comparison Problems/AudioDenoise_reconstruct.m @ 161:f42aa8bcb82f ivand_dev

debug and clean the SMALLbox Problems code

+function reconstructed=AudioDenoise_reconstruct(y, Problem)
+%%  Audio denoising Problem reconstruction function
+%   
+%   This reconstruction function is using sparse representation y 
+%   in dictionary Problem.A to reconstruct denoised audio.
+%   The output structre has following fields:
+%       audio   - denoised audio signal
+%       psnr    - psnr of the reconstructed audio signal
+%
+%   [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
+
+%
+%   Centre for Digital Music, Queen Mary, University of London.
+%   This file copyright 2011 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.A;
+
+orig   = Problem.Original;
+noisy  = Problem.Noisy;
+
+
+% reconstruct audio frames
+
+xFrames = diag(ws)*(A*y);
+wNormFrames = (ws.*wa)'*ones(1,size(xFrames,2));
+
+%   overlap and add
+
+rec   = col2imstep(xFrames, size(noisy), [windowSize 1], [windowSize*overlap 1]);
+wNorm = col2imstep(wNormFrames, size(noisy), [windowSize 1], [windowSize*overlap 1]); 
+wNorm(find(wNorm==0)) = 1; 
+recN  = rec./wNorm;
+
+%% output structure image+psnr %%
+reconstructed.audio  = recN;
+reconstructed.psnr = 20*log10(sqrt(numel(orig)) / norm(orig - reconstructed.audio));
+
+end