📄 wp2dtour.m
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function [bb,stats,coef] = WP2dTour(img,MaxDeep,qmf,titlestr)
% WP2dTour -- 2d Wavelet Packet Analysis in Adaptively Chosen Basis
% Usage
% [bb,stats,coef] = WP2dTour(img,MaxDeep,qmf[,titlestr])
% Inputs
% img 2-d image; size n by n, n dyadic
% MaxDeep integer; limit on max depth of tree in best basis search
% qmf quadrature mirror filter
% titlestr string; name of signal
% Outputs
% bb basis quadtree of best basis
% stats stat quadtree of best basis
% coef coefficients in best basis
%
% Description
% Perform an adaptive wavelet packet analysis on the given image,
% selecting the best basis and then plotting the WP coefficients
% for this basis along with the image overlaid by its 2-d partition.
%
if nargin < 4
titlestr = '';
end
%
img0 = img - mean(mean(img));
stats = Calc2dStatTree('WP',img0,MaxDeep,qmf,'Entropy',[]);
bb = Best2dBasis(stats,MaxDeep);
coef = FPT2_WP(bb,img,qmf);
%
AutoImage(abs(coef));
ax = axis; hold;
Plot2dPartition(bb,'y',ax,MaxDeep); drawnow;
title(sprintf('Coeff in WP BestBasis; %s',titlestr));
%% 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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