initial sd-vbs

initial sd-vbs

add sd-vbs

sd-vbs

1 files changed, 73 insertions, 0 deletions

diff --git a/SD-VBS/common/toolbox/toolbox_basic/stella/afromncut.m b/SD-VBS/common/toolbox/toolbox_basic/stella/afromncut.m
new file mode 100755
index 0000000..ec014d0
--- /dev/null
+++ b/SD-VBS/common/toolbox/toolbox_basic/stella/afromncut.m
@@ -0,0 +1,73 @@
+% function a = afromncut(v,s,d,visimg,no_rep,pixel_loc)
+% Input:
+%    v = eigenvectors of d*a*d, starting from the second.
+%      (the first is all one over some constant determined by d)
+%    s = eigenvalues
+%    d = normalization matrix 1/sqrt(rowsum(abs(a)))
+%    visimg = 1/0 if each eigenvector is/not 2D (so v is 3D)
+%    no_rep = 1 (default), affinity has attraction only
+%        if 1, the first column of v is the second eigenvector
+%        if 0, the first column of v is the first eigenvector.
+%    pixel_loc = nx1 matrix, each is a pixel location
+% Output:
+%    a = diag(1/d) * na * diag(1/d);
+%    If pixel_loc = []; a is returned, if not out of memory
+%    otherwise, only rows of a at pixel_loc are returned.
+%
+% This routine is used to estimate the original affinity matrix
+% through the first few eigenvectors and its normalization matrix.
+
+% A test sequence includes:
+% a = randsym(5);
+% [na,d] = normalize(a);
+% [v,s] = ncut(a,5);
+% v = v(:,2:end); s = s(2:end);
+% aa = afromncut(v,s,d);
+% max(abs(aa(:) - a(:)))
+
+% Stella X. Yu, 2000.
+
+function a = afromncut(v,s,d,visimg,no_rep,pixel_loc)
+
+[nr,nc,nv] = size(v);
+if nargin<4 | isempty(visimg),
+   visimg = (nv>1);
+end
+
+if nargin<5 | isempty(no_rep),
+   no_rep = 1;
+end
+
+if visimg,
+   nr = nr * nc;
+else
+   nv = nc;
+end
+
+if nargin<6 | isempty(pixel_loc),
+   pixel_loc = 1:nr;
+end
+
+% D^(1/2)
+d = 1./(d(:)+eps);
+
+% first recover the first eigenvector
+if no_rep,
+    u = (1/norm(d)) + zeros(nr,1);
+    s = [1;s(:)];
+    nv = nv + 1;
+else
+    u = [];
+end
+
+% the full set of generalized eigenvectors
+v = [u, reshape(v,[nr,nv-no_rep])];
+
+% This is the real D, row sum
+d = d.^2;
+
+% an equivalent way to compute v = diag(d) * v;
+v = v .* d(:,ones(nv,1)); % to avoid using a big matrix diag(d)
+
+% synthesis
+a = v(pixel_loc,:)*diag(s)*v';