📄 scfig09.m
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% scfig09 -- Short Course 09: WaveShrink of object yBlocks in Haar Basis
%
% (Panel a) depicts the noisy object yBlocks, its Haar transform (Panel
% c), wavelet shrinkage reconstruction using the Haar wavelet (Panel b),
% and the Haar Transform of the reconstruction (Panel d).
%
% The viewer is supposed to notice that in the Haar domain, the noise is
% spread out among all coefficients, while the signal is concentrated in
% only a few coefficients. Hence thresholding mostly affects the noise
% without disturbing the signal.
%
global Blocks t
%
HL = 3;
HQMF = MakeONFilter('Haar');
[x,y] = NoiseMaker(Blocks,7);
[xhat,xw] = WaveShrink(y,'Visu',HL,HQMF);
yw = FWT_PO(y,HL,HQMF);
%
% clf;
scal = .05;
versaplot(221,t,y, [],' 9 (a) Noisy Data y', [0 1 (-20) (20)],[]);
versaplot(222,t,xhat,[],' 9 (b) VisuShrink Reconstruction',[0 1 (-20) (20)],[]);
subplot(223); PlotWaveCoeff(yw,HL,scal); title(' 9 (c) Haar[y]')
subplot(224); PlotWaveCoeff(xw,HL,scal); title(' 9 (d) Haar[Reconstruction]')
%% Part of Wavelab Version 850% Built Tue Jan 3 13:20:42 EST 2006% This is Copyrighted Material% For Copying permissions see COPYING.m% Comments? e-mail wavelab@stat.stanford.edu
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