% scfig06 -- Short Course 06: Wavelet Shrinkage of the Four Noisy Signals
%
% Here we aapply a specific thresholding rule to the
% four noisy signals depicted in Figure 5.
%
% The procedure for DeNoising:
%       1.  Transform to Wavelet Domain, Using Nearly Symmetric Wavelet
%           with 8 vanishing moments.
%       2.  Apply a soft thresholding nonlinearity, with threshold set to
%           sqrt{2 log(n)}
%       3.  Transform back to the signal domain.
% 
% The reconstructions suppress the noise, while preserving the sharp structure
% in the neighborhood of the highly-variable spatial components.
%
global yblocks ybumps yheavi yDoppler
global t
%
	QMF_Filter = MakeONFilter('Symmlet',8);
	L = 5;
%
	[xhblocks]  = WaveShrink(yblocks, 'Visu',L,QMF_Filter);
	[xhbumps]   = WaveShrink(ybumps,  'Visu',L,QMF_Filter);
	[xhheavi]   = WaveShrink(yheavi,  'Visu',L,QMF_Filter);
	[xhDoppler] = WaveShrink(yDoppler,'Visu',L,QMF_Filter);
%
% 	clf;
	versaplot(221,t,xhblocks, [],' 6 (a) VisuShrink[yBlocks] '   ,[],[])
	versaplot(222,t,xhbumps,  [],' 6 (b) VisuShrink[yBumps] '    ,[],[])
	versaplot(223,t,xhheavi,  [],' 6 (c) VisuShrink[yHeaviSine] ',[],[])
	versaplot(224,t,xhDoppler,[],' 6 (d) VisuShrink[yDoppler] '  ,[],[])

 
% Revision History
%  10/1/05          AM            Name of the variable QMF is changed to
%                                 QMF_Filter
    
    
    
 
 
%
%  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 
