Mercurial > hg > smallbox
view util/SMALL_ImgDeNoiseResult.m @ 167:8324c7ea6602 danieleb
Added symmetric de-correlation function, modified target de-correlation in test function.
author | Daniele Barchiesi <daniele.barchiesi@eecs.qmul.ac.uk> |
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date | Tue, 20 Sep 2011 14:27:14 +0100 |
parents | 002ec1b2ceff |
children |
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function SMALL_ImgDeNoiseResult(SMALL) %% Represents the results of Dictionary Learning for Image denoising % % Function gets as input SMALL structure and plots Image Denoise % results: Original Image, Noisy Image and for learned dictionaries and % denoised images % % Centre for Digital Music, Queen Mary, University of London. % This file copyright 2010 Ivan Damnjanovic. % % This program is free software; you can redistribute it and/or % modify it under the terms of the GNU General Public License as % published by the Free Software Foundation; either version 2 of the % License, or (at your option) any later version. See the file % COPYING included with this distribution for more information. %% figure('Name', sprintf('Image %s (training set size- %d, sigma - %d)',SMALL.Problem.name, SMALL.Problem.n, SMALL.Problem.sigma)); m=size(SMALL.solver,2)+1; maxval=SMALL.Problem.maxval; im=SMALL.Problem.Original; imnoise=SMALL.Problem.Noisy; subplot(2, m, 1); imagesc(im/maxval);colormap(gray);axis off; axis image; % Set aspect ratio to obtain square pixels title('Original image'); subplot(2,m,m+1); imagesc(imnoise/maxval);axis off; axis image; title(sprintf('Noisy image, PSNR = %.2fdB', SMALL.Problem.noisy_psnr )); for i=2:m subplot(2, m, i); imagesc(SMALL.solver(i-1).reconstructed.Image/maxval);axis off; axis image; title(sprintf('%s Denoised image, PSNR: %.2f dB in %.2f s',... SMALL.DL(i-1).name, SMALL.solver(i-1).reconstructed.psnr, SMALL.solver(i-1).time ),'Interpreter','none'); if strcmpi(SMALL.DL(i-1).name,'ksvds') D = kron(SMALL.Problem.basedict{2},SMALL.Problem.basedict{1})*SMALL.DL(i-1).D; else D = SMALL.DL(i-1).D; end dictimg = SMALL_showdict(D,SMALL.Problem.blocksize,... round(sqrt(size(D,2))),round(sqrt(size(D,2))),'lines','highcontrast'); subplot(2,m,m+i);imagesc(dictimg);axis off; axis image; title(sprintf('%s dictionary in %.2f s',... SMALL.DL(i-1).name, SMALL.DL(i-1).time),'Interpreter','none'); end