decdemo.m

NONSUBSAMPLED CONTOURLET TRANSFORM FILTER DESIGN AND APPLICATIONS

function coeffs = decdemo( im, option )
% DECDEMO   Demonstrates contourlet decomposition and reconstruction. 显示contourlet分解与重构
%
%   DECDEMO shows how to use the contourlet toolbox to decompose说明如何使用contourlet工具箱分解
%   and reconstruct an image. 重塑形象 It provides a sample script that uses 
%   basic functions such as pdfbdec, pdfbrec, showpdfb.
%
%   It can be modified for applications such as image analysis, 
%   image retrieval and image processing.
%
%   While displaying images, the program will pause and wait for your response.
%   When you are ready, you can just press Enter key to continue.
%
%       decdemo( [im, option] )
%
% Input:
%	image:  a double or integer matrix for the input image.
%           The default is the zoneplate image.
%   option: option for the demos. The default value is 'auto'
%       'auto' ------  automtatical demo, no input
%       'user' ------  semi-automatic demo, simple interactive inputs
%       'expert' ----  mannual, complete interactive inputs. 
%                      (Not implmented in this version)
%
% Output:
%	coeffs: a cell vector for the contourlet decomposition coefficients.
%   
% See also:     PDFBDEC, PDFBREC, SHOWPDFB

% History:
%   10/20/2003  Creation.
%   10/22/2003  Change the user interface for better image display.

disp('Welcome to the contourlet decomposition demo! :)');
disp('Type help decdemo for help' ) ;
disp('You can also view decdemo.m for details.') ;
disp(' ');

% Input image
if ~exist('im', 'var')
    % Zoneplate image: good for illustrating multiscale and directional
    % decomposition
    im = imread ('barbara.png') ;
end

% Show the input image
disp( 'Displaying the input image...');
clf;
imagesc(im, [0, 255]);
title( 'Input image' ) ;
axis image off;
colormap(gray);
input( 'Press Enter key to continue...' ) ;
disp( ' ' );


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Image decomposition by contourlets using the 
% pyramidal directional filter bank (PDFB).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Parameteters:
nlevels = [0, 2, 3, 4] ;        % Decomposition level
pfilter = 'pkva' ;              % Pyramidal filter
dfilter = 'pkva' ;              % Directional filter

% Contourlet decomposition
coeffs = pdfbdec( double(im), pfilter, dfilter, nlevels );

% Display the coefficients
disp('Displaying the contourlet coefficients...') ;
imcoeff = showpdfb( coeffs ) ;
title('Contourlet coefficients');
input('Press Enter key to continue...' ) ;
disp(' ');


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Pyramidal directional filter bank (PDFB) reconstruction.
% This is the inverse of pdfbdec, i.e.
% imrec = pdfbrec(coeffs, pfilter, dfilter);
% would reconstruct imrec = im
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Reconstruct image
imrec = pdfbrec( coeffs, pfilter, dfilter ) ;

disp('Displaying the reconstructed image...') ;
disp('It should be a perfect reconstruction' ) ;
disp(' ') ;

% Show the reconstruction image and the original image
subplot(1,2,1), imagesc( im, [0, 255] ); 
title('Original image' ) ;
axis image off;
subplot(1,2,2), imagesc( imrec, [0, 255] );
title('Reconstructed image' ) ;
axis image off;

mse = sum( sum( (imrec - double(im)).^2 ) );
mse = mse / prod(size(im));

disp( sprintf('The mean square error is: %f', mse ) );
disp(' ');