📄 adfig10.m
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% adfig10 -- Adapt Figure 10: Wavelet Shrinkage 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 t
global yblocks
%
HQMF = MakeONFilter('Haar');
HL = 3;
[xhat,xw] = WaveShrink(yblocks,'Hybrid',HL,HQMF);
yw = FWT_PO(yblocks,HL,HQMF);
%clf;
ax = [ 0 1 (-10) 30];
%
versaplot(221,t,yblocks,[],' 10 (a) Noisy Data y' ,ax,[]);
versaplot(222,t,xhat ,[],' 10 (b) HaarShrink Reconstruction',ax,[]);
subplot(223); IMJPlotWaveCoeff(yw,HL,.025); title(' 10 (c) Haar[y]')
subplot(224); IMJPlotWaveCoeff(xw,HL,.025); title(' 10 (d) Haar[Reconstruction]')
%% Part of Wavelab Version 850% Built Tue Jan 3 13:20:41 EST 2006% This is Copyrighted Material% For Copying permissions see COPYING.m% Comments? e-mail wavelab@stat.stanford.edu
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