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
---
 .../texture_synthesis/src/matlab/mkGaussian.m      | 58 ++++++++++++++++++++++
 1 file changed, 58 insertions(+)
 create mode 100755 SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m

(limited to 'SD-VBS/benchmarks/texture_synthesis/src/matlab/mkGaussian.m')

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);
-- 
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