text_denoising.m

基于bandelet去噪的测试函数,并用信噪比进行评估

% test for denoising using the bandlet transform
%
%   Copyright (c) 2007 Gabriel Peyre

path(path, 'toolbox/');



n = 256;
M = imread('D:\personal\matlab\work\aa\earth_013.GIF');
m=0;
v=0.1;
M0=imnoise(M,'gaussian',m,v);
M=M0;
sigma=0.3;

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% TI Wavelets
clear options;
options.wavelet_type = 'biorthogonal';
options.wavelet_vm = 3;
Jmin = 4;
options.decomp_type = 'quad';
MW = perform_atrou_transform(M,Jmin,options);
disp('--> Computing best threshold (wavelets).');
Twav = compute_best_threshold(M,M0,sigma, options);
MWT = perform_thresholding(MW, T);
MW1 = perform_atrou_transform(MWT,Jmin,options);

nbr_scales = 3; % number of scale on witch geometry is computed
bandlet_type = 'atrou-quad';
switch bandlet_type
    case 'atrou-quad'
        callback = @callback_atrou;
        options.decomp_type = 'quad';
        Jband = 3*nbr_scales;
    case 'atrou-tri'
        callback = @callback_atrou;
        options.decomp_type = 'tri';
        Jband = 2*nbr_scales;
    case 'steerable'
        options.nb_orientations = 1;
        callback = @callback_atrou;
        Jband = options.nb_orientations*nbr_scales+1;
    case 'laplacian'
        callback = @callback_laplacian;
        Jband = nbr_scales;
    otherwise
        error('Unknown type.');
end
        

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% TI Bandlets
options.w = 8;
options.q = 8;  % for overlap set q=w/2, otherwise q=w
options.T = T;  % 10/256;
options.Jband = Jband; % number of scales for bandlets
options.Jhaar = 2; % number of scales for the 1D haar transform
options.callback = callback;
options.geometry_weight = 1; % price to pay for the geometry
options.n = n;

% use or not TI haar
options.ti = 1;

% compute the geometry for the bandlet transform
disp('--> Computing geometry.');
G = compute_geometry( M, options );
% forward transform
MB = perform_bandlet_transform( M, G, options );
% perform thresholding
disp('--> Computing best threshold (bandlets).');
Tband = compute_best_threshold(M,M0,sigma,options, G);
MBT = perform_thresholding(MB, Tband);
% reconstruct
MB1 = perform_bandlet_transform( MBT, G, options );


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%


pnoisy = psnr(M,M0);
pwav = psnr(M0,MW1);
pband = psnr(M0,MB1);



display_image_layout({M0 M MW1 MB1 }, ...
    {'Original' sprintf('Noisy,psnr=%.2f', pnoisy) sprintf('Wav,psnr=%.2f', pwav) ...
        sprintf('Band,psnr=%.2f(+%.2f)', pband, pband-pwav)  });