clear all
close all
MC     = 10;
lambdadwt  = 4.5;
lambdaudwt = [4.5*ones(1,6) 6];
lambdacurv = 4.5;
thd    = 3; 
L      = 4;
sigma  = [5,10,15,20,25,30,50];
images = {'barbara_512x512.png','lena512x512.png','house.png','boat.png','fingerprint.png','peppers256.png'};
qmf    = MakeONFilter('Symmlet',6);
randn('state',0);

for in=1:length(images)
  img=double(imread(images{in}));
  img=255*img/max(img(:));
  for is=1:length(sigma)
   for rep=1:MC
    imnoisy=img+sigma(is)*randn(size(img));
    % Term-by-term DWT.
    imden=den2d(imnoisy,qmf,2,'H',sigma(is),thd*sigma(is));
    psnrDWTterm(in,is,rep)=psnr(img(:),imden(:));
    % Block DWT.  
    imden=den2d_block(imnoisy,qmf,lambdadwt,L,sigma(is));
    psnrDWTblock(in,is,rep)=psnr(img(:),imden(:));
    
    % Term-by-term UDWT.
    imden=den2d_TI(imnoisy,qmf,2,'H',sigma(is));
    psnrUDWTterm(in,is,rep)=psnr(img(:),imden(:));   
    % Block UDWT.  
    imden=den2d_blockTI(imnoisy,qmf,lambdaudwt(is),L,sigma(is));
    psnrUDWTblock(in,is,rep)=psnr(img(:),imden(:));
    
    % Term-by-term Curvelets.
    imden=den2d_curvwrap(imnoisy,5,'H',sigma(is));
    psnrCURVterm(in,is,rep)=psnr(img(:),imden(:));     
    % Block Curvelets.
    imden=den2d_blockcurvwrap(imnoisy,4,lambdacurv,L,sigma(is));
    psnrCURVblock(in,is,rep)=psnr(img(:),imden(:));
   end
   psnrDWTblockmean(in,is)=squeeze(mean(psnrDWTblock(in,is,:),3));
   psnrUDWTblockmean(in,is)=squeeze(mean(psnrUDWTblock(in,is,:),3));
   psnrCURVblockmean(in,is)=squeeze(mean(psnrCURVblock(in,is,:),3));
   psnrDWTtermmean(in,is)=squeeze(mean(psnrDWTterm(in,is,:),3));
   psnrUDWTtermmean(in,is)=squeeze(mean(psnrUDWTterm(in,is,:),3));
   psnrCURVtermmean(in,is)=squeeze(mean(psnrCURVterm(in,is,:),3));
  end
  figure(in);
  set(gcf,'Name',sprintf('%s',images{in}),'NumberTitle','off');
  plot(sigma,psnrDWTblockmean(in,:)-psnrDWTtermmean(in,:),'-b',...
       sigma,psnrUDWTtermmean(in,:)-psnrDWTtermmean(in,:),'--b',...
       sigma,psnrUDWTblockmean(in,:)-psnrDWTtermmean(in,:),'-.b',...
       sigma,psnrCURVtermmean(in,:)-psnrDWTtermmean(in,:),':b',...
       sigma,psnrCURVblockmean(in,:)-psnrDWTtermmean(in,:),'.-b');
  axis tight			
  xlabel('\sigma');
  ylabel('PSNR improvement (dB)');
  if in==1
  	legend('DWT block','UDWT term','UDWT block','FDCT term','FDCT block');
  end
end

save simudenblockvsterm.mat


%
% Part of DBlockToolbox Version:100
% Written by: Jalal Fadili, GREYC CNRS ENSICAEN
%             Christophe Chesneau, LMNO University of Caen
%             Jean-Luc Starck, CEA-CNRS
% Created June 2008
% This material is distributed under CeCiLL licence.
% E-mail: Jalal.Fadili@greyc.ensicaen.fr
%