YEAR = 1996 }
+
+% Eero Simoncelli, 6/96.
+
+function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp3Filters();
+
+harmonics = [1 3];
+
+mtx = [ ...
+    0.5000    0.3536         0   -0.3536
+   -0.0000    0.3536    0.5000    0.3536
+    0.5000   -0.3536         0    0.3536
+   -0.0000    0.3536   -0.5000    0.3536];
+
+hi0filt = [ 
+-4.0483998600E-4  -6.2596000498E-4  -3.7829999201E-5  8.8387000142E-4  1.5450799838E-3  1.9235999789E-3  2.0687500946E-3  2.0898699295E-3  2.0687500946E-3  1.9235999789E-3  1.5450799838E-3  8.8387000142E-4  -3.7829999201E-5  -6.2596000498E-4  -4.0483998600E-4
+-6.2596000498E-4  -3.2734998967E-4  7.7435001731E-4  1.5874400269E-3  2.1750701126E-3  2.5626500137E-3  2.2892199922E-3  1.9755100366E-3  2.2892199922E-3  2.5626500137E-3  2.1750701126E-3  1.5874400269E-3  7.7435001731E-4  -3.2734998967E-4  -6.2596000498E-4
+-3.7829999201E-5  7.7435001731E-4  1.1793200392E-3  1.4050999889E-3  2.2253401112E-3  2.1145299543E-3  3.3578000148E-4  -8.3368999185E-4  3.3578000148E-4  2.1145299543E-3  2.2253401112E-3  1.4050999889E-3  1.1793200392E-3  7.7435001731E-4  -3.7829999201E-5
+8.8387000142E-4  1.5874400269E-3  1.4050999889E-3  1.2960999738E-3  -4.9274001503E-4  -3.1295299996E-3  -4.5751798898E-3  -5.1014497876E-3  -4.5751798898E-3  -3.1295299996E-3  -4.9274001503E-4  1.2960999738E-3  1.4050999889E-3  1.5874400269E-3  8.8387000142E-4
+1.5450799838E-3  2.1750701126E-3  2.2253401112E-3  -4.9274001503E-4  -6.3222697936E-3  -2.7556000277E-3  5.3632198833E-3  7.3032598011E-3  5.3632198833E-3  -2.7556000277E-3  -6.3222697936E-3  -4.9274001503E-4  2.2253401112E-3  2.1750701126E-3  1.5450799838E-3
+1.9235999789E-3  2.5626500137E-3  2.1145299543E-3  -3.1295299996E-3  -2.7556000277E-3  1.3962360099E-2  7.8046298586E-3  -9.3812197447E-3  7.8046298586E-3  1.3962360099E-2  -2.7556000277E-3  -3.1295299996E-3  2.1145299543E-3  2.5626500137E-3  1.9235999789E-3
+2.0687500946E-3  2.2892199922E-3  3.3578000148E-4  -4.5751798898E-3  5.3632198833E-3  7.8046298586E-3  -7.9501636326E-2  -0.1554141641      -7.9501636326E-2  7.8046298586E-3  5.3632198833E-3  -4.5751798898E-3  3.3578000148E-4  2.2892199922E-3  2.0687500946E-3
+2.0898699295E-3  1.9755100366E-3  -8.3368999185E-4  -5.1014497876E-3  7.3032598011E-3  -9.3812197447E-3  -0.1554141641      0.7303866148      -0.1554141641      -9.3812197447E-3  7.3032598011E-3  -5.1014497876E-3  -8.3368999185E-4  1.9755100366E-3  2.0898699295E-3
+2.0687500946E-3  2.2892199922E-3  3.3578000148E-4  -4.5751798898E-3  5.3632198833E-3  7.8046298586E-3  -7.9501636326E-2  -0.1554141641      -7.9501636326E-2  7.8046298586E-3  5.3632198833E-3  -4.5751798898E-3  3.3578000148E-4  2.2892199922E-3  2.0687500946E-3
+1.9235999789E-3  2.5626500137E-3  2.1145299543E-3  -3.1295299996E-3  -2.7556000277E-3  1.3962360099E-2  7.8046298586E-3  -9.3812197447E-3  7.8046298586E-3  1.3962360099E-2  -2.7556000277E-3  -3.1295299996E-3  2.1145299543E-3  2.5626500137E-3  1.9235999789E-3
+1.5450799838E-3  2.1750701126E-3  2.2253401112E-3  -4.9274001503E-4  -6.3222697936E-3  -2.7556000277E-3  5.3632198833E-3  7.3032598011E-3  5.3632198833E-3  -2.7556000277E-3  -6.3222697936E-3  -4.9274001503E-4  2.2253401112E-3  2.1750701126E-3  1.5450799838E-3
+8.8387000142E-4  1.5874400269E-3  1.4050999889E-3  1.2960999738E-3  -4.9274001503E-4  -3.1295299996E-3  -4.5751798898E-3  -5.1014497876E-3  -4.5751798898E-3  -3.1295299996E-3  -4.9274001503E-4  1.2960999738E-3  1.4050999889E-3  1.5874400269E-3  8.8387000142E-4
+-3.7829999201E-5  7.7435001731E-4  1.1793200392E-3  1.4050999889E-3  2.2253401112E-3  2.1145299543E-3  3.3578000148E-4  -8.3368999185E-4  3.3578000148E-4  2.1145299543E-3  2.2253401112E-3  1.4050999889E-3  1.1793200392E-3  7.7435001731E-4  -3.7829999201E-5
+-6.2596000498E-4  -3.2734998967E-4  7.7435001731E-4  1.5874400269E-3  2.1750701126E-3  2.5626500137E-3  2.2892199922E-3  1.9755100366E-3  2.2892199922E-3  2.5626500137E-3  2.1750701126E-3  1.5874400269E-3  7.7435001731E-4  -3.2734998967E-4  -6.2596000498E-4
+-4.0483998600E-4  -6.2596000498E-4  -3.7829999201E-5  8.8387000142E-4  1.5450799838E-3  1.9235999789E-3  2.0687500946E-3  2.0898699295E-3  2.0687500946E-3  1.9235999789E-3  1.5450799838E-3  8.8387000142E-4  -3.7829999201E-5  -6.2596000498E-4  -4.0483998600E-4
+];
+
+lo0filt = [
+-8.7009997515E-5  -1.3542800443E-3  -1.6012600390E-3  -5.0337001448E-4  2.5240099058E-3  -5.0337001448E-4  -1.6012600390E-3  -1.3542800443E-3  -8.7009997515E-5
+-1.3542800443E-3  2.9215801042E-3  7.5227199122E-3  8.2244202495E-3  1.1076199589E-3  8.2244202495E-3  7.5227199122E-3  2.9215801042E-3  -1.3542800443E-3
+-1.6012600390E-3  7.5227199122E-3  -7.0612900890E-3  -3.7694871426E-2  -3.2971370965E-2  -3.7694871426E-2  -7.0612900890E-3  7.5227199122E-3  -1.6012600390E-3
+-5.0337001448E-4  8.2244202495E-3  -3.7694871426E-2  4.3813198805E-2  0.1811603010      4.3813198805E-2  -3.7694871426E-2  8.2244202495E-3  -5.0337001448E-4
+2.5240099058E-3  1.1076199589E-3  -3.2971370965E-2  0.1811603010      0.4376249909      0.1811603010      -3.2971370965E-2  1.1076199589E-3  2.5240099058E-3
+-5.0337001448E-4  8.2244202495E-3  -3.7694871426E-2  4.3813198805E-2  0.1811603010      4.3813198805E-2  -3.7694871426E-2  8.2244202495E-3  -5.0337001448E-4
+-1.6012600390E-3  7.5227199122E-3  -7.0612900890E-3  -3.7694871426E-2  -3.2971370965E-2  -3.7694871426E-2  -7.0612900890E-3  7.5227199122E-3  -1.6012600390E-3
+-1.3542800443E-3  2.9215801042E-3  7.5227199122E-3  8.2244202495E-3  1.1076199589E-3  8.2244202495E-3  7.5227199122E-3  2.9215801042E-3  -1.3542800443E-3
+-8.7009997515E-5  -1.3542800443E-3  -1.6012600390E-3  -5.0337001448E-4  2.5240099058E-3  -5.0337001448E-4  -1.6012600390E-3  -1.3542800443E-3  -8.7009997515E-5
+];
+
+lofilt = [
+-4.3500000174E-5  1.2078000145E-4  -6.7714002216E-4  -1.2434000382E-4  -8.0063997302E-4  -1.5970399836E-3  -2.5168000138E-4  -4.2019999819E-4  1.2619999470E-3  -4.2019999819E-4  -2.5168000138E-4  -1.5970399836E-3  -8.0063997302E-4  -1.2434000382E-4  -6.7714002216E-4  1.2078000145E-4  -4.3500000174E-5
+1.2078000145E-4  4.4606000301E-4  -5.8146001538E-4  5.6215998484E-4  -1.3688000035E-4  2.3255399428E-3  2.8898599558E-3  4.2872801423E-3  5.5893999524E-3  4.2872801423E-3  2.8898599558E-3  2.3255399428E-3  -1.3688000035E-4  5.6215998484E-4  -5.8146001538E-4  4.4606000301E-4  1.2078000145E-4
+-6.7714002216E-4  -5.8146001538E-4  1.4607800404E-3  2.1605400834E-3  3.7613599561E-3  3.0809799209E-3  4.1121998802E-3  2.2212199401E-3  5.5381999118E-4  2.2212199401E-3  4.1121998802E-3  3.0809799209E-3  3.7613599561E-3  2.1605400834E-3  1.4607800404E-3  -5.8146001538E-4  -6.7714002216E-4
+-1.2434000382E-4  5.6215998484E-4  2.1605400834E-3  3.1757799443E-3  3.1846798956E-3  -1.7774800071E-3  -7.4316998944E-3  -9.0569201857E-3  -9.6372198313E-3  -9.0569201857E-3  -7.4316998944E-3  -1.7774800071E-3  3.1846798956E-3  3.1757799443E-3  2.1605400834E-3  5.6215998484E-4  -1.2434000382E-4
+-8.0063997302E-4  -1.3688000035E-4  3.7613599561E-3  3.1846798956E-3  -3.5306399222E-3  -1.2604200281E-2  -1.8847439438E-2  -1.7508180812E-2  -1.6485679895E-2  -1.7508180812E-2  -1.8847439438E-2  -1.2604200281E-2  -3.5306399222E-3  3.1846798956E-3  3.7613599561E-3  -1.3688000035E-4  -8.0063997302E-4
+-1.5970399836E-3  2.3255399428E-3  3.0809799209E-3  -1.7774800071E-3  -1.2604200281E-2  -2.0229380578E-2  -1.1091699824E-2  3.9556599222E-3  1.4385120012E-2  3.9556599222E-3  -1.1091699824E-2  -2.0229380578E-2  -1.2604200281E-2  -1.7774800071E-3  3.0809799209E-3  2.3255399428E-3  -1.5970399836E-3
+-2.5168000138E-4  2.8898599558E-3  4.1121998802E-3  -7.4316998944E-3  -1.8847439438E-2  -1.1091699824E-2  2.1906599402E-2  6.8065837026E-2  9.0580143034E-2  6.8065837026E-2  2.1906599402E-2  -1.1091699824E-2  -1.8847439438E-2  -7.4316998944E-3  4.1121998802E-3  2.8898599558E-3  -2.5168000138E-4
+-4.2019999819E-4  4.2872801423E-3  2.2212199401E-3  -9.0569201857E-3  -1.7508180812E-2  3.9556599222E-3  6.8065837026E-2  0.1445499808      0.1773651242      0.1445499808      6.8065837026E-2  3.9556599222E-3  -1.7508180812E-2  -9.0569201857E-3  2.2212199401E-3  4.2872801423E-3  -4.2019999819E-4
+1.2619999470E-3  5.5893999524E-3  5.5381999118E-4  -9.6372198313E-3  -1.6485679895E-2  1.4385120012E-2  9.0580143034E-2  0.1773651242      0.2120374441      0.1773651242      9.0580143034E-2  1.4385120012E-2  -1.6485679895E-2  -9.6372198313E-3  5.5381999118E-4  5.5893999524E-3  1.2619999470E-3
+-4.2019999819E-4  4.2872801423E-3  2.2212199401E-3  -9.0569201857E-3  -1.7508180812E-2  3.9556599222E-3  6.8065837026E-2  0.1445499808      0.1773651242      0.1445499808      6.8065837026E-2  3.9556599222E-3  -1.7508180812E-2  -9.0569201857E-3  2.2212199401E-3  4.2872801423E-3  -4.2019999819E-4
+-2.5168000138E-4  2.8898599558E-3  4.1121998802E-3  -7.4316998944E-3  -1.8847439438E-2  -1.1091699824E-2  2.1906599402E-2  6.8065837026E-2  9.0580143034E-2  6.8065837026E-2  2.1906599402E-2  -1.1091699824E-2  -1.8847439438E-2  -7.4316998944E-3  4.1121998802E-3  2.8898599558E-3  -2.5168000138E-4
+-1.5970399836E-3  2.3255399428E-3  3.0809799209E-3  -1.7774800071E-3  -1.2604200281E-2  -2.0229380578E-2  -1.1091699824E-2  3.9556599222E-3  1.4385120012E-2  3.9556599222E-3  -1.1091699824E-2  -2.0229380578E-2  -1.2604200281E-2  -1.7774800071E-3  3.0809799209E-3  2.3255399428E-3  -1.5970399836E-3
+-8.0063997302E-4  -1.3688000035E-4  3.7613599561E-3  3.1846798956E-3  -3.5306399222E-3  -1.2604200281E-2  -1.8847439438E-2  -1.7508180812E-2  -1.6485679895E-2  -1.7508180812E-2  -1.8847439438E-2  -1.2604200281E-2  -3.5306399222E-3  3.1846798956E-3  3.7613599561E-3  -1.3688000035E-4  -8.0063997302E-4
+-1.2434000382E-4  5.6215998484E-4  2.1605400834E-3  3.1757799443E-3  3.1846798956E-3  -1.7774800071E-3  -7.4316998944E-3  -9.0569201857E-3  -9.6372198313E-3  -9.0569201857E-3  -7.4316998944E-3  -1.7774800071E-3  3.1846798956E-3  3.1757799443E-3  2.1605400834E-3  5.6215998484E-4  -1.2434000382E-4
+-6.7714002216E-4  -5.8146001538E-4  1.4607800404E-3  2.1605400834E-3  3.7613599561E-3  3.0809799209E-3  4.1121998802E-3  2.2212199401E-3  5.5381999118E-4  2.2212199401E-3  4.1121998802E-3  3.0809799209E-3  3.7613599561E-3  2.1605400834E-3  1.4607800404E-3  -5.8146001538E-4  -6.7714002216E-4
+1.2078000145E-4  4.4606000301E-4  -5.8146001538E-4  5.6215998484E-4  -1.3688000035E-4  2.3255399428E-3  2.8898599558E-3  4.2872801423E-3  5.5893999524E-3  4.2872801423E-3  2.8898599558E-3  2.3255399428E-3  -1.3688000035E-4  5.6215998484E-4  -5.8146001538E-4  4.4606000301E-4  1.2078000145E-4
+-4.3500000174E-5  1.2078000145E-4  -6.7714002216E-4  -1.2434000382E-4  -8.0063997302E-4  -1.5970399836E-3  -2.5168000138E-4  -4.2019999819E-4  1.2619999470E-3  -4.2019999819E-4  -2.5168000138E-4  -1.5970399836E-3  -8.0063997302E-4  -1.2434000382E-4  -6.7714002216E-4  1.2078000145E-4  -4.3500000174E-5
+];
+
+bfilts = [...
+-8.1125000725E-4  4.4451598078E-3  1.2316980399E-2  1.3955879956E-2  1.4179450460E-2  1.3955879956E-2  1.2316980399E-2  4.4451598078E-3  -8.1125000725E-4 ...
+3.9103501476E-3  4.4565401040E-3  -5.8724298142E-3  -2.8760801069E-3  8.5267601535E-3  -2.8760801069E-3  -5.8724298142E-3  4.4565401040E-3  3.9103501476E-3 ...
+1.3462699717E-3  -3.7740699481E-3  8.2581602037E-3  3.9442278445E-2  5.3605638444E-2  3.9442278445E-2  8.2581602037E-3  -3.7740699481E-3  1.3462699717E-3 ...
+7.4700999539E-4  -3.6522001028E-4  -2.2522680461E-2  -0.1105690673      -0.1768419296      -0.1105690673      -2.2522680461E-2  -3.6522001028E-4  7.4700999539E-4 ...
+0.0000000000      0.0000000000      0.0000000000      0.0000000000      0.0000000000      0.0000000000      0.0000000000      0.0000000000      0.0000000000     ...
+-7.4700999539E-4  3.6522001028E-4  2.2522680461E-2  0.1105690673      0.1768419296      0.1105690673      2.2522680461E-2  3.6522001028E-4  -7.4700999539E-4 ...
+-1.3462699717E-3  3.7740699481E-3  -8.2581602037E-3  -3.9442278445E-2  -5.3605638444E-2  -3.9442278445E-2  -8.2581602037E-3  3.7740699481E-3  -1.3462699717E-3 ...
+-3.9103501476E-3  -4.4565401040E-3  5.8724298142E-3  2.8760801069E-3  -8.5267601535E-3  2.8760801069E-3  5.8724298142E-3  -4.4565401040E-3  -3.9103501476E-3 ...
+8.1125000725E-4  -4.4451598078E-3  -1.2316980399E-2  -1.3955879956E-2  -1.4179450460E-2  -1.3955879956E-2  -1.2316980399E-2  -4.4451598078E-3  8.1125000725E-4; ...
+...
+0.0000000000      -8.2846998703E-4  -5.7109999034E-5  4.0110000555E-5  4.6670897864E-3  8.0871898681E-3  1.4807609841E-2  8.6204400286E-3  -3.1221499667E-3 ...
+8.2846998703E-4  0.0000000000      -9.7479997203E-4  -6.9718998857E-3  -2.0865600090E-3  2.3298799060E-3  -4.4814897701E-3  1.4917500317E-2  8.6204400286E-3 ...
+5.7109999034E-5  9.7479997203E-4  0.0000000000      -1.2145539746E-2  -2.4427289143E-2  5.0797060132E-2  3.2785870135E-2  -4.4814897701E-3  1.4807609841E-2 ...
+-4.0110000555E-5  6.9718998857E-3  1.2145539746E-2  0.0000000000      -0.1510555595      -8.2495503128E-2  5.0797060132E-2  2.3298799060E-3  8.0871898681E-3 ...
+-4.6670897864E-3  2.0865600090E-3  2.4427289143E-2  0.1510555595      0.0000000000      -0.1510555595      -2.4427289143E-2  -2.0865600090E-3  4.6670897864E-3 ...
+-8.0871898681E-3  -2.3298799060E-3  -5.0797060132E-2  8.2495503128E-2  0.1510555595      0.0000000000      -1.2145539746E-2  -6.9718998857E-3  4.0110000555E-5 ...
+-1.4807609841E-2  4.4814897701E-3  -3.2785870135E-2  -5.0797060132E-2  2.4427289143E-2  1.2145539746E-2  0.0000000000      -9.7479997203E-4  -5.7109999034E-5 ...
+-8.6204400286E-3  -1.4917500317E-2  4.4814897701E-3  -2.3298799060E-3  2.0865600090E-3  6.9718998857E-3  9.7479997203E-4  0.0000000000      -8.2846998703E-4 ...
+3.1221499667E-3  -8.6204400286E-3  -1.4807609841E-2  -8.0871898681E-3  -4.6670897864E-3  -4.0110000555E-5  5.7109999034E-5  8.2846998703E-4  0.0000000000; ...
+...
+8.1125000725E-4  -3.9103501476E-3  -1.3462699717E-3  -7.4700999539E-4  0.0000000000      7.4700999539E-4  1.3462699717E-3  3.9103501476E-3  -8.1125000725E-4 ...
+-4.4451598078E-3  -4.4565401040E-3  3.7740699481E-3  3.6522001028E-4  0.0000000000      -3.6522001028E-4  -3.7740699481E-3  4.4565401040E-3  4.4451598078E-3 ...
+-1.2316980399E-2  5.8724298142E-3  -8.2581602037E-3  2.2522680461E-2  0.0000000000      -2.2522680461E-2  8.2581602037E-3  -5.8724298142E-3  1.2316980399E-2 ...
+-1.3955879956E-2  2.8760801069E-3  -3.9442278445E-2  0.1105690673      0.0000000000      -0.1105690673      3.9442278445E-2  -2.8760801069E-3  1.3955879956E-2 ...
+-1.4179450460E-2  -8.5267601535E-3  -5.3605638444E-2  0.1768419296      0.0000000000      -0.1768419296     5.3605638444E-2  8.5267601535E-3  1.4179450460E-2 ...
+-1.3955879956E-2  2.8760801069E-3  -3.9442278445E-2  0.1105690673      0.0000000000      -0.1105690673      3.9442278445E-2  -2.8760801069E-3  1.3955879956E-2 ...
+-1.2316980399E-2  5.8724298142E-3  -8.2581602037E-3  2.2522680461E-2  0.0000000000      -2.2522680461E-2  8.2581602037E-3  -5.8724298142E-3  1.2316980399E-2 ...
+-4.4451598078E-3  -4.4565401040E-3  3.7740699481E-3  3.6522001028E-4  0.0000000000      -3.6522001028E-4  -3.7740699481E-3  4.4565401040E-3  4.4451598078E-3 ...
+8.1125000725E-4  -3.9103501476E-3  -1.3462699717E-3  -7.4700999539E-4  0.0000000000      7.4700999539E-4  1.3462699717E-3  3.9103501476E-3  -8.1125000725E-4; ...
+...
+3.1221499667E-3  -8.6204400286E-3  -1.4807609841E-2  -8.0871898681E-3  -4.6670897864E-3  -4.0110000555E-5  5.7109999034E-5  8.2846998703E-4  0.0000000000  ...   
+-8.6204400286E-3  -1.4917500317E-2  4.4814897701E-3  -2.3298799060E-3  2.0865600090E-3  6.9718998857E-3  9.7479997203E-4  -0.0000000000      -8.2846998703E-4 ...
+-1.4807609841E-2  4.4814897701E-3  -3.2785870135E-2  -5.0797060132E-2  2.4427289143E-2  1.2145539746E-2  0.0000000000      -9.7479997203E-4  -5.7109999034E-5 ...
+-8.0871898681E-3  -2.3298799060E-3  -5.0797060132E-2  8.2495503128E-2  0.1510555595      -0.0000000000      -1.2145539746E-2  -6.9718998857E-3  4.0110000555E-5 ...
+-4.6670897864E-3  2.0865600090E-3  2.4427289143E-2  0.1510555595      0.0000000000      -0.1510555595      -2.4427289143E-2  -2.0865600090E-3  4.6670897864E-3 ...
+-4.0110000555E-5  6.9718998857E-3  1.2145539746E-2  0.0000000000      -0.1510555595      -8.2495503128E-2  5.0797060132E-2  2.3298799060E-3  8.0871898681E-3 ...
+5.7109999034E-5  9.7479997203E-4  -0.0000000000      -1.2145539746E-2  -2.4427289143E-2  5.0797060132E-2  3.2785870135E-2  -4.4814897701E-3  1.4807609841E-2 ...
+8.2846998703E-4  -0.0000000000      -9.7479997203E-4  -6.9718998857E-3  -2.0865600090E-3  2.3298799060E-3  -4.4814897701E-3  1.4917500317E-2  8.6204400286E-3 ...
+0.0000000000      -8.2846998703E-4  -5.7109999034E-5  4.0110000555E-5  4.6670897864E-3  8.0871898681E-3  1.4807609841E-2  8.6204400286E-3  -3.1221499667E-3 ...
+]'; 
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp5Filters.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp5Filters.m
new file mode 100755
index 0000000..4cddcfd
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/sp5Filters.m
@@ -0,0 +1,110 @@
+% Steerable pyramid filters.  Transform described  in:
+%
+% @INPROCEEDINGS{Simoncelli95b,
+%       TITLE = "The Steerable Pyramid: A Flexible Architecture for
+%                Multi-Scale Derivative Computation",
+%       AUTHOR = "E P Simoncelli and W T Freeman",
+%       BOOKTITLE = "Second Int'l Conf on Image Processing",
+%       ADDRESS = "Washington, DC", MONTH = "October", YEAR = 1995 }
+%
+% Filter kernel design described in:
+%
+%@INPROCEEDINGS{Karasaridis96,
+%       TITLE = "A Filter Design Technique for 
+%               Steerable Pyramid Image Transforms",
+%       AUTHOR = "A Karasaridis and E P Simoncelli",
+%       BOOKTITLE = "ICASSP",   ADDRESS = "Atlanta, GA",
+%       MONTH = "May",  YEAR = 1996 }
+
+% Eero Simoncelli, 6/96.
+
+function [lo0filt,hi0filt,lofilt,bfilts,mtx,harmonics] = sp5Filters();
+
+harmonics = [1 3 5];
+
+mtx = [ ...
+    0.3333    0.2887    0.1667    0.0000   -0.1667   -0.2887
+    0.0000    0.1667    0.2887    0.3333    0.2887    0.1667
+    0.3333   -0.0000   -0.3333   -0.0000    0.3333   -0.0000
+    0.0000    0.3333    0.0000   -0.3333    0.0000    0.3333
+    0.3333   -0.2887    0.1667   -0.0000   -0.1667    0.2887
+   -0.0000    0.1667   -0.2887    0.3333   -0.2887    0.1667];
+
+hi0filt = [ 
+-0.00033429 -0.00113093 -0.00171484 -0.00133542 -0.00080639 -0.00133542 -0.00171484 -0.00113093 -0.00033429
+-0.00113093 -0.00350017 -0.00243812 0.00631653 0.01261227 0.00631653 -0.00243812 -0.00350017 -0.00113093
+-0.00171484 -0.00243812 -0.00290081 -0.00673482 -0.00981051 -0.00673482 -0.00290081 -0.00243812 -0.00171484
+-0.00133542 0.00631653 -0.00673482 -0.07027679 -0.11435863 -0.07027679 -0.00673482 0.00631653 -0.00133542
+-0.00080639 0.01261227 -0.00981051 -0.11435863 0.81380200 -0.11435863 -0.00981051 0.01261227 -0.00080639
+-0.00133542 0.00631653 -0.00673482 -0.07027679 -0.11435863 -0.07027679 -0.00673482 0.00631653 -0.00133542
+-0.00171484 -0.00243812 -0.00290081 -0.00673482 -0.00981051 -0.00673482 -0.00290081 -0.00243812 -0.00171484
+-0.00113093 -0.00350017 -0.00243812 0.00631653 0.01261227 0.00631653 -0.00243812 -0.00350017 -0.00113093
+-0.00033429 -0.00113093 -0.00171484 -0.00133542 -0.00080639 -0.00133542 -0.00171484 -0.00113093 -0.00033429];
+
+
+lo0filt = [
+0.00341614 -0.01551246 -0.03848215 -0.01551246 0.00341614
+-0.01551246 0.05586982 0.15925570 0.05586982 -0.01551246
+-0.03848215 0.15925570 0.40304148 0.15925570 -0.03848215
+-0.01551246 0.05586982 0.15925570 0.05586982 -0.01551246
+0.00341614 -0.01551246 -0.03848215 -0.01551246 0.00341614];
+
+lofilt = 2*[
+0.00085404 -0.00244917 -0.00387812 -0.00944432 -0.00962054 -0.00944432 -0.00387812 -0.00244917 0.00085404
+-0.00244917 -0.00523281 -0.00661117 0.00410600 0.01002988 0.00410600 -0.00661117 -0.00523281 -0.00244917
+-0.00387812 -0.00661117 0.01396746 0.03277038 0.03981393 0.03277038 0.01396746 -0.00661117 -0.00387812
+-0.00944432 0.00410600 0.03277038 0.06426333 0.08169618 0.06426333 0.03277038 0.00410600 -0.00944432
+-0.00962054 0.01002988 0.03981393 0.08169618 0.10096540 0.08169618 0.03981393 0.01002988 -0.00962054
+-0.00944432 0.00410600 0.03277038 0.06426333 0.08169618 0.06426333 0.03277038 0.00410600 -0.00944432
+-0.00387812 -0.00661117 0.01396746 0.03277038 0.03981393 0.03277038 0.01396746 -0.00661117 -0.00387812
+-0.00244917 -0.00523281 -0.00661117 0.00410600 0.01002988 0.00410600 -0.00661117 -0.00523281 -0.00244917
+0.00085404 -0.00244917 -0.00387812 -0.00944432 -0.00962054 -0.00944432 -0.00387812 -0.00244917 0.00085404];
+
+bfilts = [...
+ 0.00277643 0.00496194 0.01026699 0.01455399 0.01026699 0.00496194 0.00277643 ...
+-0.00986904 -0.00893064 0.01189859 0.02755155 0.01189859 -0.00893064 -0.00986904 ...
+-0.01021852 -0.03075356 -0.08226445 -0.11732297 -0.08226445 -0.03075356 -0.01021852 ...
+ 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 ...
+ 0.01021852 0.03075356 0.08226445 0.11732297 0.08226445 0.03075356 0.01021852 ...
+ 0.00986904 0.00893064 -0.01189859 -0.02755155 -0.01189859 0.00893064 0.00986904 ...
+-0.00277643 -0.00496194 -0.01026699 -0.01455399 -0.01026699 -0.00496194 -0.00277643;
+...
+-0.00343249 -0.00640815 -0.00073141 0.01124321 0.00182078 0.00285723 0.01166982 ...
+-0.00358461 -0.01977507 -0.04084211 -0.00228219 0.03930573 0.01161195 0.00128000 ...
+ 0.01047717 0.01486305 -0.04819057 -0.12227230 -0.05394139 0.00853965 -0.00459034 ...
+ 0.00790407 0.04435647 0.09454202 -0.00000000 -0.09454202 -0.04435647 -0.00790407 ...
+ 0.00459034 -0.00853965 0.05394139 0.12227230 0.04819057 -0.01486305 -0.01047717 ...
+-0.00128000 -0.01161195 -0.03930573 0.00228219 0.04084211 0.01977507 0.00358461 ...
+-0.01166982 -0.00285723 -0.00182078 -0.01124321 0.00073141 0.00640815 0.00343249;
+...
+ 0.00343249 0.00358461 -0.01047717 -0.00790407 -0.00459034 0.00128000 0.01166982 ...
+ 0.00640815 0.01977507 -0.01486305 -0.04435647 0.00853965 0.01161195 0.00285723 ...
+ 0.00073141 0.04084211 0.04819057 -0.09454202 -0.05394139 0.03930573 0.00182078 ...
+-0.01124321 0.00228219 0.12227230 -0.00000000 -0.12227230 -0.00228219 0.01124321 ...
+-0.00182078 -0.03930573 0.05394139 0.09454202 -0.04819057 -0.04084211 -0.00073141 ...
+-0.00285723 -0.01161195 -0.00853965 0.04435647 0.01486305 -0.01977507 -0.00640815 ...
+-0.01166982 -0.00128000 0.00459034 0.00790407 0.01047717 -0.00358461 -0.00343249;
+...
+-0.00277643 0.00986904 0.01021852 -0.00000000 -0.01021852 -0.00986904 0.00277643 ...
+-0.00496194 0.00893064 0.03075356 -0.00000000 -0.03075356 -0.00893064 0.00496194 ...
+-0.01026699 -0.01189859 0.08226445 -0.00000000 -0.08226445 0.01189859 0.01026699 ...
+-0.01455399 -0.02755155 0.11732297 -0.00000000 -0.11732297 0.02755155 0.01455399 ...
+-0.01026699 -0.01189859 0.08226445 -0.00000000 -0.08226445 0.01189859 0.01026699 ...
+-0.00496194 0.00893064 0.03075356 -0.00000000 -0.03075356 -0.00893064 0.00496194 ...
+-0.00277643 0.00986904 0.01021852 -0.00000000 -0.01021852 -0.00986904 0.00277643;
+...
+-0.01166982 -0.00128000 0.00459034 0.00790407 0.01047717 -0.00358461 -0.00343249 ...
+-0.00285723 -0.01161195 -0.00853965 0.04435647 0.01486305 -0.01977507 -0.00640815 ...
+-0.00182078 -0.03930573 0.05394139 0.09454202 -0.04819057 -0.04084211 -0.00073141 ...
+-0.01124321 0.00228219 0.12227230 -0.00000000 -0.12227230 -0.00228219 0.01124321 ...
+ 0.00073141 0.04084211 0.04819057 -0.09454202 -0.05394139 0.03930573 0.00182078 ...
+ 0.00640815 0.01977507 -0.01486305 -0.04435647 0.00853965 0.01161195 0.00285723 ...
+ 0.00343249 0.00358461 -0.01047717 -0.00790407 -0.00459034 0.00128000 0.01166982;
+...
+-0.01166982 -0.00285723 -0.00182078 -0.01124321 0.00073141 0.00640815 0.00343249 ...
+-0.00128000 -0.01161195 -0.03930573 0.00228219 0.04084211 0.01977507 0.00358461 ...
+ 0.00459034 -0.00853965 0.05394139 0.12227230 0.04819057 -0.01486305 -0.01047717 ...
+ 0.00790407 0.04435647 0.09454202 -0.00000000 -0.09454202 -0.04435647 -0.00790407 ...
+ 0.01047717 0.01486305 -0.04819057 -0.12227230 -0.05394139 0.00853965 -0.00459034 ...
+-0.00358461 -0.01977507 -0.04084211 -0.00228219 0.03930573 0.01161195 0.00128000 ...
+-0.00343249 -0.00640815 -0.00073141 0.01124321 0.00182078 0.00285723 0.01166982]'; 
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrBand.m
new file mode 100755
index 0000000..474a8dc
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrBand.m
@@ -0,0 +1,34 @@
+% [LEV,IND] = spyrBand(PYR,INDICES,LEVEL,BAND)
+%
+% Access a band from a steerable pyramid.
+% 
+%   LEVEL indicates the scale (finest = 1, coarsest = spyrHt(INDICES)).
+% 
+%   BAND (optional, default=1) indicates which subband 
+%     (1 = vertical, rest proceeding anti-clockwise).
+
+% Eero Simoncelli, 6/96.
+
+function res =  spyrBand(pyr,pind,level,band)
+
+if (exist('level') ~= 1)
+  level = 1;
+end
+
+if (exist('band') ~= 1)
+  band = 1;
+end
+
+nbands = spyrNumBands(pind);
+if ((band > nbands) | (band < 1))
+  error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands));
+end     
+
+maxLev = spyrHt(pind);
+if ((level > maxLev) | (level < 1))
+  error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev));
+end
+
+firstband = 1 + band + nbands*(level-1);
+res  = pyrBand(pyr, pind, firstband);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHigh.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHigh.m
new file mode 100755
index 0000000..f91b466
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHigh.m
@@ -0,0 +1,10 @@
+% RES = spyrHigh(PYR, INDICES)
+%
+% Access the highpass residual band from a steerable pyramid.
+
+% Eero Simoncelli, 6/96.
+
+function res =  spyrHigh(pyr,pind)
+
+res  = pyrBand(pyr, pind, 1);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHt.m
new file mode 100755
index 0000000..8706b9e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrHt.m
@@ -0,0 +1,16 @@
+% [HEIGHT] = spyrHt(INDICES)
+%
+% Compute height of steerable pyramid with given index matrix.
+
+% Eero Simoncelli, 6/96.
+
+function [ht] =  spyrHt(pind)
+
+nbands = spyrNumBands(pind);
+
+% Don't count lowpass, or highpass residual bands
+if (size(pind,1) > 2)
+  ht = (size(pind,1)-2)/nbands;
+else
+  ht = 0;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrLev.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrLev.m
new file mode 100755
index 0000000..5cb4a85
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrLev.m
@@ -0,0 +1,24 @@
+% [LEV,IND] = spyrLev(PYR,INDICES,LEVEL)
+%
+% Access a level from a steerable pyramid.
+% Return as an SxB matrix, B = number of bands, S = total size of a band.
+% Also returns an Bx2 matrix containing dimensions of the subbands.
+
+% Eero Simoncelli, 6/96.
+
+function [lev,ind] =  spyrLev(pyr,pind,level)
+
+nbands = spyrNumBands(pind);
+                
+if ((level > spyrHt(pind)) | (level < 1))
+  error(sprintf('Level number must be in the range [1, %d].', spyrHt(pind)));
+end     
+        
+firstband = 2 + nbands*(level-1);
+firstind = 1;
+for l=1:firstband-1
+  firstind = firstind + prod(pind(l,:));
+end
+
+ind = pind(firstband:firstband+nbands-1,:);
+lev  = pyr(firstind:firstind+sum(prod(ind'))-1);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrNumBands.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrNumBands.m
new file mode 100755
index 0000000..68aec3f
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/spyrNumBands.m
@@ -0,0 +1,20 @@
+% [NBANDS] = spyrNumBands(INDICES)
+%
+% Compute number of orientation bands in a steerable pyramid with
+% given index matrix.  If the pyramid contains only the highpass and
+% lowpass bands (i.e., zero levels), returns 0.
+
+% Eero Simoncelli, 2/97.
+
+function [nbands] =  spyrNumBands(pind)
+
+if (size(pind,1) == 2)
+  nbands  = 0;
+else
+  % Count number of orientation bands:
+  b = 3;
+  while ((b <= size(pind,1)) & all( pind(b,:) == pind(2,:)) )
+    b = b+1;
+  end
+  nbands = b-2;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer.m
new file mode 100755
index 0000000..8f9c2ac
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer.m
@@ -0,0 +1,68 @@
+% RES = STEER(BASIS, ANGLE, HARMONICS, STEERMTX)
+%
+% Steer BASIS to the specfied ANGLE.  
+% 
+% BASIS should be a matrix whose columns are vectorized rotated copies of a 
+% steerable function, or the responses of a set of steerable filters.
+% 
+% ANGLE can be a scalar, or a column vector the size of the basis.
+% 
+% HARMONICS (optional, default is N even or odd low frequencies, as for 
+% derivative filters) should be a list of harmonic numbers indicating
+% the angular harmonic content of the basis.
+% 
+% STEERMTX (optional, default assumes cosine phase harmonic components,
+% and filter positions at 2pi*n/N) should be a matrix which maps
+% the filters onto Fourier series components (ordered [cos0 cos1 sin1 
+% cos2 sin2 ... sinN]).  See steer2HarmMtx.m
+
+% Eero Simoncelli, 7/96.
+
+function res = steer(basis,angle,harmonics,steermtx)
+
+num = size(basis,2);
+
+if ( any(size(angle) ~= [size(basis,1) 1]) & any(size(angle) ~= [1 1]) )
+  error('ANGLE must be a scalar, or a column vector the size of the basis elements');
+end
+
+%% If HARMONICS are not passed, assume derivatives.
+if (exist('harmonics') ~= 1)
+  if (mod(num,2) == 0)
+    harmonics = [0:(num/2)-1]'*2 + 1;
+  else
+    harmonics = [0:(num-1)/2]'*2;
+  end
+else
+  harmonics = harmonics(:);
+  if ((2*size(harmonics,1)-any(harmonics == 0)) ~= num)
+    error('harmonics list is incompatible with basis size');
+  end
+end
+
+%% If STEERMTX not passed, assume evenly distributed cosine-phase filters:
+if (exist('steermtx') ~= 1)
+  steermtx = steer2HarmMtx(harmonics, pi*[0:num-1]/num, 'even');
+end
+
+steervect = zeros(size(angle,1),num);
+arg = angle * harmonics(find(harmonics~=0))';
+if (all(harmonics))
+        steervect(:, 1:2:num) = cos(arg);
+        steervect(:, 2:2:num) = sin(arg);
+else
+        steervect(:, 1) = ones(size(arg,1),1);
+        steervect(:, 2:2:num) = cos(arg);
+        steervect(:, 3:2:num) = sin(arg);
+end
+
+steervect = steervect * steermtx;
+
+if (size(steervect,1) > 1)
+        tmp = basis' .* steervect';
+        res = sum(tmp)';
+else
+        res = basis * steervect';
+end
+        
+        
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer2HarmMtx.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer2HarmMtx.m
new file mode 100755
index 0000000..1f3e80e
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/steer2HarmMtx.m
@@ -0,0 +1,71 @@
+% MTX = steer2HarmMtx(HARMONICS, ANGLES, REL_PHASES)
+%
+% Compute a steering matrix (maps a directional basis set onto the
+% angular Fourier harmonics).  HARMONICS is a vector specifying the
+% angular harmonics contained in the steerable basis/filters.  ANGLES 
+% (optional) is a vector specifying the angular position of each filter.  
+% REL_PHASES (optional, default = 'even') specifies whether the harmonics 
+% are cosine or sine phase aligned about those positions.
+% The result matrix is suitable for passing to the function STEER.
+
+% Eero Simoncelli, 7/96.
+
+function mtx = steer2HarmMtx(harmonics, angles, evenorodd)
+
+%%=================================================================
+%%% Optional Parameters:
+
+if (exist('evenorodd') ~= 1)
+  evenorodd = 'even';
+end
+
+% Make HARMONICS a row vector
+harmonics = harmonics(:)';
+
+numh = 2*size(harmonics,2) - any(harmonics == 0);
+
+if (exist('angles') ~= 1)
+  angles = pi * [0:numh-1]'/numh;
+else
+  angles = angles(:);
+end
+
+%%=================================================================
+
+if isstr(evenorodd)
+  if strcmp(evenorodd,'even')
+    evenorodd = 0;
+  elseif strcmp(evenorodd,'odd')
+    evenorodd = 1;
+  else
+    error('EVEN_OR_ODD should be the string  EVEN or ODD');
+  end
+end
+
+%% Compute inverse matrix, which maps Fourier components onto 
+%% steerable basis.
+imtx = zeros(size(angles,1),numh);
+col = 1;
+for h=harmonics
+  args = h*angles;
+  if (h == 0)
+    imtx(:,col) = ones(size(angles));
+    col = col+1;
+  elseif evenorodd
+    imtx(:,col) = sin(args);
+    imtx(:,col+1) = -cos(args);
+    col = col+2;
+  else
+    imtx(:,col) = cos(args);
+    imtx(:,col+1) = sin(args);
+    col = col+2;
+  end
+end
+  
+r = rank(imtx);
+if (( r ~= numh ) & ( r ~= size(angles,1) ))
+  fprintf(2,'WARNING: matrix is not full rank');
+end  
+
+mtx = pinv(imtx);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/subMtx.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/subMtx.m
new file mode 100755
index 0000000..ea3c2ea
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/subMtx.m
@@ -0,0 +1,21 @@
+% MTX = subMtx(VEC, DIMENSIONS, START_INDEX)
+%
+% Reshape a portion of VEC starting from START_INDEX (optional,
+% default=1) to the given dimensions.
+
+% Eero Simoncelli, 6/96.
+
+function mtx = subMtx(vec, sz, offset)
+
+if (exist('offset') ~= 1)
+   offset = 1;
+end
+
+vec = vec(:);
+sz = sz(:);
+
+if (size(sz,1) ~= 2)
+  error('DIMENSIONS must be a 2-vector.');
+end
+
+mtx = reshape( vec(offset:offset+prod(sz)-1), sz(1), sz(2) );
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upBlur.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upBlur.m
new file mode 100755
index 0000000..948c2e1
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upBlur.m
@@ -0,0 +1,52 @@
+% RES = upBlur(IM, LEVELS, FILT)
+%
+% Upsample and blur an image.  The blurring is done with filter
+% kernel specified by FILT (default = 'binom5'), which can be a string
+% (to be passed to namedFilter), a vector (applied separably as a 1D
+% convolution kernel in X and Y), or a matrix (applied as a 2D
+% convolution kernel).  The downsampling is always by 2 in each
+% direction.
+%
+% The procedure is applied recursively LEVELS times (default=1).
+
+% Eero Simoncelli, 4/97.
+
+function res = upBlur(im, nlevs, filt)
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('nlevs') ~= 1) 
+  nlevs = 1;
+end
+
+if (exist('filt') ~= 1) 
+  filt = 'binom5';
+end
+
+%------------------------------------------------------------
+
+if isstr(filt)
+  filt = namedFilter(filt);
+end  
+
+if nlevs > 1
+  im = upBlur(im,nlevs-1,filt);
+end
+
+if (nlevs >= 1)
+  if (any(size(im)==1))
+    if (size(im,1)==1)
+      filt = filt';
+    end
+    res = upConv(im,filt,'reflect1',(size(im)~=1)+1);
+  elseif (any(size(filt)==1))
+    filt = filt(:);
+    res = upConv(im,filt,'reflect1',[2 1]);
+    res = upConv(res,filt','reflect1',[1 2]);
+  else
+    res = upConv(im,filt,'reflect1',[2 2]);
+  end
+else
+  res = im;
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upConv.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upConv.m
new file mode 100755
index 0000000..4d1ffd9
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/upConv.m
@@ -0,0 +1,80 @@
+% RES = upConv(IM, FILT, EDGES, STEP, START, STOP, RES)
+%
+% Upsample matrix IM, followed by convolution with matrix FILT.  These
+% arguments should be 1D or 2D matrices, and IM must be larger (in
+% both dimensions) than FILT.  The origin of filt
+% is assumed to be floor(size(filt)/2)+1.
+%
+% EDGES is a string determining boundary handling:
+%    'circular' - Circular convolution
+%    'reflect1' - Reflect about the edge pixels
+%    'reflect2' - Reflect, doubling the edge pixels
+%    'repeat'   - Repeat the edge pixels
+%    'zero'     - Assume values of zero outside image boundary
+%    'extend'   - Reflect and invert
+%    'dont-compute' - Zero output when filter overhangs OUTPUT boundaries
+%
+% Upsampling factors are determined by STEP (optional, default=[1 1]),
+% a 2-vector [y,x].
+% 
+% The window over which the convolution occurs is specfied by START 
+% (optional, default=[1,1], and STOP (optional, default = 
+% step .* (size(IM) + floor((start-1)./step))).
+%
+% RES is an optional result matrix.  The convolution result will be 
+% destructively added into this matrix.  If this argument is passed, the 
+% result matrix will not be returned. DO NOT USE THIS ARGUMENT IF 
+% YOU DO NOT UNDERSTAND WHAT THIS MEANS!!
+% 
+% NOTE: this operation corresponds to multiplication of a signal
+% vector by a matrix whose columns contain copies of the time-reversed
+% (or space-reversed) FILT shifted by multiples of STEP.  See corrDn.m
+% for the operation corresponding to the transpose of this matrix.
+
+% Eero Simoncelli, 6/96.  revised 2/97.
+
+function result = upConv(im,filt,edges,step,start,stop,res)
+
+%% THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
+
+fprintf(1,'WARNING: You should compile the MEX version of "upConv.c",\n         found in the MEX subdirectory of matlabPyrTools, and put it in your matlab path.  It is MUCH faster, and provides more boundary-handling options.\n');
+
+%------------------------------------------------------------
+%% OPTIONAL ARGS:
+
+if (exist('edges') == 1) 
+  if (strcmp(edges,'reflect1') ~= 1)
+    warning('Using REFLECT1 edge-handling (use MEX code for other options).');
+  end
+end
+
+if (exist('step') ~= 1)
+  step = [1,1];
+end     
+
+if (exist('start') ~= 1)
+  start = [1,1];
+end     
+
+% A multiple of step
+if (exist('stop') ~= 1)
+  stop = step .* (floor((start-ones(size(start)))./step)+size(im))
+end     
+
+if ( ceil((stop(1)+1-start(1)) / step(1)) ~= size(im,1) )
+  error('Bad Y result dimension');
+end
+if ( ceil((stop(2)+1-start(2)) / step(2)) ~= size(im,2) )
+  error('Bad X result dimension');
+end
+
+if (exist('res') ~= 1)
+  res = zeros(stop-start+1);
+end     
+
+%------------------------------------------------------------
+
+tmp = zeros(size(res));
+tmp(start(1):step(1):stop(1),start(2):step(2):stop(2)) = im;
+
+result = rconv2(tmp,filt) + res;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/var2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/var2.m
new file mode 100755
index 0000000..6957eff
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/var2.m
@@ -0,0 +1,17 @@
+% V = VAR2(MTX,MEAN)
+%
+% Sample variance of a matrix.
+%  Passing MEAN (optional) makes the calculation faster.
+
+function res = var2(mtx, mn)
+
+if (exist('mn') ~= 1)
+  mn =  mean2(mtx);
+end
+
+if (isreal(mtx))
+  res = sum(sum(abs(mtx-mn).^2)) / max((prod(size(mtx)) - 1),1);
+else
+  res = sum(sum(real(mtx-mn).^2)) + i*sum(sum(imag(mtx-mn).^2));
+  res = res  / max((prod(size(mtx)) - 1),1);
+end
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/vectify.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/vectify.m
new file mode 100755
index 0000000..3664223
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/vectify.m
@@ -0,0 +1,8 @@
+% [VEC] = columnize(MTX)
+% 
+% Pack elements of MTX into a column vector.  Just provides a
+% function-call notatoin for the operation MTX(:)
+
+function vec = columnize(mtx)
+
+vec = mtx(:);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrBand.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrBand.m
new file mode 100755
index 0000000..c027cca
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrBand.m
@@ -0,0 +1,39 @@
+% RES = wpyrBand(PYR, INDICES, LEVEL, BAND)
+%
+% Access a subband from a separable QMF/wavelet pyramid.  
+% 
+% LEVEL (optional, default=1) indicates the scale (finest = 1,
+% coarsest = wpyrHt(INDICES)).  
+% 
+% BAND (optional, default=1) indicates which subband (1=horizontal,
+% 2=vertical, 3=diagonal).
+
+% Eero Simoncelli, 6/96.
+
+function im =  wpyrBand(pyr,pind,level,band)
+
+if (exist('level') ~= 1)
+  level = 1;
+end
+
+if (exist('band') ~= 1)
+  band = 1;
+end
+
+if ((pind(1,1) == 1) | (pind(1,2) ==1))
+  nbands = 1;
+else
+  nbands = 3;
+end
+                
+if ((band > nbands) | (band < 1))
+  error(sprintf('Bad band number (%d) should be in range [1,%d].', band, nbands));
+end
+        
+maxLev = wpyrHt(pind);
+if ((level > maxLev) | (level < 1))
+  error(sprintf('Bad level number (%d), should be in range [1,%d].', level, maxLev));
+end
+
+band = band + nbands*(level-1);
+im = pyrBand(pyr,pind,band);
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrHt.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrHt.m
new file mode 100755
index 0000000..476be83
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrHt.m
@@ -0,0 +1,15 @@
+% [HEIGHT] = wpyrHt(INDICES)
+%
+% Compute height of separable QMF/wavelet pyramid with given index matrix.
+
+% Eero Simoncelli, 6/96.
+
+function [ht] =  wpyrHt(pind)
+
+if ((pind(1,1) == 1) | (pind(1,2) ==1))
+        nbands = 1;
+else
+        nbands = 3;
+end
+
+ht = (size(pind,1)-1)/nbands;
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrLev.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrLev.m
new file mode 100755
index 0000000..18f30ae
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/wpyrLev.m
@@ -0,0 +1,30 @@
+% [LEV,IND] = wpyrLev(PYR,INDICES,LEVEL)
+%
+% Access a level from a separable QMF/wavelet pyramid.
+% Return as an SxB matrix, B = number of bands, S = total size of a band.
+% Also returns an Bx2 matrix containing dimensions of the subbands.
+
+% Eero Simoncelli, 6/96.
+
+function [lev,ind] =  wpyrLev(pyr,pind,level)
+
+if ((pind(1,1) == 1) | (pind(1,2) ==1))
+  nbands = 1;
+else
+  nbands = 3;
+end
+                
+if ((level > wpyrHt(pind)) | (level < 1))
+  error(sprintf('Level number must be in the range [1, %d].', wpyrHt(pind)));
+end     
+        
+firstband = 1 + nbands*(level-1)
+firstind = 1;
+for l=1:firstband-1
+  firstind = firstind + prod(pind(l,:));
+end
+
+
+ind = pind(firstband:firstband+nbands-1,:);
+lev  = pyr(firstind:firstind+sum(prod(ind'))-1);
+
diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/zconv2.m b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/zconv2.m
new file mode 100755
index 0000000..f678d89
--- /dev/null
+++ b/SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/zconv2.m
@@ -0,0 +1,41 @@
+% RES = ZCONV2(MTX1, MTX2, CTR)
+%
+% Convolution of two matrices, with boundaries handled as if the larger mtx
+% lies in a sea of zeros. Result will be of size of LARGER vector.
+% 
+% The origin of the smaller matrix is assumed to be its center.
+% For even dimensions, the origin is determined by the CTR (optional) 
+% argument:
+%      CTR   origin
+%       0     DIM/2      (default)
+%       1     (DIM/2)+1  (behaves like conv2(mtx1,mtx2,'same'))
+
+% Eero Simoncelli, 2/97.
+
+function c = zconv2(a,b,ctr)
+
+if (exist('ctr') ~= 1)
+  ctr = 0;
+end
+
+if (( size(a,1) >= size(b,1) ) & ( size(a,2) >= size(b,2) ))
+    large = a; small = b;
+elseif  (( size(a,1) <= size(b,1) ) & ( size(a,2) <= size(b,2) ))
+    large = b; small = a;
+else
+  error('one arg must be larger than the other in both dimensions!');
+end
+
+ly = size(large,1);
+lx = size(large,2);
+sy = size(small,1);
+sx = size(small,2);
+
+%% These values are the index of the small mtx that falls on the
+%% border pixel of the large matrix when computing the first
+%% convolution response sample:
+sy2 = floor((sy+ctr+1)/2);
+sx2 = floor((sx+ctr+1)/2);
+
+clarge = conv2(large,small);
+c = clarge(sy2:ly+sy2-1, sx2:lx+sx2-1);
diff --git a/SD-VBS/benchmarks/tracking/Makefile b/SD-VBS/benchmarks/tracking/Makefile
new file mode 100644
index 0000000..60cc0ec
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/Makefile
@@ -0,0 +1,3 @@
+include ../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/tracking/data/Makefile b/SD-VBS/benchmarks/tracking/data/Makefile
new file mode 100644
index 0000000..ba33d35
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/Makefile
@@ -0,0 +1,3 @@
+include ../../../common/makefiles/Makefile.include
+include $(MAKEFILE_COMMON_DIR)/Makefile.recurse
+
diff --git a/SD-VBS/benchmarks/tracking/data/cif/1.bmp b/SD-VBS/benchmarks/tracking/data/cif/1.bmp
new file mode 100644
index 0000000..6744178
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/cif/1.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/cif/2.bmp b/SD-VBS/benchmarks/tracking/data/cif/2.bmp
new file mode 100644
index 0000000..8c2ac57
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/cif/2.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/cif/3.bmp b/SD-VBS/benchmarks/tracking/data/cif/3.bmp
new file mode 100644
index 0000000..b7195fb
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/cif/3.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/cif/4.bmp b/SD-VBS/benchmarks/tracking/data/cif/4.bmp
new file mode 100644
index 0000000..9f0525a
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/cif/4.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/cif/5.bmp b/SD-VBS/benchmarks/tracking/data/cif/5.bmp
new file mode 100644
index 0000000..2f88c26
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/cif/5.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/cif/Makefile b/SD-VBS/benchmarks/tracking/data/cif/Makefile
new file mode 100644
index 0000000..1be9797
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/cif/Makefile
@@ -0,0 +1,7 @@
+INPUT=cif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=tracking
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/tracking/data/cif/expected.m b/SD-VBS/benchmarks/tracking/data/cif/expected.m
new file mode 100644
index 0000000..679cea9
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/cif/expected.m
@@ -0,0 +1,2 @@
+269.915165      175.828888      195.635312      172.654409      268.516358      289.931921      267.230697      190.086741      
+147.986242      145.928399      148.067509      130.441486      124.919389      64.008098       131.967361      162.460857      
diff --git a/SD-VBS/benchmarks/tracking/data/cif/tracking b/SD-VBS/benchmarks/tracking/data/cif/tracking
new file mode 100755
index 0000000..ca31ed0
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/cif/tracking
diff --git a/SD-VBS/benchmarks/tracking/data/fullhd/1.bmp b/SD-VBS/benchmarks/tracking/data/fullhd/1.bmp
new file mode 100644
index 0000000..3db2ad6
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/fullhd/1.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/fullhd/2.bmp b/SD-VBS/benchmarks/tracking/data/fullhd/2.bmp
new file mode 100644
index 0000000..9ff8e9c
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/fullhd/2.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/fullhd/3.bmp b/SD-VBS/benchmarks/tracking/data/fullhd/3.bmp
new file mode 100644
index 0000000..ec53ae6
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/fullhd/3.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/fullhd/4.bmp b/SD-VBS/benchmarks/tracking/data/fullhd/4.bmp
new file mode 100644
index 0000000..c45c5e9
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/fullhd/4.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/fullhd/Makefile b/SD-VBS/benchmarks/tracking/data/fullhd/Makefile
new file mode 100644
index 0000000..2b37182
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/fullhd/Makefile
@@ -0,0 +1,7 @@
+INPUT=fullhd
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=tracking
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/tracking/data/fullhd/expected.m b/SD-VBS/benchmarks/tracking/data/fullhd/expected.m
new file mode 100644
index 0000000..eb034f0
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/fullhd/expected.m
@@ -0,0 +1,2 @@
+1487.193453     720.553084      1481.188344     382.962678      
+308.382612      306.797105      323.948844      369.542919      
diff --git a/SD-VBS/benchmarks/tracking/data/fullhd/tracking b/SD-VBS/benchmarks/tracking/data/fullhd/tracking
new file mode 100755
index 0000000..d6afa68
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/fullhd/tracking
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/1.bmp b/SD-VBS/benchmarks/tracking/data/qcif/1.bmp
new file mode 100644
index 0000000..140ace2
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/1.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/10.bmp b/SD-VBS/benchmarks/tracking/data/qcif/10.bmp
new file mode 100644
index 0000000..61518bc
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/10.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/2.bmp b/SD-VBS/benchmarks/tracking/data/qcif/2.bmp
new file mode 100644
index 0000000..8e1f7cc
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/2.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/3.bmp b/SD-VBS/benchmarks/tracking/data/qcif/3.bmp
new file mode 100644
index 0000000..95fe31f
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/3.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/4.bmp b/SD-VBS/benchmarks/tracking/data/qcif/4.bmp
new file mode 100644
index 0000000..464608a
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/4.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/5.bmp b/SD-VBS/benchmarks/tracking/data/qcif/5.bmp
new file mode 100644
index 0000000..71eb1b7
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/5.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/6.bmp b/SD-VBS/benchmarks/tracking/data/qcif/6.bmp
new file mode 100644
index 0000000..83e5379
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/6.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/7.bmp b/SD-VBS/benchmarks/tracking/data/qcif/7.bmp
new file mode 100644
index 0000000..95b4015
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/7.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/8.bmp b/SD-VBS/benchmarks/tracking/data/qcif/8.bmp
new file mode 100644
index 0000000..8847887
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/8.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/9.bmp b/SD-VBS/benchmarks/tracking/data/qcif/9.bmp
new file mode 100644
index 0000000..4301f11
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/9.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/Makefile b/SD-VBS/benchmarks/tracking/data/qcif/Makefile
new file mode 100644
index 0000000..fb48d25
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/Makefile
@@ -0,0 +1,7 @@
+INPUT=qcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=tracking
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/expected.m b/SD-VBS/benchmarks/tracking/data/qcif/expected.m
new file mode 100644
index 0000000..65c5984
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/expected.m
@@ -0,0 +1,2 @@
+142.858025      145.068198      102.770607      141.110282      90.859800       135.351851      80.185357       113.844268      117.388158      142.126183      80.877169       
+70.993874       35.205162       77.320628       62.895414       38.040784       78.853200       86.164881       63.301686       74.036975       46.176383       92.916465       
diff --git a/SD-VBS/benchmarks/tracking/data/qcif/tracking b/SD-VBS/benchmarks/tracking/data/qcif/tracking
new file mode 100755
index 0000000..7288f16
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/qcif/tracking
diff --git a/SD-VBS/benchmarks/tracking/data/sim/1.bmp b/SD-VBS/benchmarks/tracking/data/sim/1.bmp
new file mode 100644
index 0000000..825ea49
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim/1.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sim/2.bmp b/SD-VBS/benchmarks/tracking/data/sim/2.bmp
new file mode 100644
index 0000000..d3451be
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim/2.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sim/3.bmp b/SD-VBS/benchmarks/tracking/data/sim/3.bmp
new file mode 100644
index 0000000..b060b06
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim/3.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sim/4.bmp b/SD-VBS/benchmarks/tracking/data/sim/4.bmp
new file mode 100644
index 0000000..137accc
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim/4.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sim/Makefile b/SD-VBS/benchmarks/tracking/data/sim/Makefile
new file mode 100644
index 0000000..42e2aa9
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim/Makefile
@@ -0,0 +1,6 @@
+INPUT=sim
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=tracking
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/tracking/data/sim/expected.m b/SD-VBS/benchmarks/tracking/data/sim/expected.m
new file mode 100644
index 0000000..6f90559
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim/expected.m
@@ -0,0 +1,2 @@
+24.422544       21.868191       40.786198       37.742716       30.302637       16.079615       30.062715       35.344185       
+14.131628       32.266282       37.315204       24.606535       32.839030       14.301861       22.509506       15.748797       
diff --git a/SD-VBS/benchmarks/tracking/data/sim/tracking b/SD-VBS/benchmarks/tracking/data/sim/tracking
new file mode 100755
index 0000000..a990020
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim/tracking
diff --git a/SD-VBS/benchmarks/tracking/data/sim_fast/1.bmp b/SD-VBS/benchmarks/tracking/data/sim_fast/1.bmp
new file mode 100644
index 0000000..272897c
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim_fast/1.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sim_fast/2.bmp b/SD-VBS/benchmarks/tracking/data/sim_fast/2.bmp
new file mode 100644
index 0000000..414d2cb
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim_fast/2.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sim_fast/3.bmp b/SD-VBS/benchmarks/tracking/data/sim_fast/3.bmp
new file mode 100644
index 0000000..340e885
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim_fast/3.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sim_fast/4.bmp b/SD-VBS/benchmarks/tracking/data/sim_fast/4.bmp
new file mode 100644
index 0000000..c347859
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim_fast/4.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sim_fast/Makefile b/SD-VBS/benchmarks/tracking/data/sim_fast/Makefile
new file mode 100644
index 0000000..12bcfa5
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim_fast/Makefile
@@ -0,0 +1,6 @@
+INPUT=sim_fast
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=tracking
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/tracking/data/sim_fast/expected.m b/SD-VBS/benchmarks/tracking/data/sim_fast/expected.m
new file mode 100644
index 0000000..f944bf8
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim_fast/expected.m
@@ -0,0 +1,2 @@
+25.330446       17.728868       14.459743       
+16.949109       9.076394        22.247495       
diff --git a/SD-VBS/benchmarks/tracking/data/sim_fast/tracking b/SD-VBS/benchmarks/tracking/data/sim_fast/tracking
new file mode 100755
index 0000000..7309b27
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sim_fast/tracking
diff --git a/SD-VBS/benchmarks/tracking/data/sqcif/1.bmp b/SD-VBS/benchmarks/tracking/data/sqcif/1.bmp
new file mode 100644
index 0000000..06a8c3d
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sqcif/1.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sqcif/2.bmp b/SD-VBS/benchmarks/tracking/data/sqcif/2.bmp
new file mode 100644
index 0000000..fd5c01f
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sqcif/2.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sqcif/3.bmp b/SD-VBS/benchmarks/tracking/data/sqcif/3.bmp
new file mode 100644
index 0000000..14ab860
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sqcif/3.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sqcif/4.bmp b/SD-VBS/benchmarks/tracking/data/sqcif/4.bmp
new file mode 100644
index 0000000..7afba08
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sqcif/4.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/sqcif/Makefile b/SD-VBS/benchmarks/tracking/data/sqcif/Makefile
new file mode 100644
index 0000000..c47a0fd
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sqcif/Makefile
@@ -0,0 +1,6 @@
+INPUT=sqcif
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=tracking
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
diff --git a/SD-VBS/benchmarks/tracking/data/sqcif/expected.m b/SD-VBS/benchmarks/tracking/data/sqcif/expected.m
new file mode 100644
index 0000000..db8a05c
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sqcif/expected.m
@@ -0,0 +1,2 @@
+65.833985       96.386766       76.545247       96.006777       62.175348       60.185245       31.941927       68.970416       85.550211       109.931998      72.298306       74.080821       
+25.209999       70.490525       41.265387       59.869753       52.207516       62.050369       30.542002       70.430274       63.040458       45.825585       49.742089       63.956939       
diff --git a/SD-VBS/benchmarks/tracking/data/sqcif/tracking b/SD-VBS/benchmarks/tracking/data/sqcif/tracking
new file mode 100755
index 0000000..6ec0f98
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/sqcif/tracking
diff --git a/SD-VBS/benchmarks/tracking/data/test/1.bmp b/SD-VBS/benchmarks/tracking/data/test/1.bmp
new file mode 100644
index 0000000..72079a8
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/test/1.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/test/2.bmp b/SD-VBS/benchmarks/tracking/data/test/2.bmp
new file mode 100644
index 0000000..d13e26c
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/test/2.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/test/3.bmp b/SD-VBS/benchmarks/tracking/data/test/3.bmp
new file mode 100644
index 0000000..10eb499
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/test/3.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/test/4.bmp b/SD-VBS/benchmarks/tracking/data/test/4.bmp
new file mode 100644
index 0000000..6536ea7
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/test/4.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/test/Makefile b/SD-VBS/benchmarks/tracking/data/test/Makefile
new file mode 100644
index 0000000..963bebc
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/test/Makefile
@@ -0,0 +1,5 @@
+INPUT=test
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=tracking
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
diff --git a/SD-VBS/benchmarks/tracking/data/test/expected.m b/SD-VBS/benchmarks/tracking/data/test/expected.m
new file mode 100644
index 0000000..139597f
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/test/expected.m
@@ -0,0 +1,2 @@
+
+
diff --git a/SD-VBS/benchmarks/tracking/data/test/tracking b/SD-VBS/benchmarks/tracking/data/test/tracking
new file mode 100755
index 0000000..665fa11
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/test/tracking
diff --git a/SD-VBS/benchmarks/tracking/data/vga/1.bmp b/SD-VBS/benchmarks/tracking/data/vga/1.bmp
new file mode 100644
index 0000000..9695b0c
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/vga/1.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/vga/2.bmp b/SD-VBS/benchmarks/tracking/data/vga/2.bmp
new file mode 100644
index 0000000..937d03a
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/vga/2.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/vga/3.bmp b/SD-VBS/benchmarks/tracking/data/vga/3.bmp
new file mode 100644
index 0000000..faedea3
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/vga/3.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/vga/4.bmp b/SD-VBS/benchmarks/tracking/data/vga/4.bmp
new file mode 100644
index 0000000..2be82b8
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/vga/4.bmp
diff --git a/SD-VBS/benchmarks/tracking/data/vga/Makefile b/SD-VBS/benchmarks/tracking/data/vga/Makefile
new file mode 100644
index 0000000..e3fa1c2
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/vga/Makefile
@@ -0,0 +1,7 @@
+INPUT=vga
+include ../../../../common/makefiles/Makefile.include
+
+BMARK=tracking
+include $(MAKEFILE_COMMON_DIR)/Makefile.common
+
+
diff --git a/SD-VBS/benchmarks/tracking/data/vga/expected.m b/SD-VBS/benchmarks/tracking/data/vga/expected.m
new file mode 100644
index 0000000..05d987c
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/vga/expected.m
@@ -0,0 +1,2 @@
+470.825057      292.917830      182.675337      492.818305      276.157171      504.514201      
+216.367613      229.865854      255.912628      150.704991      276.525215      149.690554      
diff --git a/SD-VBS/benchmarks/tracking/data/vga/tracking b/SD-VBS/benchmarks/tracking/data/vga/tracking
new file mode 100755
index 0000000..bb2e3b9
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/data/vga/tracking
diff --git a/SD-VBS/benchmarks/tracking/src/c/calcAreaSum.c b/SD-VBS/benchmarks/tracking/src/c/calcAreaSum.c
new file mode 100644
index 0000000..40f03dc
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/c/calcAreaSum.c
@@ -0,0 +1,81 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "tracking.h"
+
+/** Compute the sum of pixels over pixel neighborhood.
+    Neighborhood = winSize*winSize 
+    This will be useful when we compute the displacement
+    of the neighborhood across frames instead of tracking each pixel.
+
+    Input:  src Image
+            # rows, cols, size of window
+    Output: windowed-sum image, ret.
+
+    Example:
+    
+    winSize = 4, cols = 8, rows = 16
+    nave_half = 2, nave = 4
+    Say, the first row of the image is:
+                3 8 6 2 4 8 9 5
+    a1 =    0 0 3 8 6 2 4 8 9 5 0 0 (append nave_half zeros to left and right border)
+    asum =  (sum the first nave # pixels - 0 0 3 8 ) = 11
+    ret(0,0) =  11
+    For ret(0,1), we need to move the window to the right by one pixel and subtract
+    from a1sum the leftmost pixel. So, we add value 6 and subtract value at a1(0,0), = 0 here.
+    ret(0,1) = 17 = a1sum
+    For ret(0,2), a1sum - a1(0,1) + a1(2+nave) = 17 - 0 + 2 = 19 = a1sum
+    For ret(0,3), a1sum - a1(0,2) + a1(3+nave) = 19 - 3 + 4 = 20 = a1sum
+
+    We proceed this way for all the rows and then perform summantion across all cols.
+**/
+F2D* calcAreaSum(F2D* src, int cols, int rows, int winSize)
+{
+    int nave, nave_half, i, j, k;
+    F2D *ret, *a1;
+    float a1sum;
+    
+    nave = winSize;
+    nave_half = floor((nave+1)/2);
+
+    ret = fMallocHandle(rows, cols);
+    a1 = fSetArray(1, cols+nave,0);
+
+    for(i=0; i<rows; i++)
+    {
+        for(j=0; j<cols; j++) {
+            asubsref(a1,j+nave_half) = subsref(src,i,j);
+                }
+        a1sum = 0;
+        for(k=0; k<nave; k++) {
+            a1sum += asubsref(a1,k);
+                }
+        for(j=0; j<cols; j++)
+        {
+            subsref(ret,i,j) = a1sum;
+            a1sum += asubsref(a1,j+nave) - asubsref(a1,j);
+        }
+    }
+    fFreeHandle(a1);
+
+    a1 = fSetArray(1, rows+nave,0);
+    for(i=0; i<cols; i++)
+    {
+        for(j=0; j<rows; j++) {
+            asubsref(a1,j+nave_half) = subsref(ret,j,i);
+                }
+        a1sum = 0;
+        for(k=0; k<nave; k++) {
+            a1sum += asubsref(a1,k);
+                }
+        for(j=0; j<rows; j++)
+        {
+            subsref(ret,j,i) = a1sum;
+            a1sum += asubsref(a1,j+nave) - asubsref(a1,j);
+        }
+    }
+    fFreeHandle(a1);
+
+    return ret; 
+}
diff --git a/SD-VBS/benchmarks/tracking/src/c/calcGoodFeature.c b/SD-VBS/benchmarks/tracking/src/c/calcGoodFeature.c
new file mode 100644
index 0000000..0ef1862
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/c/calcGoodFeature.c
@@ -0,0 +1,78 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "tracking.h"
+
+/** Computes lambda matrix, strength at each pixel
+    
+    det = determinant( [ IverticalEdgeSq IhorzVertEdge; IhorzVertEdge IhorizontalEdgeSq] ) ;
+    tr = IverticalEdgeSq + IhorizontalEdgeSq;
+    lamdba = det/tr;
+
+    Lambda is the measure of the strength of pixel
+    neighborhood. By strength we mean the amount of 
+    edge information it has, which translates to
+    sharp features in the image.
+
+    Input:  Edge images - vertical and horizontal
+            Window size (neighborhood size)
+    Output: Lambda, strength of pixel neighborhood
+
+    Given the edge images, we compute strength based
+    on how strong the edges are within each neighborhood.
+
+**/
+
+F2D* calcGoodFeature(F2D* verticalEdgeImage, F2D* horizontalEdgeImage, int cols, int rows, int winSize)
+{
+    int i, j, k, ind;
+    F2D *verticalEdgeSq, *horizontalEdgeSq, *horzVertEdge;
+    F2D *tr, *det, *lambda;
+    F2D *cummulative_verticalEdgeSq, *cummulative_horzVertEdge, *cummulative_horizontalEdgeSq;
+
+    verticalEdgeSq = fMallocHandle(rows, cols);
+    horzVertEdge = fMallocHandle(rows, cols);
+    horizontalEdgeSq = fMallocHandle(rows, cols);
+    
+    for( i=0; i<rows; i++)
+    {
+        for( j=0; j<cols; j++)
+        {
+            subsref(verticalEdgeSq,i,j) = subsref(verticalEdgeImage,i,j) * subsref(verticalEdgeImage,i,j);
+            subsref(horzVertEdge,i,j) = subsref(verticalEdgeImage,i,j) * subsref(horizontalEdgeImage,i,j);
+            subsref(horizontalEdgeSq,i,j) = subsref(horizontalEdgeImage,i,j) * subsref(horizontalEdgeImage,i,j);
+        }
+    }
+    
+    cummulative_verticalEdgeSq = calcAreaSum(verticalEdgeSq, cols, rows, winSize); 
+    cummulative_horzVertEdge = calcAreaSum(horzVertEdge, cols, rows, winSize);
+    cummulative_horizontalEdgeSq = calcAreaSum(horizontalEdgeSq, cols, rows, winSize);    
+     
+    tr = fMallocHandle(rows, cols);
+    det = fMallocHandle(rows, cols);
+    lambda = fMallocHandle(rows, cols);
+    
+    for( i=0; i<rows; i++)
+    {
+        for( j=0; j<cols; j++)
+        {
+            subsref(tr,i,j) = subsref(cummulative_verticalEdgeSq,i,j) + subsref(cummulative_horizontalEdgeSq,i,j);
+            subsref(det,i,j) = subsref(cummulative_verticalEdgeSq,i,j) * subsref(cummulative_horizontalEdgeSq,i,j) - subsref(cummulative_horzVertEdge,i,j) * subsref(cummulative_horzVertEdge,i,j);
+            subsref(lambda,i,j) = ( subsref(det,i,j) / (subsref(tr,i,j)+0.00001) ) ;
+        }
+    }
+   
+    fFreeHandle(verticalEdgeSq);
+    fFreeHandle(horzVertEdge);
+    fFreeHandle(horizontalEdgeSq);
+
+    fFreeHandle(cummulative_verticalEdgeSq);
+    fFreeHandle(cummulative_horzVertEdge);
+    fFreeHandle(cummulative_horizontalEdgeSq);
+    
+    fFreeHandle(tr);
+    fFreeHandle(det);
+     
+    return lambda;
+}
diff --git a/SD-VBS/benchmarks/tracking/src/c/calcPyrLKTrack.c b/SD-VBS/benchmarks/tracking/src/c/calcPyrLKTrack.c
new file mode 100644
index 0000000..3718673
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/c/calcPyrLKTrack.c
@@ -0,0 +1,179 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "tracking.h"
+
+/** calcPyrLKTrack tries to find the displacement (translation in x and y) of features computed in the previous frame.
+    To compute the displacement, we interpolate the existing feature position around the pixel neighborhood.
+    For better results, we perform interpolatations across all pyramid levels.
+
+    Input:  Previous frame blurred images, vertical and horizontal
+            Current frame edge images, vertical and horizontal
+            Current frame blurred images, for level 0 and 1
+            Number of features from previous frame
+            Window size
+            Accuracy
+            Number of iterations to compute motion vector
+            Features from the previous frame
+            currentFrameFeatures, Populate the current frame features' displacements
+    Output: Number of valid features
+
+**/
+
+I2D* calcPyrLKTrack(F2D* previousImageBlur_level1, F2D* previousImageBlur_level2, F2D* vertEdge_level1, F2D* vertEdge_level2, F2D* horzEdge_level1, F2D* horzEdge_level2, F2D* currentImageBlur_level1, F2D* currentImageBlur_level2, F2D* previousFrameFeatures, int nFeatures, int winSize, float accuracy, int max_iter, F2D* currentFrameFeatures)
+{
+    int idx, level, pLevel, i, j, k, winSizeSq;
+    I2D *valid;
+    F2D *rate, *iPatch, *jPatch, *iDxPatch;
+    F2D *iDyPatch;
+    float tr, x, y, dX, dY, c_xx, c_yy, c_xy;
+    int imgSize_1, imgSize_2;
+    float mX, mY, dIt, eX, eY, c_det;
+    I2D *imgDims;
+
+    imgDims = iMallocHandle(2, 2);
+    subsref(imgDims,0,0) = previousImageBlur_level1->height;
+    subsref(imgDims,0,1) = previousImageBlur_level1->width;
+    subsref(imgDims,1,0) = previousImageBlur_level2->height;
+    subsref(imgDims,1,1) = previousImageBlur_level2->width;
+
+    pLevel = 2;
+    rate = fMallocHandle(1, 6);
+
+    asubsref(rate,0) = 1;
+    asubsref(rate,1) = 0.5;
+    asubsref(rate,2) = 0.25;
+    asubsref(rate,3) = 0.125;
+    asubsref(rate,4) = 0.0625;
+    asubsref(rate,5) = 0.03125;
+    
+    winSizeSq = 4*winSize*winSize;
+    valid = iSetArray(1,nFeatures, 1);
+
+    /** For each feature passed from previous frame, compute the dx and dy, the displacements **/
+    for(i=0; i<nFeatures; i++)
+    {
+        dX = 0;
+        dY = 0;
+
+        /** Compute the x and y co-ordinate values at "pLevel" **/
+        x = subsref(previousFrameFeatures,0,i) * asubsref(rate,pLevel);
+        y = subsref(previousFrameFeatures,1,i) * asubsref(rate,pLevel);
+        c_det = 0;
+
+        /** For each pyramid level, try to find correspondence.
+            We look for the correspondence in a given window size
+            , (winSize x winSize) neighborhood **/
+        for(level = pLevel-1; level>=0; level--)
+        {
+            x = x+x;
+            y = y+y;
+            dX = dX + dX;
+            dY = dY + dY;
+            imgSize_1 = subsref(imgDims,level,0);
+            imgSize_2 = subsref(imgDims,level,1);
+
+            c_xx = 0;
+            c_xy = 0;
+            c_yy = 0;
+        
+            if((x-winSize)<0 || (y-winSize)<0 || (y+winSize+1)>=imgSize_1 || (x+winSize+1)>=imgSize_2)
+            {
+                asubsref(valid,i) = 0;
+                break;
+            }
+
+            /** Perform interpolation. Use co-ord from previous
+                frame and use the images from current frame **/
+
+            if(level ==0)
+            {
+                iPatch = getInterpolatePatch(previousImageBlur_level1, imgSize_2, x, y, winSize);
+                iDxPatch = getInterpolatePatch(vertEdge_level1, imgSize_2, x, y, winSize);
+                iDyPatch = getInterpolatePatch(horzEdge_level1, imgSize_2, x, y, winSize);
+            }
+            if(level ==1)
+            {
+                iPatch = getInterpolatePatch(previousImageBlur_level2, imgSize_2, x, y, winSize);
+                iDxPatch = getInterpolatePatch(vertEdge_level2, imgSize_2, x, y, winSize);
+                iDyPatch = getInterpolatePatch(horzEdge_level2, imgSize_2, x, y, winSize);
+            }
+
+            /** Compute feature strength in similar way as calcGoodFeature **/
+            for(idx=0; idx<winSizeSq; idx++)
+            {
+                c_xx += asubsref(iDxPatch,idx) * asubsref(iDxPatch,idx);
+                c_xy += asubsref(iDxPatch,idx) * asubsref(iDyPatch,idx);
+                c_yy += asubsref(iDyPatch,idx) * asubsref(iDyPatch,idx);
+            }
+            
+            c_det = (c_xx * c_yy -c_xy * c_xy);
+            tr = c_xx + c_yy;
+
+            if((c_det/(tr+0.00001)) < accuracy)
+            {
+                asubsref(valid,i) = 0;
+                fFreeHandle(iPatch);
+                fFreeHandle(iDxPatch);
+                fFreeHandle(iDyPatch);
+                break;
+            }
+            c_det = 1/c_det;
+
+            /** We compute dX and dY using previous frame and current
+                frame images. For this, the strength is computed at each
+                pixel in the new image.  **/
+            for(k=0; k<max_iter; k++)
+            {
+                if( (x+dX-winSize)<0 || (y+dY-winSize)<0 || (y+dY+winSize+1)>=imgSize_1 || (x+dX+winSize+1)>=imgSize_2)
+                {
+                    asubsref(valid,i) = 0;
+                    break;
+                }
+                
+                if(level == 0)
+                    jPatch = getInterpolatePatch(currentImageBlur_level1, imgSize_2, x+dX, y+dY, winSize);
+                if(level == 1)
+                    jPatch = getInterpolatePatch(currentImageBlur_level2, imgSize_2, x+dX, y+dY, winSize);
+                
+                eX = 0;
+                eY = 0;
+                for(idx=0; idx<winSizeSq; idx++)
+                {
+                    dIt = asubsref(iPatch,idx) - asubsref(jPatch,idx);
+                    eX += dIt * asubsref(iDxPatch,idx);
+                    eY += dIt * asubsref(iDyPatch,idx);
+                }
+                
+                mX = c_det * (eX * c_yy - eY * c_xy);
+                mY = c_det * (-eX * c_xy + eY * c_xx);
+                dX = dX + mX;
+                dY = dY + mY;
+            
+                if( (mX*mX+mY*mY) < accuracy)
+                {
+                    fFreeHandle(jPatch);
+                    break;
+                }
+                
+                fFreeHandle(jPatch);
+            }
+
+            fFreeHandle(iPatch);
+            fFreeHandle(iDxPatch);
+            fFreeHandle(iDyPatch);
+        }
+
+        subsref(currentFrameFeatures,0,i) = subsref(previousFrameFeatures,0,i) + dX;
+        subsref(currentFrameFeatures,1,i) = subsref(previousFrameFeatures,1,i) + dY;
+        
+    }
+
+    fFreeHandle(rate);
+    iFreeHandle(imgDims);
+    return valid;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/tracking/src/c/fillFeatures.c b/SD-VBS/benchmarks/tracking/src/c/fillFeatures.c
new file mode 100644
index 0000000..42de169
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/c/fillFeatures.c
@@ -0,0 +1,67 @@
+/********************************
+
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "tracking.h"
+
+/** Find the position and values of the top N_FEA features 
+        from the lambda matrix **/
+
+F2D* fillFeatures(F2D* lambda, int N_FEA, int win)
+{
+    int i, j, k, l;
+    int rows = lambda->height;
+    int cols = lambda->width;
+    F2D* features;
+
+        features = fSetArray(3, N_FEA, 0);
+
+        /** init array **/
+    for(i=0; i<N_FEA; i++)
+    {
+        subsref(features, 0, i) = -1.0;
+        subsref(features, 1, i) = -1.0;
+        subsref(features, 2, i) = 0.0;
+    }
+    
+
+        /** 
+                Find top N_FEA values and store them in 
+        features array along with row and col information 
+                It should be possible to make this algorithm better
+                if we use a pointer-based data structure,
+                but have not implemented due to MATLAB compatibility
+        **/ 
+
+        for (i=win; i<rows-win; i++)
+        {
+                for (j=win; j<cols-win; j++)
+                {
+            float currLambdaVal = subsref(lambda,i,j);
+                        if (subsref(features, 2, N_FEA-1) > currLambdaVal)
+                                continue;
+                        
+                        for (k=0; k<N_FEA; k++) 
+                        {
+                                if (subsref(features, 2, k) < currLambdaVal) 
+                                {
+                                        /** shift one slot **/
+                                        for (l=N_FEA-1; l>k; l--)
+                                        {
+                                                subsref(features, 0, l) = subsref(features, 0, l-1);
+                                                subsref(features, 1, l) = subsref(features, 1, l-1);
+                                                subsref(features, 2, l) = subsref(features, 2, l-1);
+                                        }       
+                                        
+                                subsref(features, 0, k) = j * 1.0;
+                                subsref(features, 1, k) = i * 1.0;
+                                subsref(features, 2, k) = currLambdaVal;
+                                        break;
+                                }
+                        }
+                }
+        }
+
+    return features;
+}
diff --git a/SD-VBS/benchmarks/tracking/src/c/getANMS.c b/SD-VBS/benchmarks/tracking/src/c/getANMS.c
new file mode 100644
index 0000000..7ecce8b
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/c/getANMS.c
@@ -0,0 +1,156 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "tracking.h"
+
+/** ANMS - Adaptive Non-Maximal Suppression
+    This function takes features as input and suppresses those which
+    are close to each other (within the SUPPRESSION_RADIUS) and have
+    similar feature strength
+**/
+F2D *getANMS (F2D *points, float r)
+{
+    float MAX_LIMIT = 100000;
+    F2D *suppressR;
+    float C_ROBUST = 1.0;
+    F2D *srtdPnts;
+    int n;
+    I2D *srtdVIdx, *supId;
+    float t, t1, r_sq;
+    F2D *tempF, *srtdV, *interestPnts;
+    int i, j, validCount, cnt, end, k;
+    int iter, rows, cols;
+    F2D *temp;
+    int supIdPtr = 0;
+    
+    /** Concatenate x,y,v to form points matrix **/
+    r_sq = r * r;
+    n = points->height;
+
+    srtdVIdx = iMallocHandle(points->height, 1);
+    for (i = 0; i < srtdVIdx->height; i++) {
+        asubsref(srtdVIdx,i) = i;
+        }
+    srtdPnts = fMallocHandle (srtdVIdx->height, points->width);
+    for (i = 0; i < srtdVIdx->height; i++) {
+        for(j=0; j<points->width; j++) {
+            subsref(srtdPnts,i,j) = subsref(points, asubsref(srtdVIdx,i), j);
+                }
+        }
+    temp = fSetArray (1, 3, 0);
+    suppressR = fSetArray(n, 1, MAX_LIMIT);
+    validCount = n;
+    iter = 0;
+    
+    /** Allocate supId for #validCount and fill the values of
+        supId with the indices where suppressR>r_sq **/
+    k = 0;
+    supId = iMallocHandle(validCount, 1);
+    for (i = 0; i < (suppressR->height*suppressR->width); i++)
+    {
+        if ( asubsref(suppressR,i) > r_sq)
+        {
+            asubsref(supId,k++) = i;
+        }
+    }
+         
+    /** While number of features not-inspected is >0,  **/
+    while (validCount > 0)
+    {
+        F2D *tempp, *temps;
+        
+        /** Inspect the strongest feature point in srtdPnts
+            The index of that feature is in supId and the
+            index values in supId are arranged in descending order **/
+        asubsref(temp,0) = subsref(srtdPnts, asubsref(supId,0), 0);
+        asubsref(temp,1) = subsref(srtdPnts, asubsref(supId,0), 1);
+        asubsref(temp,2) = subsref(srtdPnts, asubsref(supId,0), 2);
+       
+        /** Stacking up the interestPnts matrix with top features
+            post suppression **/
+        if(iter == 0)
+            interestPnts = fDeepCopy(temp);
+        else
+        {
+            tempp = fDeepCopy(interestPnts);
+            fFreeHandle(interestPnts); 
+            interestPnts = ffVertcat(tempp, temp);
+            fFreeHandle(tempp);
+        }
+        iter++;
+ 
+        tempp = fDeepCopy(srtdPnts);
+        temps = fDeepCopy(suppressR);
+
+        fFreeHandle(srtdPnts);
+        fFreeHandle(suppressR);
+
+        /** Remove the feature that has been added to interestPnts **/
+        srtdPnts = fMallocHandle(supId->height-1, 3);
+        suppressR = fMallocHandle(supId->height-1, 1);
+        k=0;
+
+        for(i=1; i<(supId->height); i++)    /** Filling srtdPnts after removing the feature that was added to interestPnts**/
+        {
+            subsref(srtdPnts,(i-1),0) = subsref(tempp, asubsref(supId,i) ,0);
+            subsref(srtdPnts,(i-1),1) = subsref(tempp, asubsref(supId,i) ,1);
+            subsref(srtdPnts,(i-1),2) = subsref(tempp, asubsref(supId,i) ,2);
+            subsref(suppressR,(i-1),0) = subsref(temps, asubsref(supId,i) ,0);
+        }
+         
+        fFreeHandle(tempp);
+        fFreeHandle(temps);
+        rows = interestPnts->height-1;
+        cols = interestPnts->width;
+
+        /** For each feature, find how robust it is compared to the one in interestPnts **/
+        for (i = 0; i < srtdPnts->height; i++)
+            {
+            t = 0;
+                t1 = 0;
+
+                if ((C_ROBUST * subsref(interestPnts,rows,2)) >= subsref(srtdPnts, i,2))
+                {
+                        t = subsref(srtdPnts, i,0) - subsref(interestPnts,rows,0);
+                        t1 = subsref(srtdPnts, i,1) - subsref(interestPnts,rows,1);
+                        t = t * t + t1 * t1;
+                t1 = 0;
+            }
+
+                if ((C_ROBUST * subsref(interestPnts,rows,2)) < subsref(srtdPnts, i,2))
+                t1 = 1 * MAX_LIMIT;
+
+                if ( asubsref(suppressR, i) > (t + t1))
+            {
+                    asubsref(suppressR, i) = t + t1;
+            }  
+        }
+        
+        /** Inspect the new suppressR to find how many valid features left **/
+        validCount=0;
+        for (i = 0; i < suppressR->height; i++) {
+                if ( asubsref(suppressR,i) > r_sq) {
+                validCount++;
+                        } 
+                }
+        k = 0;
+        iFreeHandle(supId);
+        /** Allocate supId for #validCount and fill the values of
+        supId with the indices where suppressR>r_sq **/
+        supId = iMallocHandle(validCount, 1);
+        for (i = 0; i < suppressR->height*suppressR->width; i++) {
+            if ( asubsref(suppressR,i) > r_sq)
+                asubsref(supId,k++) = i;
+                }
+    }
+    
+    iFreeHandle(supId);
+    iFreeHandle(srtdVIdx);
+    fFreeHandle(srtdPnts);
+    fFreeHandle(temp);
+    fFreeHandle(suppressR);
+
+    return interestPnts;
+}
+
diff --git a/SD-VBS/benchmarks/tracking/src/c/getInterpolatePatch.c b/SD-VBS/benchmarks/tracking/src/c/getInterpolatePatch.c
new file mode 100644
index 0000000..99e95f9
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/c/getInterpolatePatch.c
@@ -0,0 +1,43 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "tracking.h"
+
+/** Perform simple interpolation around  2*winSize*2*winSize neighbourhood **/
+F2D* getInterpolatePatch(F2D* src, int cols, float centerX, float centerY, int winSize)
+{
+    F2D *dst;
+    float a, b, a11, a12, a21, a22;
+    int i, j, k, srcIdx, dstIdx;
+    int srcIdxx, dstIdxx;
+
+    a = centerX - floor(centerX);
+    b = centerY - floor(centerY);
+
+    a11 = (1-a)*(1-b);
+    a12 = a*(1-b);
+    a21 = (1-a)*b;
+    a22 = a*b;
+
+    dst = fSetArray(1,2*winSize*2*winSize, 0);
+
+
+    for(i=-winSize; i<winSize; i++)
+    {
+        srcIdxx = floor(centerY) + i;
+        dstIdxx = i+winSize;
+
+        for(j=-winSize; j<(winSize); j++)
+        {
+            srcIdx = srcIdxx * cols + floor(centerX) + j;
+            dstIdx = dstIdxx * 2 * winSize + j + winSize;
+            asubsref(dst,dstIdx) = asubsref(src,srcIdx)*a11 + asubsref(src,srcIdx+1)*a12 + asubsref(src,srcIdx+cols)*a21 + asubsref(src,srcIdx+1+cols)*a22;
+        }
+    }
+
+    return dst;
+}
+
+
+
diff --git a/SD-VBS/benchmarks/tracking/src/c/script_tracking.c b/SD-VBS/benchmarks/tracking/src/c/script_tracking.c
new file mode 100644
index 0000000..bb48ace
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/c/script_tracking.c
@@ -0,0 +1,263 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#include "tracking.h"
+#include <malloc.h>
+#include "extra.h"
+#define TRACKING_MEM 1<<29
+
+int main(int argc, char* argv[])
+{
+    SET_UP
+    mallopt(M_TOP_PAD, TRACKING_MEM);
+    mallopt(M_MMAP_MAX, 0);
+    int i, j, k, N_FEA, WINSZ, LK_ITER, rows, cols;
+    int endR, endC;
+    F2D *blurredImage, *previousFrameBlurred_level1, *previousFrameBlurred_level2, *blurred_level1, *blurred_level2;
+    F2D *verticalEdgeImage, *horizontalEdgeImage, *verticalEdge_level1, *verticalEdge_level2, *horizontalEdge_level1, *horizontalEdge_level2, *interestPnt;
+    F2D *lambda, *lambdaTemp, *features;
+    I2D *Ic, *status;
+    float SUPPRESION_RADIUS;
+    F2D *newpoints;
+
+    int numFind, m, n;
+    F2D *np_temp;
+
+    char im1[100];
+    int counter=2;
+    float accuracy = 0.03;
+    int count;
+    
+
+    N_FEA = 1600;
+    WINSZ = 4;
+    SUPPRESION_RADIUS = 10.0;
+    LK_ITER = 20;
+
+    #ifdef test
+        WINSZ = 2;
+        N_FEA = 100;
+        LK_ITER = 2;
+        counter = 2;
+        accuracy = 0.1;
+    #endif
+    #ifdef sim_fast
+        WINSZ = 2;
+        N_FEA = 100;
+        LK_ITER = 2;
+        counter = 4;
+    #endif
+    #ifdef sim
+        WINSZ = 2;
+        N_FEA = 200;
+        LK_ITER = 2;
+        counter = 4;
+    #endif
+    #ifdef sqcif
+        WINSZ = 8;
+        N_FEA = 500;
+        LK_ITER = 15;
+        counter = 2;
+    #endif
+    #ifdef qcif
+        WINSZ = 12;
+        N_FEA = 400;
+        LK_ITER = 15;
+        counter = 4;
+    #endif
+    #ifdef cif
+        WINSZ = 20;
+        N_FEA = 500;
+        LK_ITER = 20;
+        counter = 4;
+    #endif
+    #ifdef vga
+        WINSZ = 32;
+        N_FEA = 400;
+        LK_ITER = 20;
+        counter = 4;
+    #endif
+    #ifdef wuxga
+        WINSZ = 64;
+        N_FEA = 500;
+        LK_ITER = 20;
+        counter = 4;
+    #endif
+    #ifdef fullhd
+        WINSZ = 48;
+        N_FEA = 500;
+        LK_ITER = 20;
+        counter = 4;
+    #endif
+
+    I2D* images[counter];
+    /** Read input image **/
+    for(count=1; count<=counter; count++)
+    {
+        /** Read image **/
+        printf("Input image %d: ", count);
+        scanf("%s", im1);
+        images[count - 1] = readImage(im1);
+        if(count == 1) Ic = readImage(im1);
+    }
+
+
+    rows = Ic->height;
+    cols = Ic->width;
+    
+    printf("start\n");   
+    for_each_job{
+        
+        /** IMAGE PRE-PROCESSING **/
+    
+        /** Blur the image to remove noise - weighted avergae filter **/
+        blurredImage = imageBlur(Ic);
+    
+        /** Scale down the image to build Image Pyramid. We find features across all scales of the image **/
+        blurred_level1 = blurredImage;                   /** Scale 0 **/
+        blurred_level2 = imageResize(blurredImage);      /** Scale 1 **/
+    
+    
+        /** Edge Images - From pre-processed images, build gradient images, both horizontal and vertical **/
+        verticalEdgeImage = calcSobel_dX(blurredImage);
+        horizontalEdgeImage = calcSobel_dY(blurredImage);
+    
+        /** Edge images are used for feature detection. So, using the verticalEdgeImage and horizontalEdgeImage images, we compute feature strength
+            across all pixels. Lambda matrix is the feature strength matrix returned by calcGoodFeature **/
+        
+        lambda = calcGoodFeature(verticalEdgeImage, horizontalEdgeImage, verticalEdgeImage->width, verticalEdgeImage->height, WINSZ);
+        endR = lambda->height;
+        endC = lambda->width;
+        lambdaTemp = fReshape(lambda, endR*endC, 1);
+    
+        /** We sort the lambda matrix based on the strengths **/
+        /** Fill features matrix with top N_FEA features **/
+        fFreeHandle(lambdaTemp);
+        lambdaTemp = fillFeatures(lambda, N_FEA, WINSZ);
+        features = fTranspose(lambdaTemp);
+        
+        /** Suppress features that have approximately similar strength and belong to close neighborhood **/
+        interestPnt = getANMS(features, SUPPRESION_RADIUS);
+        
+        /** Refill interestPnt in features matrix **/
+        fFreeHandle(features);
+        features = fSetArray(2, interestPnt->height, 0);
+        for(i=0; i<2; i++) {
+            for(j=0; j<interestPnt->height; j++) {
+                subsref(features,i,j) = subsref(interestPnt,j,i); 
+                }
+        } 
+         
+    
+        fFreeHandle(verticalEdgeImage);
+        fFreeHandle(horizontalEdgeImage);
+        fFreeHandle(interestPnt);
+        fFreeHandle(lambda);
+        fFreeHandle(lambdaTemp);
+        /** Until now, we processed base frame. The following for loop processes other frames **/
+        for(count=1; count<=counter; count++)
+        {
+            /** Read image **/
+            //sprintf(im1, "%s/%d.bmp", argv[1], count);
+            //Ic = readImage(im1);
+            I2D* Icc = images[count-1];
+            rows = Icc->height;
+            cols = Icc->width;
+            
+        
+            /** Blur image to remove noise **/
+            blurredImage = imageBlur(Icc);
+            previousFrameBlurred_level1 = fDeepCopy(blurred_level1);
+            previousFrameBlurred_level2 = fDeepCopy(blurred_level2);
+            
+            fFreeHandle(blurred_level1);
+            fFreeHandle(blurred_level2);
+        
+            /** Image pyramid **/
+            blurred_level1 = blurredImage;
+            blurred_level2 = imageResize(blurredImage);
+        
+            /** Gradient image computation, for all scales **/
+            verticalEdge_level1 = calcSobel_dX(blurred_level1);   
+            horizontalEdge_level1 = calcSobel_dY(blurred_level1); 
+            
+            verticalEdge_level2 = calcSobel_dX(blurred_level2); 
+            horizontalEdge_level2 = calcSobel_dY(blurred_level2);
+            
+            newpoints = fSetArray(2, features->width, 0);
+                
+            /** Based on features computed in the previous frame, find correspondence in the current frame. "status" returns the index of corresponding features **/
+            status = calcPyrLKTrack(previousFrameBlurred_level1, previousFrameBlurred_level2, verticalEdge_level1, verticalEdge_level2, horizontalEdge_level1, horizontalEdge_level2, blurred_level1, blurred_level2, features, features->width, WINSZ, accuracy, LK_ITER, newpoints);
+            fFreeHandle(verticalEdge_level1);
+            fFreeHandle(verticalEdge_level2);
+            fFreeHandle(horizontalEdge_level1);
+            fFreeHandle(horizontalEdge_level2);
+            fFreeHandle(previousFrameBlurred_level1);
+            fFreeHandle(previousFrameBlurred_level2);
+            //printf("height = %d, width = %d, numFind = %d\n", newpoints->height, newpoints->width);
+            
+            /** Populate newpoints with features that had correspondence with previous frame features **/
+            np_temp = fDeepCopy(newpoints);
+            if(status->width > 0 )
+            {
+                k = 0;
+                numFind=0;
+                for(i=0; i<status->width; i++)
+                {
+                    if( asubsref(status,i) == 1)
+                        numFind++;
+                }
+                fFreeHandle(newpoints);
+                newpoints = fSetArray(2, numFind, 0);
+        
+                for(i=0; i<status->width; i++)
+                {
+                    if( asubsref(status,i) == 1)
+                    {
+                        subsref(newpoints,0,k) = subsref(np_temp,0,i);
+                        subsref(newpoints,1,k++) = subsref(np_temp,1,i);
+                    }
+                }    
+            }    
+            
+            iFreeHandle(status);
+            fFreeHandle(np_temp);
+            fFreeHandle(features);
+        
+            /** Populate newpoints into features **/
+            features = fDeepCopy(newpoints);
+            fFreeHandle(newpoints);
+        }
+    }
+    printf("end..\n");
+#ifdef CHECK   
+    /* Self checking */
+    {
+        int ret=0;
+        float tol = 2.0;
+#ifdef GENERATE_OUTPUT
+        fWriteMatrix(features, argv[1]);
+#endif
+        ret = fSelfCheck(features, "expected_C.txt", tol); 
+        if (ret == -1)
+            printf("Error in Tracking Map\n");
+    }
+#endif
+    
+    fFreeHandle(blurred_level1);
+    fFreeHandle(blurred_level2);
+    fFreeHandle(features);
+
+    for(count=1; count<=counter; count++)
+    {
+        free(images[count - 1] );
+    }
+    iFreeHandle(Ic);
+    WRITE_TO_FILE
+    return 0;
+
+}
+
+
+
diff --git a/SD-VBS/benchmarks/tracking/src/c/tracking.h b/SD-VBS/benchmarks/tracking/src/c/tracking.h
new file mode 100644
index 0000000..24b8b2d
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/c/tracking.h
@@ -0,0 +1,20 @@
+/********************************
+Author: Sravanthi Kota Venkata
+********************************/
+
+#ifndef _SCRIPT_TRACK_
+#define _SCRIPT_TRACK_
+
+#include "sdvbs_common.h"
+
+F2D* calcAreaSum(F2D* src, int cols, int rows, int winSize);
+F2D* calcGoodFeature(F2D* dX, F2D* dY, int cols, int rows, int winSize);
+I2D* calcPyrLKTrack(F2D* ip1, F2D* ip2, F2D* idxp1, F2D* idxp2, F2D* idyp1, F2D* idyp2, F2D* jp1, F2D* jp2, F2D* fPnt, int nFeatures, int winSize, float accuracy, int maxIter, F2D* newPnt);
+F2D *getANMS (F2D *points, float r);
+F2D* getInterpolatePatch(F2D* src, int cols, float centerX, float centerY, int winSize);
+float polynomial(int d, F2D* a, F2D* b, int dim);
+I2D* sortInd(F2D* input, int dim);
+F2D* fillFeatures(F2D* lambda, int N_FEA, int win);
+
+#endif
+
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/Filtering.m b/SD-VBS/benchmarks/tracking/src/matlab/Filtering.m
new file mode 100755
index 0000000..d42ebb7
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/Filtering.m
@@ -0,0 +1,30 @@
+function imageOut = Filtering(imageIn, rows, cols, kernel, kernelSize)

+

+imageOut = zeros(rows, cols);%initalize output image to all zeros

+imageIn = double(imageIn);%convert to double to allow image arithmetic

+

+ intialCol = ((kernelSize+1)/2);

+ endCol = round(cols - ((kernelSize+1)/2));

+ halfKernel = (kernelSize-1)/2;

+ 

+ initialRow = ((kernelSize+1)/2);

+ endRow = (rows - ((kernelSize+1)/2));

+ 

+ %% Start 1-D filtering row-wise first.

+ 

+ for i=initialRow:endRow

+     for j=initialCol:endCol

+     imageOut(i,j) = sum(imageIn(i,j-halfKernel:j+halfKernel).*kernel)/sum(kernel);%actual filtering step

+     end

+ end

+ 

+ %% Start 1-D filtering col-wise first.

+ 

+% kernelT = kernel';

+% for i=initialRow:endRow

+%     for j=initialCol:endCol

+%     imageOut(i,j) = sum(imageOut(i-halfKernel:i+halfKernel,j).*kernelT)/sum(kernel);%kernel to be transposed for performing multiplcation

+%     end

+% end

+% 

+% %imshow(uint8(imageOut));

diff --git a/SD-VBS/benchmarks/tracking/src/matlab/calcAreaSum.m b/SD-VBS/benchmarks/tracking/src/matlab/calcAreaSum.m
new file mode 100755
index 0000000..f8dd3da
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/calcAreaSum.m
@@ -0,0 +1,48 @@
+%calcAreaSum:

+% sizeX = cols

+% sizeY = rows

+function ret = calcAreaSum(src, sizeX, sizeY, winSize, dataDir)

+

+src = double(src);

+nave = winSize;

+nave_half = floor((nave+1)/2);

+a1=zeros(1,sizeX+nave);

+    

+for i=1:sizeY

+        %pull out one row

+        for j=1:sizeX

+                a1(j+nave_half)=src(i,j);

+        end

+

+        a1sum=0;

+        %sum up values within a window

+        for k=1:nave

+                a1sum = a1sum+a1(k);

+        end

+

+        for j=1:sizeX

+                ret(i,j) = a1sum;

+                a1sum = a1sum + a1(j+nave) - a1(j);

+        end

+end

+

+a1=zeros(1,sizeY+nave);

+for i=1:sizeX

+

+        %pull out one col

+        for j=1:sizeY

+                a1(j+nave_half)=ret(j,i);

+        end

+

+        a1sum=0;

+        %sum up values within a window

+        for k=1:nave

+                a1sum = a1sum+a1(k);

+        end

+

+        for j=1:sizeY

+                ret(j,i) = a1sum;

+                a1sum = a1sum + a1(j+nave) - a1(j);

+        end

+end

+

diff --git a/SD-VBS/benchmarks/tracking/src/matlab/calcGoodFeature.m b/SD-VBS/benchmarks/tracking/src/matlab/calcGoodFeature.m
new file mode 100755
index 0000000..b83faa6
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/calcGoodFeature.m
@@ -0,0 +1,28 @@
+%calcGoodFeature:

+

+function [lambda, tr, det,c_xx, c_xy, c_yy] = calcGoodFeature(dX, dY, sizeX, sizeY, winSize, dataDir) 

+

+    for i=1:sizeY

+        for j=1:sizeX

+                xx(i,j)=dX(i,j)*dX(i,j);

+                xy(i,j)=dX(i,j)*dY(i,j);

+            yy(i,j)=dY(i,j)*dY(i,j);

+        end

+    end

+    

+        c_xx=calcAreaSum(xx, sizeX, sizeY, winSize,dataDir);

+    c_xy=calcAreaSum(xy, sizeX, sizeY, winSize,dataDir);

+        c_yy=calcAreaSum(yy, sizeX, sizeY, winSize,dataDir);

+ 

+        for i=1:sizeY

+        for j=1:sizeX

+                tr(i,j)= c_xx(i,j)+c_yy(i,j);

+                det(i,j)= c_xx(i,j)*c_yy(i,j)-c_xy(i,j)*c_xy(i,j);

+%             if( tr(i,j) == 0 )

+%                 lambda(i,j) = 0;

+%             else

+                lambda(i,j)=det(i,j)/(tr(i,j) + 0.00001);

+%            end

+        end

+    end

+ 

diff --git a/SD-VBS/benchmarks/tracking/src/matlab/calcPyrLKTrack.m b/SD-VBS/benchmarks/tracking/src/matlab/calcPyrLKTrack.m
new file mode 100755
index 0000000..c965c2b
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/calcPyrLKTrack.m
@@ -0,0 +1,108 @@
+function [newFPnt, valid] = calcPyrLKTrack(iP, iDxP, iDyP, jP, fPnt, nFeatures, winSize, accuracy_th, max_iter)
+        
+cellDims = size(iP);
+GOOD_FEATURE_LAMBDA_TH = accuracy_th;
+
+for i=1:(cellDims(1))
+    curImgDims = size(iP{i});
+        imgDims(i,1)= curImgDims(1);
+        imgDims(i,2)= curImgDims(2);
+
+end
+
+pLevel = cellDims(1);
+
+rate=[1, 0.5, 0.25, 0.125, 0.0625, 0.03125];
+winSizeSq=4*winSize*winSize;
+iPatch=cell(1, winSizeSq);
+jPatch=cell(1, winSizeSq);
+iDxPatch=cell(1,winSizeSq);
+iDyPatch=cell(1,winSizeSq);
+
+valid(1:nFeatures) = 1;
+newFPnt = zeros(2,nFeatures);
+
+for i=1:nFeatures
+
+    dX=0;
+    dY=0;
+
+%% x is rows here and y is cols
+    
+    x=fPnt(1,i)*rate(pLevel+1);                 %half size of real level
+    y=fPnt(2,i)*rate(pLevel+1);
+
+    for level=pLevel:-1:1
+
+        x = x+x;
+        y = y+y;
+        dX = dX+dX;
+        dY = dY+dY;
+        imgSize(1)=imgDims(level,1); %y,x               
+        imgSize(2)=imgDims(level,2); %y,x               
+
+        c_xx = 0;
+        c_xy = 0;
+        c_yy = 0;
+            
+        %when feature goes out to the boundary.
+
+        if ((x-winSize)<1 || (y-winSize)<1 || (y+winSize+1)>imgSize(1) || (x+winSize+1)>imgSize(2))
+            %winSize+1due to interpolation
+            %error or skip the level??
+            valid(i) = 0;
+            break;
+        end
+
+        
+        iPatch = getInterpolatePatch(iP{level}, imgSize(1), imgSize(2), x, y, winSize);
+        iDxPatch = getInterpolatePatch(iDxP{level}, imgSize(1), imgSize(2), x, y, winSize);
+        iDyPatch = getInterpolatePatch(iDyP{level}, imgSize(1), imgSize(2), x, y, winSize);
+
+        for idx=1:winSizeSq
+            c_xx = c_xx + iDxPatch(idx) * iDxPatch(idx);
+            c_xy = c_xy + iDxPatch(idx) * iDyPatch(idx);
+            c_yy = c_yy + iDyPatch(idx) * iDyPatch(idx);
+        end
+
+        c_det = c_xx * c_yy - c_xy * c_xy;
+        
+        if (c_det/(c_xx+c_yy+0.00001)) < GOOD_FEATURE_LAMBDA_TH
+            valid(i)=0;
+            break;
+        end
+
+        c_det=1/c_det;
+
+        for k=1:max_iter
+            if ((x+dX-winSize)<1 || (y+dY-winSize)<1 || (y+dY+winSize+1)>imgSize(1) || (x+dX+winSize+1)>imgSize(2))
+                %winSize+1due to interpolation
+                %error or skip the level??
+                valid(i)=0;
+                break;
+            end
+
+            jPatch = getInterpolatePatch(jP{level}, imgSize(1), imgSize(2), x+dX, y+dY, winSize);
+            eX = 0;
+            eY = 0;
+            for idx=1:winSizeSq
+                dIt = iPatch(idx) - jPatch(idx);
+                eX = eX + (dIt*iDxPatch(idx));
+                eY = eY + (dIt*iDyPatch(idx));
+            end
+
+            mX = c_det*(eX*c_yy-eY*c_xy);
+            mY = c_det*(-eX*c_xy+eY*c_xx);
+            dX = dX + mX;
+            dY = dY + mY;
+
+
+            if ((mX*mX+mY*mY)<accuracy_th)
+                break;
+            end
+        end
+    end
+    
+    newFPnt(1, i) = fPnt(1,i)+dX;
+    newFPnt(2, i) = fPnt(2,i)+dY;
+end
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/calcSobel.m b/SD-VBS/benchmarks/tracking/src/matlab/calcSobel.m
new file mode 100755
index 0000000..8617c25
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/calcSobel.m
@@ -0,0 +1,74 @@
+function [Dx, Dy] = calcSobel(imageIn)
+
+imsize = size(imageIn);
+rows = imsize(1);
+cols = imsize(2);
+
+Dx = zeros(rows, cols);     %initalize output image to all zeros
+Dy = zeros(rows, cols);     %initalize output image to all zeros
+imageIn = double(imageIn);  %convert to double to allow image arithmetic
+
+kernel_1 = [1 2 1];
+kernel_2 = [1 0 -1];
+kernelSize = 3;
+
+sum_kernel_1 = 4;
+sum_kernel_2 = 2;
+
+startCol = 2;           %((kernelSize+1)/2);
+endCol = cols - 1;      %round(cols - ((kernelSize+1)/2));
+halfKernel = 1;         %(kernelSize-1)/2;
+
+startRow = 2;           %((kernelSize+1)/2);
+endRow = rows - 1;      %(rows - ((kernelSize+1)/2));
+
+%imshow(uint8(imageIn));
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%% Calculate Gx (gradient in X-dir)
+%% Gx = ([1 2 1]') * ([1 0 -1] * imageIn)
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%% Start 1-D filtering row-wise first.
+
+tempOut = zeros(rows, cols);%initalize temp image to all zeros
+for i=startRow:endRow
+   for j=startCol:endCol
+       tempOut(i,j) = sum(imageIn(i,j-halfKernel:j+halfKernel).*kernel_2)/sum_kernel_2;%actual filtering step
+   end
+end
+
+% Start 1-D filtering col-wise first.
+
+for i=startRow:endRow
+   for j=startCol:endCol
+       Dx(i,j) = sum(tempOut(i-halfKernel:i+halfKernel,j).*kernel_1')/sum_kernel_1;%kernel to be transposed for performing multiplcation
+       Dx(i,j) = Dx(i,j);% + 128;
+   end
+end
+
+
+%imshow(uint8(Dx));
+
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%% Calculate Gy (gradient in Y-dir)
+%% Gy = ([1 0 -1]') * ([1 2 1] * imageIn)
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%% Start 1-D filtering row-wise first.
+
+for i=startRow:endRow
+    for j=startCol:endCol
+        tempOut(i,j) = sum(imageIn(i-halfKernel:i+halfKernel,j).*kernel_2')/sum_kernel_2;%kernel to be transposed for performing multiplcation
+    end
+end
+
+for i=startRow:endRow
+    for j=startCol:endCol
+        Dy(i,j) = sum(tempOut(i,j-halfKernel:j+halfKernel).*kernel_1)/sum_kernel_1;
+    end
+end
+
+
+%imshow(uint8(Dy));
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/getInterpolatePatch.m b/SD-VBS/benchmarks/tracking/src/matlab/getInterpolatePatch.m
new file mode 100755
index 0000000..d0a64d3
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/getInterpolatePatch.m
@@ -0,0 +1,22 @@
+function [dstImg] = getInterpolatePatch(srcImg,rows, cols,centerX,centerY,winSize)

+

+a=centerX-floor(centerX);

+b=centerY-floor(centerY);

+a11=(1-a)*(1-b);

+a12=a*(1-b);

+a21=(1-a)*b;

+a22=a*b;

+

+for i=-winSize:winSize-1

+        srcIdxx=floor(centerY)+i;

+        dstIdxx=i+winSize+1;

+        for j=-winSize:winSize-1

+                srcIdx = srcIdxx * cols + floor(centerX) + j;

+                dstIdx = dstIdxx*2*winSize+j+winSize+1;

+                dstImg(dstIdx)=srcImg(srcIdxx, floor(centerX)+j)*a11;

+        dstImg(dstIdx)= dstImg(dstIdx) + srcImg(srcIdxx, floor(centerX)+j+1)*a12;

+        dstImg(dstIdx)= dstImg(dstIdx) + srcImg(srcIdxx+1, floor(centerX)+j)*a21;

+        dstImg(dstIdx)= dstImg(dstIdx) + srcImg(srcIdxx+1, floor(centerX)+j+1)*a22;

+    end

+end

+

diff --git a/SD-VBS/benchmarks/tracking/src/matlab/getPyramid.m b/SD-VBS/benchmarks/tracking/src/matlab/getPyramid.m
new file mode 100755
index 0000000..845456a
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/getPyramid.m
@@ -0,0 +1,10 @@
+function pyr=getPyramid(img, level)
+kernel=[1/16,1/4,3/8,1/4,1/16];
+pyr=cell(level,1);
+pyr{1}=double(img);
+for i=2:level
+%    imgBlur=conv2(pyr{i-1}, kernel, 'same');
+%    imgBlur=conv2(imgBlur, kernel, 'same');
+%    pyr{i}=imgBlur(1:2:end, 1:2:end);
+    pyr{i}=calcResizedImgMex(pyr{i-1});
+end
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/imageBlur.m b/SD-VBS/benchmarks/tracking/src/matlab/imageBlur.m
new file mode 100755
index 0000000..fd6c199
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/imageBlur.m
@@ -0,0 +1,36 @@
+function imageOut = imageBlur(imageIn)

+

+imsize = size(imageIn);

+rows = imsize(1);

+cols = imsize(2);

+

+imageOut = zeros(rows, cols);%initalize output image to all zeros

+imageIn = double(imageIn);%convert to double to allow image arithmetic

+

+kernel = [1 4 6 4 1];

+kernelSize = 5;

+

+startCol = 3;       %((kernelSize+1)/2);

+endCol = cols - 2;  %round(cols - ((kernelSize+1)/2));

+halfKernel = 2;     %(kernelSize-1)/2;

+

+startRow = 3;       %((kernelSize+1)/2);

+endRow = rows - 2;  %(rows - ((kernelSize+1)/2));

+

+%% Start 1-D filtering row-wise first.

+

+tempOut = zeros(rows, cols);%initalize temp image to all zeros

+for i=startRow:endRow

+    for j=startCol:endCol

+        tempOut(i,j) = sum(imageIn(i,j-halfKernel:j+halfKernel).*kernel)/sum(kernel);%actual filtering step

+    end

+end

+

+%% Start 1-D filtering col-wise first.

+

+for i=startRow:endRow

+    for j=startCol:endCol

+    imageOut(i,j) = sum(tempOut(i-halfKernel:i+halfKernel,j).*kernel')/sum(kernel);%kernel to be transposed for performing multiplcation

+    end

+end

+

diff --git a/SD-VBS/benchmarks/tracking/src/matlab/imageResize.m b/SD-VBS/benchmarks/tracking/src/matlab/imageResize.m
new file mode 100755
index 0000000..e5fa7b8
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/imageResize.m
@@ -0,0 +1,50 @@
+function [imageOut] = imageResize(imageIn)
+
+ imageIn = double(imageIn);
+ imsize = size(imageIn);
+ rows = imsize(1);
+ cols = imsize(2);
+ 
+ %% level 1 is the base image.
+ 
+ outputRows = floor((rows+1)/2);
+ outputCols = floor((cols+1)/2);
+ 
+ kernel = [1,4,6,4,1];
+ kernelSize = 5;
+ 
+ temp = zeros(rows, outputCols);%initalize output image to all zeros
+ imageOut = zeros(outputRows, outputCols);%initalize output image to all zeros
+ imageIn = double(imageIn);%convert to double to allow image arithmetic
+ 
+ initialCol = 3;        %((kernelSize+1)/2);
+ endCol = cols - 2;     %round(cols - ((kernelSize+1)/2));
+ halfKernel = 2;        %(kernelSize-1)/2;
+ 
+ initialRow = 3;        %((kernelSize+1)/2);
+ endRow = rows - 2;     %(rows - ((kernelSize+1)/2));
+
+ %% Start 1-D filtering row-wise first.
+ 
+ for i=initialRow:endRow
+     k = 1;
+     for j=initialCol:2:endCol
+         temp(i,k) = sum(imageIn(i,j-halfKernel:j+halfKernel).*kernel)/sum(kernel);%actual filtering step
+         k = k+1;
+     end
+ end
+ 
+ %imshow(uint8(temp));
+ 
+ %% Start 1-D filtering col-wise first.
+% 
+ kernelT = kernel';
+ j = 1;
+ for i=initialRow:2:endRow
+     for k=1:outputCols
+         imageOut(j,k) = sum(temp(i-halfKernel:i+halfKernel,k).*kernelT)/sum(kernel);%kernel to be transposed for performing multiplcation
+     end
+     j = j + 1;
+ end
+ 
+% %imshow(uint8(imageOut));
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/rgb2gray_f2_f3.m b/SD-VBS/benchmarks/tracking/src/matlab/rgb2gray_f2_f3.m
new file mode 100755
index 0000000..23397a3
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/rgb2gray_f2_f3.m
@@ -0,0 +1,16 @@
+%! _rgb2gray_f2_f3

+

+function grayImage = rgb2gray_f2_f3(colorImage)

+

+%0.2989 * R + 0.5870 * G + 0.1140 * B

+rows = size(colorImage, 1);

+cols = size(colorImage, 2);

+rgb = size(colorImage, 3);

+

+grayImage = zeros(rows, cols);

+for i = 1:rows

+    for j = 1:cols

+        grayImage(i,j) = 0.2989 * colorImage(i,j,1) + 0.5870 * colorImage(i,j,2) + 0.1140 * colorImage(i,j,3);

+    end

+end

+    
\ No newline at end of file
diff --git a/SD-VBS/benchmarks/tracking/src/matlab/script_run_profile.m b/SD-VBS/benchmarks/tracking/src/matlab/script_run_profile.m
new file mode 100755
index 0000000..62d367f
--- /dev/null
+++ b/SD-VBS/benchmarks/tracking/src/matlab/script_run_profile.m
@@ -0,0 +1,178 @@
+function script_run_profile(dataDir, resultDir, type, common, toolDir)
+
+if(~isdeployed)
+    addpath(fullfile(toolDir, '/lagrcv/'));
+    addpath(fullfile(toolDir, '/toolbox_basic/filter/'));
+    addpath(fullfile(toolDir, '/ikkjin/'));
+end
+IMAGE_DIR=dataDir;
+
+path(path,common); 
+
+tol = 2;
+
+%% Input params
+N_FEA=1600;
+WINSZ=4; %size of sum-up window
+NO_PYR=2;
+SUPPRESION_RADIUS=10;
+LK_ITER=20;
+counter = 2;
+accuracy = 0.03;
+
+if(strcmp(type,'test'))
+    WINSZ = 2;
+    N_FEA = 10;
+    LK_ITER = 2;
+    counter = 2;
+    accuracy = 0.1;
+elseif(strcmp(type, 'sim_fast'))
+    WINSZ = 2;
+    N_FEA = 100;
+    LK_ITER = 2;
+    counter = 4;
+elseif(strcmp(type,'sim'))
+    WINSZ = 2;
+    N_FEA = 200;
+    LK_ITER = 2;
+    counter = 4;
+elseif(strcmp(type,'sqcif'))
+    WINSZ = 8;
+    N_FEA = 500;
+    LK_ITER = 15;
+    counter = 2;
+elseif(strcmp(type, 'qcif'))
+    WINSZ = 12;
+    N_FEA = 400;
+    LK_ITER = 15;
+    counter = 4;
+elseif(strcmp(type,'cif'))
+    WINSZ = 20;
+    N_FEA = 500;
+    LK_ITER = 20;
+    counter = 4;
+elseif(strcmp(type, 'vga'))
+    WINSZ = 32;
+    N_FEA = 400;
+    LK_ITER = 20;
+    counter = 4;
+elseif(strcmp(type,'fullhd'))
+    WINSZ = 48;
+    N_FEA = 500;
+    LK_ITER = 20;
+    counter = 4;
+elseif(strcmp(type,'wuxga'))
+    WINSZ = 64;
+    N_FEA = 500;
+    LK_ITER = 20;
+    counter = 4;
+end
+
+imgName = [dataDir, '/1.bmp'];
+Icur=readImage(imgName);
+
+[rows,cols] = size(Icur);
+fprintf(1,'Input size\t\t- (%dx%d)\n', rows, cols);
+
+%% Timing
+start = photonStartTiming;
+
+Icur = imageBlur(double(Icur));
+
+ Jpyr = cell(2,1);
+ Jpyr{1} = Icur;
+ Jpyr{2} = imageResize(Icur);
+
+ [dX, dY] = calcSobel(double(Icur));
+ sizeWin = size(dX);
+ [lambda, tr, det, c_xx, c_xy, c_yy] = calcGoodFeature(dX, dY, sizeWin(2), sizeWin(1), WINSZ, dataDir);
+
+imgsz=size(lambda);
+lambda([1:WINSZ,end-WINSZ:end],:)=0;
+lambda(:,[1:WINSZ,end-WINSZ:end])=0;
+
+[temp,idx]=sort(lambda(:), 'descend');
+featureIdx=idx(1:N_FEA);
+features=zeros(3, N_FEA);
+features(1,:)=ceil(featureIdx/imgsz(1));
+
+fIdxT = featureIdx';
+features(2,:)=fIdxT-(features(1,:)-1)*imgsz(1);
+features(3,:)=lambda(featureIdx);
+
+for i=1:N_FEA
+    features(3,i) = lambda(idx(i));
+end
+
+f1T = features(1,:)';
+f2T = features(2,:)';
+f3T = features(3,:)';
+
+interestPnt=getANMS(f1T, f2T, f3T, SUPPRESION_RADIUS, dataDir);
+
+interestPnt=interestPnt';
+features=interestPnt(1:2,:);
+    
+%% Timing
+endC = photonEndTiming;
+elapsed = photonReportTiming(start, endC);
+
+for iter=1:counter
+    imgName = [dataDir, '/', num2str(iter),  '.bmp'];
+    Iprev=Icur;
+    Icur=readImage(imgName);
+    
+    %% Self check params
+    tol = 0.1;
+    %% Timing
+    start = photonStartTiming;
+
+    Icur = imageBlur(double(Icur));
+    
+    Ipyr=Jpyr;
+    
+    Jpyr = cell(2,1);
+    Jpyr{1} = Icur;
+    Jpyr{2} = imageResize(Icur);
+
+    dxPyr = cell(2,1);
+    dyPyr = cell(2,1);
+     
+    [dxPyr{1}, dyPyr{1}] = calcSobel(Jpyr{1});
+    [dxPyr{2}, dyPyr{2}] = calcSobel(Jpyr{2});
+    
+    sizeWin = size(dxPyr{2});
+    nFeatures = size(features);
+     
+    [newpoints, currStatus] = calcPyrLKTrack(Ipyr, dxPyr, dyPyr, Jpyr, double(features), nFeatures(2), WINSZ, 0.03, LK_ITER);
+    
+    newpoints=newpoints(:,find(currStatus));
+
+    %% Timing
+    stop = photonEndTiming;
+
+    temp = photonReportTiming(start, stop);
+    elapsed(1) = elapsed(1) + temp(1);
+    elapsed(2) = elapsed(2) + temp(2);
+
+%      figure(1);
+%      imagesc(Icur);colormap gray
+%      hold on;
+%      scatter(newpoints(1,:), newpoints(2,:), 'r+');
+%      hold off;    
+%      drawnow
+%     
+    features=newpoints;
+
+end
+    
+%% Self checking
+fWriteMatrix(features, dataDir);
+
+photonPrintTiming(elapsed);
+
+if(~isdeployed)
+    rmpath(fullfile(toolDir, '/lagrcv/'));
+    rmpath(fullfile(toolDir, '/toolbox_basic/filter/'));
+    rmpath(fullfile(toolDir, '/ikkjin/'));
+end