📄 mefig212.m
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% mefig212 -- Segmented vs. Ordinary de-noising; object "Ramp"
%
% In this display we compare segmented de-noising of figure 2.11
% with traditional de-noising using periodized nearly-symmetric wavelets
% having 8 vanishing moments.
%
% De-noising in a non-segmented wavelet transform domain leads to
% serious Gibbs phenomena. Such oscillation at discontinuities are
% avoided by de-noising with ideally-selected segmentation point.
%
global x yRamp L SmoothRamp
global Ramp % MRD 04/99
if (length(yRamp)==0)
warndlg('Please Run Figure 2.11 first and then run Fig. 2.12');
return;
end
%
qmf = MakeONFilter('Symmlet',8);
L=4;
%
wyRamp = FWT_PO(yRamp,L,qmf);
shRamp = MultiVisu(wyRamp,L);
sbRamp = IWT_PO(shRamp,L,qmf);
%
%clf;
subplot(221)
plot(x,sbRamp); title('2.12a Ordinary DeNoise[yRamp] ')
%
subplot(222)
plot(x,SmoothRamp); title('2.12b Seg-DeNoise[yRamp]')
sum((5*Ramp - SmoothRamp).^2)
sum((5*Ramp - sbRamp).^2)
%
%
% Prepared for the paper Minimum Entropy Segmentation
% Copyright (c) 1994 David L. Donoho
%
%% 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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