annotate Problems/AudioDeclipping_reconstruct.m @ 140:31d2864dfdd4 ivand_dev

Audio Impainting additional constraints with cvx added
author Ivan Damnjanovic lnx <ivan.damnjanovic@eecs.qmul.ac.uk>
date Mon, 25 Jul 2011 17:27:05 +0100
parents 1334d2302dd9
children f42aa8bcb82f
rev   line source
ivan@136 1 function reconstructed=AudioDeclipping_reconstruct(y, Problem, SparseDict)
ivan@136 2 %% Audio declipping Problem reconstruction function
ivan@136 3 %
ivan@136 4 % This reconstruction function is using sparse representation y
ivan@140 5 % in dictionary Problem.A to reconstruct declipped audio.
ivan@140 6 %
ivan@140 7 % [1] I. Damnjanovic, M. E. P. Davies, and M. P. Plumbley "SMALLbox - an
ivan@140 8 % evaluation framework for sparse representations and dictionary
ivan@140 9 % learning algorithms," V. Vigneron et al. (Eds.): LVA/ICA 2010,
ivan@140 10 % Springer-Verlag, Berlin, Germany, LNCS 6365, pp. 418-425
ivan@140 11 % [2] A. Adler, V. Emiya, M. G. Jafari, M. Elad, R. Gribonval, and M. D.
ivan@140 12 % Plumbley, “Audio Inpainting,” submitted to IEEE Trans. Audio, Speech,
ivan@140 13 % and Lang. Proc., 2011, http://hal.inria.fr/inria-00577079/en/.
ivan@136 14
ivan@136 15 %
ivan@136 16 % Centre for Digital Music, Queen Mary, University of London.
ivan@136 17 % This file copyright 2009 Ivan Damnjanovic.
ivan@136 18 %
ivan@136 19 % This program is free software; you can redistribute it and/or
ivan@136 20 % modify it under the terms of the GNU General Public License as
ivan@136 21 % published by the Free Software Foundation; either version 2 of the
ivan@136 22 % License, or (at your option) any later version. See the file
ivan@136 23 % COPYING included with this distribution for more information.
ivan@136 24 %%
ivan@136 25
ivan@136 26 windowSize = Problem.windowSize;
ivan@136 27 overlap = Problem.overlap;
ivan@136 28 ws = Problem.ws(windowSize);
ivan@136 29 wa = Problem.wa(windowSize);
ivan@136 30 A = Problem.B;
ivan@136 31
ivan@136 32 orig = Problem.original;
ivan@136 33 clipped = Problem.clipped;
ivan@136 34 clipMask = Problem.clipMask;
ivan@136 35
ivan@136 36 % reconstruct audio frames
ivan@136 37
ivan@136 38 xFrames = diag(ws)*(A*y);
ivan@136 39 wNormFrames = (ws.*wa)'*ones(1,size(xFrames,2));
ivan@136 40
ivan@136 41 % overlap and add
ivan@136 42
ivan@136 43 rec = col2imstep(xFrames, size(clipped), [windowSize 1], [windowSize*overlap 1]);
ivan@136 44 wNorm = col2imstep(wNormFrames, size(clipped), [windowSize 1], [windowSize*overlap 1]);
ivan@136 45 wNorm(find(wNorm==0)) = 1;
ivan@136 46 recN = rec./wNorm;
ivan@136 47
ivan@136 48 % change only clipped samples
ivan@136 49
ivan@136 50 recSignal = orig.*double(~clipMask) + recN.*double(clipMask);
ivan@136 51
ivan@136 52 %% output structure image+psnr %%
ivan@136 53 reconstructed.audioAllSamples = recN;
ivan@136 54 reconstructed.audioOnlyClipped = recSignal;
ivan@136 55 [reconstructed.snrAll , reconstructed.snrMiss] = SNRInpaintingPerformance(orig, clipped, recSignal, clipMask, 1);
ivan@136 56
ivan@136 57 end