testbestpartition.m

beamlet变化的工具箱

function TestBestPartition(name,D,Entropy,EntPar)



% 

% Ridgelet Packet Analysis in Adaptively Chosen Basis

%  

%  Inputs

%    name        name of a 2-d image (loaded from WaveLab); size n by n, n dyadic

%                Allowed names are 'Barton', 'Canaletto', 'Coifman', 'Daubechies',...

%             'Fingerprint', 'Lincoln', 'Lenna', 'MRIScan', 'Phone'    

%     D          D = [D1,D2] maximum depth of splitting -- Range D1=2,3,4,5,6; D2=2,3,4,5,6;

%    Entropy    type of entropy to record in tree: options are

%                   'Entropy' -- Coifman-Wickerhauser

%                   'Log'	 -- sum log |th_i|		

%                   'l^p'     -- sum |th_i|^p, 0 < p < 2, p = par

%                   'N(eps)'  -- #>= eps, eps = par

%                   'Risk'    -- sum min(th_i^2,eps^2), eps=par

%                   'Sum'     -- sum th_i

%                   'SURE'    -- SURE(Thresholding), thresh = par

%    EntPar     extra parameter, depends on type of entropy$

%

%  Description

%    Perform an adaptive anisotropic Radial Polar packet analysis on the given image,

%    selecting the best anisotropic partitioning basis then plotting the RP coefficients

%    for this basis along with the image overlaid by its 2-d polar partition.

%

%Example TestBestPart('Lenna',[3,3],'l^p',1.5)


% check input parameters

	if nargin < 3

		error('Usage:  TestBestPartition(name,D,Entropy[,EntPar])');

	end;

	if nargin < 4,

		EntPar=[];

	end

%

	if length(D)==1,

		D = [ D D];

	end

%------------------------------------------

% to supress the output text by ReadImage.m

global WLVERBOSE        %set by BeamPath.m

WLVERBOSE = 'No';

%------------------------------------------

im   = ReadImage(name);

[s1,s2]=size(im);
if s1~=s2
    if min(s1,s2)<=256
    im = im(1:min(s1,s2),1:min(s1,s2));
else
    im = im(1:256,1:256);
end
end




subplot(1,3,1)

imagesc(im)

axis image;set (gca,'XTick',[]);

set (gca,'YTick',[]);

   



im = im ./max(im(:));

img0  = im - mean(mean(im));



RPFTGlobal= fft2_rp(img0);

RPFTGlobalShow = RPFTGlobal([2:size(RPFTGlobal,1)/2+1,size(RPFTGlobal,1)/2+1:size(RPFTGlobal,1)],:);



FFTGlobal  = fftshift(fft2(im));

FFTGlobalShow = FFTGlobal([2:size(FFTGlobal,1)/2+1,size(FFTGlobal,1)/2+1:size(FFTGlobal,1)],:);





% build a best basis for this image

RPPkt = CalcRPPktTable(RPFTGlobal,D,'Sine');

RPtree  = CalcRPStatTree(RPPkt,D,Entropy,EntPar);

bb    = BestRPBasis(RPtree,D); 



subplot(1,3,2)

AutoImageInv(abs(RPFTGlobalShow));

Polrax = axis; hold on;

PlotRPPartition(bb,'r',Polrax,D); 



% calculate statistics

coef  = FPT2_RPkt(bb,img0,D);

e = CalcEntropy(coef,Entropy,EntPar);



set(gca,'XTick',[]);

set(gca,'YTick',[]);



% show the fft domain with the best bases



subplot(1,3,3)

AutoImageInv(log(1+abs(FFTGlobalShow)));

Polrax = axis; hold on;

PlotRectoPolarRPPartition(bb,'r',Polrax,D);

set(gca,'XTick',[]);

set(gca,'YTick',[]);



colormap(hot)



%------------------

WLVERBOSE = 'Yes';

%------------------

%
% Part of BeamLab Version:200
% Built:Friday,23-Aug-2002 00:00:00
% This is Copyrighted Material
% For Copying permissions see COPYING.m
% Comments? e-mail [e-mail]
%
%
% Part of BeamLab Version:200
% Built:Saturday,14-Sep-2002 00:00:00
% This is Copyrighted Material
% For Copying permissions see COPYING.m
% Comments? e-mail [e-mail]
%