annotate Problems/ImageDenoise_reconstruct.m @ 163:855025f4c779 ivand_dev

renaiming small_cgp to small_pcgp
author Ivan Damnjanovic lnx <ivan.damnjanovic@eecs.qmul.ac.uk>
date Wed, 07 Sep 2011 14:16:50 +0100
parents f42aa8bcb82f
children
rev   line source
ivan@161 1 function reconstructed=ImageDenoise_reconstruct(y, Problem, SparseDict)
ivan@161 2 %% Image Denoising Problem reconstruction function
ivan@161 3 %
ivan@161 4 % This reconstruction function is using sparse representation y
ivan@161 5 % in dictionary Problem.A to reconstruct the patches of the denoised
ivan@161 6 % image.
ivan@161 7
ivan@161 8 %
ivan@161 9 % Centre for Digital Music, Queen Mary, University of London.
ivan@161 10 % This file copyright 2009 Ivan Damnjanovic.
ivan@161 11 %
ivan@161 12 % This program is free software; you can redistribute it and/or
ivan@161 13 % modify it under the terms of the GNU General Public License as
ivan@161 14 % published by the Free Software Foundation; either version 2 of the
ivan@161 15 % License, or (at your option) any later version. See the file
ivan@161 16 % COPYING included with this distribution for more information.
ivan@161 17 %%
ivan@161 18
ivan@161 19
ivan@161 20 % stepsize %
ivan@161 21 if (isfield(Problem,'stepsize'))
ivan@161 22 stepsize = Problem.stepsize;
ivan@161 23 if (numel(stepsize)==1)
ivan@161 24 stepsize = ones(1,2)*stepsize;
ivan@161 25 end
ivan@161 26 else
ivan@161 27 stepsize = ones(1,2);
ivan@161 28 end
ivan@161 29 if (any(stepsize<1))
ivan@161 30 error('Invalid step size.');
ivan@161 31 end
ivan@161 32
ivan@161 33 % lambda %
ivan@161 34 if (isfield(Problem,'lambda'))
ivan@161 35 lambda = Problem.lambda;
ivan@161 36 else
ivan@161 37 lambda = Problem.maxval/(10*Problem.sigma);
ivan@161 38 end
ivan@161 39 if exist('SparseDict','var')&&(SparseDict==1)
ivan@161 40 if issparse(Problem.A)
ivan@161 41 A = Problem.A;
ivan@161 42 else
ivan@161 43 A = sparse(Problem.A);
ivan@161 44 end
ivan@161 45 cl_samp=add_dc(dictsep(Problem.basedict,A,y), Problem.b1dc,'columns');
ivan@161 46 else
ivan@161 47 cl_samp=add_dc(Problem.A*y, Problem.b1dc,'columns');
ivan@161 48 end
ivan@161 49 % combine the patches into reconstructed image
ivan@161 50 cl_im=col2imstep(cl_samp, size(Problem.Noisy), Problem.blocksize);
ivan@161 51
ivan@161 52 cnt = countcover(size(Problem.Noisy),Problem.blocksize,stepsize);
ivan@161 53
ivan@161 54 im = (cl_im+lambda*Problem.Noisy)./(cnt + lambda);
ivan@161 55 % y(y~=0)=1;
ivan@161 56 % numD=sum(y,2);
ivan@161 57 % nnzy=sum(y,1);
ivan@161 58 % figure(200);plot(sort(numD));
ivan@161 59 % figure(201);plot(sort(nnzy));
ivan@161 60 [v.RMSErn, v.RMSEcd, v.rn_im, v.cd_im]=SMALL_vmrse_type2(Problem.Original, Problem.Noisy, im);
ivan@161 61 %% output structure image+psnr %%
ivan@161 62 reconstructed.Image=im;
ivan@161 63 reconstructed.psnr = 20*log10(Problem.maxval * sqrt(numel(Problem.Original(:))) / norm(Problem.Original(:)-im(:)));
ivan@161 64 reconstructed.vmrse=v;
ivan@161 65 reconstructed.ssim=SMALL_ssim_index(Problem.Original, im);
ivan@161 66 end