Mercurial > hg > smallbox
view Problems/AudioDeclipping_reconstruct.m @ 156:a4d0977d4595 danieleb
First branch commit, danieleb
author | danieleb |
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date | Tue, 30 Aug 2011 11:12:31 +0100 |
parents | 31d2864dfdd4 |
children | f42aa8bcb82f |
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function reconstructed=AudioDeclipping_reconstruct(y, Problem, SparseDict) %% Audio declipping Problem reconstruction function % % This reconstruction function is using sparse representation y % in dictionary Problem.A to reconstruct declipped audio. % % [1] I. Damnjanovic, M. E. P. Davies, and M. P. Plumbley "SMALLbox - an % evaluation framework for sparse representations and dictionary % learning algorithms," V. Vigneron et al. (Eds.): LVA/ICA 2010, % Springer-Verlag, Berlin, Germany, LNCS 6365, pp. 418-425 % [2] A. Adler, V. Emiya, M. G. Jafari, M. Elad, R. Gribonval, and M. D. % Plumbley, “Audio Inpainting,” submitted to IEEE Trans. Audio, Speech, % and Lang. Proc., 2011, http://hal.inria.fr/inria-00577079/en/. % % Centre for Digital Music, Queen Mary, University of London. % This file copyright 2009 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. %% windowSize = Problem.windowSize; overlap = Problem.overlap; ws = Problem.ws(windowSize); wa = Problem.wa(windowSize); A = Problem.B; orig = Problem.original; clipped = Problem.clipped; clipMask = Problem.clipMask; % reconstruct audio frames xFrames = diag(ws)*(A*y); wNormFrames = (ws.*wa)'*ones(1,size(xFrames,2)); % overlap and add rec = col2imstep(xFrames, size(clipped), [windowSize 1], [windowSize*overlap 1]); wNorm = col2imstep(wNormFrames, size(clipped), [windowSize 1], [windowSize*overlap 1]); wNorm(find(wNorm==0)) = 1; recN = rec./wNorm; % change only clipped samples recSignal = orig.*double(~clipMask) + recN.*double(clipMask); %% output structure image+psnr %% reconstructed.audioAllSamples = recN; reconstructed.audioOnlyClipped = recSignal; [reconstructed.snrAll , reconstructed.snrMiss] = SNRInpaintingPerformance(orig, clipped, recSignal, clipMask, 1); end