From f618466c25d43f3bae9e40920273bf77de1e1149 Mon Sep 17 00:00:00 2001
From: leochanj105 <leochanj@live.unc.edu>
Date: Mon, 19 Oct 2020 23:09:30 -0400
Subject: initial sd-vbs

initial sd-vbs

add sd-vbs

sd-vbs
---
 .../src/matlabPyrTools/entropy2.m                  | 31 ++++++++++++++++++++++
 1 file changed, 31 insertions(+)
 create mode 100755 SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/entropy2.m

(limited to 'SD-VBS/benchmarks/texture_synthesis/src/matlabPyrTools/entropy2.m')

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));
+
-- 
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