1 files changed, 0 insertions, 58 deletions

diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m
deleted file mode 100755
index fa8a554..0000000
--- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m
+++ /dev/null
@@ -1,58 +0,0 @@
-% 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);