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diff --git a/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureAnalysis.m b/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureAnalysis.m
deleted file mode 100755
index d7a0ec1..0000000
--- a/SD-VBS/benchmarks/texture_synthesis/src/matlab/textureAnalysis.m
+++ /dev/null
@@ -1,245 +0,0 @@
-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);
-
-