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denoiseanddeblur.m
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%% USING THE MATRIX FUNCTION ROUTINE TO DENOISE THE IMAGE:
clear; clc;
warning('off','all');
clear classes
cd('AIRToolsII/');
AIRToolsII_setup;
cd('..');
cd('IRtools/');
IRtools_setup;
cd('..');
warning('on','all');
FID = fopen('results_IRfun.dat','a');
fprintf(FID,'Experiment run on %s\n',datestr(now));
levelblur = {'mild','medium','severe'};
plotfigures = false;
%% Launch iteration:
imagename = 'satellite';
for blurindex = [1,2,3]
fprintf(FID,'TEST CASE %s - BlurLevel %s \n',imagename{1},levelblur{blurindex});
%% Generate the blurred and noised signal:
options = struct('trueImage', imagename{1},...
'BlurLevel', levelblur{blurindex}, ... % must be 'mild' or 'medium' or 'severe'.
'BC', 'zero',...
'CommitCrime', 'off');
[A, bl, x_true, ProbInfo] = PRblurgauss(options);
if plotfigures
PRshowb(bl,ProbInfo,blurindex+10);
end
for NoiseLevel = [1e-3,1e-2,1e-1,2e-1,3e-1,5e-1] % ,6e-1
fprintf(FID,'%1.1e',NoiseLevel);
[b, NoiseInfo] = PRnoise(bl, 'gauss',NoiseLevel);
if plotfigures
figure(99)
subplot(1,3,1);
imshow(reshape(x_true,sqrt([size(x_true,1),size(x_true,1)])),[]);
title('True Image');
subplot(1,3,2);
imshow(reshape(bl,sqrt([size(x_true,1),size(x_true,1)])),[]);
title('Blurred Image');
subplot(1,3,3);
imshow(reshape(b,sqrt([size(x_true,1),size(x_true,1)])),[]);
title('Noisy and Blurred Image');
xlabel(sprintf('PSNR %1.2f',psnr(b,x_true)));
figure(1)
subplot(2,3,1);
imshow(reshape(b,sqrt([size(x_true,1),size(x_true,1)])),[]);
title('Noisy and Blurred Image');
xlabel(sprintf('PSNR %1.2f',psnr(b,x_true)));
end
%% Apply the CGLS to restore the signal:
fprintf('CGLS Algorithm:\n');
options = IRcgls('defaults');
options.x_true = x_true;
options.NoiseLevel = NoiseLevel;
options.verbosity = 'off';
options.IterBar = 'off';
tic;
[Xcgls,infocgls] = IRcgls(A,b,options);
timecgls = toc;
options.NoStop = 'on';
[~,infocglsbest] = IRcgls(A,b,options);
fprintf(FID, ' & %d (%d) & %1.1e & %1.2f (%1.2f)',...
infocgls.StopReg.It,infocglsbest.BestReg.It,timecgls,...
psnr(reshape(infocgls.StopReg.X,size(x_true)),x_true),...
psnr(reshape(infocglsbest.BestReg.X,size(x_true)),x_true));
if plotfigures
figure(1)
subplot(2,3,2);
imshow(reshape(infocgls.StopReg.X,sqrt([size(x_true,1),size(x_true,1)])),[]);
title('CGLS');
xlabel(sprintf('PSNR %1.2f',psnr(infocgls.StopReg.X,x_true)));
end
%% Apply the Range-Restricted GMRES
fprintf('\nRangeRestricted GMRES Algorithm:\n');
options = IRrrgmres('defaults');
options.x_true = x_true;
options.NoiseLevel = NoiseLevel;
options.verbosity = 'off';
options.IterBar = 'off';
tic;
[Xrrgmres,inforrgmres] = IRrrgmres(A,b,options);
timerrgmres = toc;
options.NoStop = 'on';
[~,inforrgmresbest] = IRrrgmres(A,b,options);
fprintf(FID,' & %d (%d) & %1.1e & %1.2f (%1.2f)', ...
inforrgmres.StopReg.It,...
inforrgmresbest.BestReg.It,timerrgmres,...
psnr(reshape(inforrgmres.StopReg.X,size(x_true)),x_true),...
psnr(reshape(inforrgmresbest.BestReg.X,size(x_true)),x_true));
if plotfigures
figure(1)
subplot(2,3,4);
imshow(reshape(inforrgmres.StopReg.X,sqrt([size(x_true,1),size(x_true,1)])),[]);
title('RR-GMRES');
xlabel(sprintf('PSNR %1.2f',psnr(inforrgmres.StopReg.X,x_true)));
end
%% CGLS for Tikhonov method
fprintf('\nTikhonov CGLS method:\n');
options = IRcgls('defaults');
if plotfigures
figure(2)
end
options.x_true = x_true;
options.verbosity = 'off';
options.IterBar = 'off';
options.NoiseLevel = 'none';
tic;
options.RegParam = settikhonov(A,b);
[Xtikhonov,infotikhonov] = IRcgls(A,b,options);
timetikhonov = toc;
fprintf(FID,'& %1.2e & %d & %1.1e & %1.2f',...
options.RegParam,infotikhonov.StopReg.It,timetikhonov,...
psnr(reshape(infotikhonov.StopReg.X,size(x_true)),x_true));
if plotfigures
figure(1)
subplot(2,3,5);
imshow(reshape(infotikhonov.StopReg.X,sqrt([size(x_true,1),size(x_true,1)])),[]);
title('Tikhonov CGLS');
xlabel(sprintf('PSNR %1.2f',psnr(infotikhonov.StopReg.X,x_true)));
end
%% Apply the matrix-function denoiser:
fprintf('\nMatrix Function Regularizer:\n');
options = IRfun('defaults');
options.RegParam = NoiseLevel*1e-1;
options.x_true = x_true;
options.NoStop = 'off';
options.RegBeta = 1e+6;
options.verbosity = 0;
options.NoiseLevel = NoiseLevel;
options.MaxIter = 100;
options.IterBar = 'off';
options.Reorth = 'on';
options.eta = 1.01;
options.RegType = 'lanczos';
fprintf(FID,' & %1.1e',options.RegParam);
tic;
[X,infofun] = IRfun(A,b,options);
timefun = toc;
options.NoStop = 'on';
[~,infofunbest] = IRfun(A,b,options);
fprintf(FID,'& %d (%d) & %1.1e & %1.2f (%1.2f)',...
infofun.StopReg.It,infofunbest.BestReg.It,timefun,...
psnr(reshape(infofun.StopReg.X,size(x_true)),x_true),...
psnr(reshape(infofunbest.BestReg.X,size(x_true)),x_true));
if plotfigures
figure(1)
subplot(2,3,6);
imshow(reshape(infofun.StopReg.X,sqrt([size(x_true,1),size(x_true,1)])),[]);
title('Matrix Function');
xlabel(sprintf('PSNR %1.2f',psnr(infofun.StopReg.X,x_true)));
export_fig(sprintf('satellite_%s_%1.1e.eps',levelblur{blurindex},NoiseLevel))
end
%% Apply Hybrid methods : Hybrid-GMRES
fprintf('\nHybrid GMRES method:\n');
options = IRhybrid_gmres('defaults');
options.x_true = x_true;
options.verbosity = 'off';
options.IterBar = 'off';
options.NoStop = 'off';
tic;
[Xhybridgmres,infohybridgmres] = IRhybrid_gmres(A,b,options);
timehybridgmres = toc;
options.NoStop = 'on';
[~,infohybridgmresbest] = IRhybrid_gmres(A,b,options);
fprintf(FID, ' & %d (%d) & %1.1e & %1.2f (%1.2f)',...
infohybridgmres.StopReg.It,infohybridgmresbest.BestReg.It,timehybridgmres,...
psnr(reshape(infohybridgmres.StopReg.X,size(x_true)),x_true),...
psnr(reshape(infohybridgmresbest.BestReg.X,size(x_true)),x_true));
%% Apply Hybrid methods : Hybrid-FGMRES
fprintf('\nHybrid fgmres method:\n');
options = IRhybrid_fgmres('defaults');
options.x_true = x_true;
options.verbosity = 'off';
options.IterBar = 'off';
options.NoStop = 'off';
tic;
[Xhybridfgmres,infohybridfgmres] = IRhybrid_fgmres(A,b,options);
timehybridfgmres = toc;
options.NoStop = 'on';
[~,infohybridfgmresbest] = IRhybrid_fgmres(A,b,options);
fprintf(FID, ' & %d (%d) & %1.1e & %1.2f (%1.2f)',...
infohybridfgmres.StopReg.It,infohybridfgmresbest.BestReg.It,timehybridfgmres,...
psnr(reshape(infohybridfgmres.StopReg.X,size(x_true)),x_true),...
psnr(reshape(infohybridfgmresbest.BestReg.X,size(x_true)),x_true));
%% Apply Hybrid methods : Hybrid-lsqr
fprintf('\nHybrid lsqr method:\n');
options = IRhybrid_lsqr('defaults');
options.x_true = x_true;
options.verbosity = 'off';
options.IterBar = 'off';
options.NoStop = 'off';
tic;
[Xhybridlsqr,infohybridlsqr] = IRhybrid_lsqr(A,b,options);
timehybridlsqr = toc;
options.NoStop = 'on';
[~,infohybridlsqrbest] = IRhybrid_lsqr(A,b,options);
fprintf(FID, ' & %d (%d) & %1.1e & %1.2f (%1.2f)',...
infohybridlsqr.StopReg.It,infohybridlsqrbest.BestReg.It,timehybridlsqr,...
psnr(reshape(infohybridlsqr.StopReg.X,size(x_true)),x_true),...
psnr(reshape(infohybridlsqrbest.BestReg.X,size(x_true)),x_true));
fprintf(FID,'\\\\\n');
end
fprintf(FID,'\n\n\n\n');
end
fclose(FID);