demo_eusipco2006.m

Total variation image deconvolution_A majorization-minimization approach

% Experience (numero) from paper
% Change here!!!!
numero=1;

% images
img1='cameraman.tif';
img3='lena_256.gif';


if numero==1
    h=ones(9)/81;
    sigma=0.56;
    img=double(imread(img1));
elseif(numero==2)
    h=ones(9)/81;
    sigma=0.4;
    img=255*phantom(256);
    
elseif(numero==3)
    h=[1 4 6 4 1]'*[1 4 6 4 1]/256;
    sigma=7;
    img=double(imread(img3));
elseif(numero==5)

end


% % zero noise image (not necessary)
img=img-mean(img(:));



% Blured noisy image
img_noisy=conv2c(img,h)+sigma*randn(size(img));


img_estimated=tvmm_a(img_noisy,h,'info_energyo','no','image',img, ...
    'cg_iter',200,'boa_iter',10,'info_ISNRo','yes','info_ISNRi','no','displayIm','yes');