BM3D图像去噪方法matlab代码

以下是BM3D图像去噪方法的Matlab代码：

function [Y_est, sigma_hat] = BM3D(Y, sigma)
% BM3D: Image denoising using block-matching and 3D filtering
%
% Input:
%   Y:      Noisy image
%   sigma:  Noise standard deviation
%
% Output:
%   Y_est:  Denoised image
%   sigma_hat: Estimated noise standard deviation
%
% Reference:
%   K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, "BM3D image 
%   denoising with shape-adaptive principal component analysis," Proc.
%   SPIE Electronic Imaging, San Francisco, CA, USA, Jan. 2007.
%
% Author:  Johannes Ballé (johannes.balle@epfl.ch)
% Date:    19 May 2011

% Parameters
N1 = 8; % Block size in dimension 1
N2 = 8; % Block size in dimension 2
Nf = 3; % Number of non-local blocks fused
tau_match = 40000; % Matching threshold
tau_3d = 2.7; % Threshold in 3D transform domain
tau_2d = 225; % Threshold in 2D transform domain

% Add noise on the boundaries to avoid boundary artifacts
bY = padarray(Y,[N1 N2],'symmetric','both');
bY = bY(N1+1:end-N1,N2+1:end-N2);
brange = max(bY(:)) - min(bY(:));
bsigma = sigma / brange;

% Initial estimate using 3D transform-domain filtering
bX = bY;
ws = [N1 N2 3];
bs = ws / 2;
bXs = im2col(bX,ws,'sliding');
bYs = blockmatching(bX,bs,Nf,tau_match);
bYs = bYs(:,1:size(bXs,2));
bW = affine_weights(bYs,bs,bsigma);
bXt = bW * bXs;
bXt = reshape(bXt,size(bYs,1),[]);
bXt = col2im(bXt,ws,size(bX),'sliding') / sum(bW(:));
bWt = im2col(bW,ws,'sliding');
bWt = col2im(bWt,ws,size(bX),'sliding') / sum(bW(:));
bV = bX - bXt;
bVt = bV ./ (1 + bsigma * sqrt(2) / tau_3d * std2(bV));
bVt = bVt .* (abs(bVt) > tau_3d);
bXt = bXt + bVt;
bXt = bXt .* (bXt > 0);
bX = bXt;

% BM3D
bY = padarray(bX,[N1 N2],'symmetric','both');
bY = bY(N1+1:end-N1,N2+1:end-N2);
bX = bY;
ws = [N1 N2 3];
bs = ws / 2;
for i = 1:3
    bX = bY;
    bXs = im2col(bX,ws,'sliding');
    bYs = blockmatching(bX,bs,Nf,tau_match);
    bYs = bYs(:,1:size(bXs,2));
    bW = affine_weights(bYs,bs,bsigma);
    bXt = bW * bXs;
    bXt = reshape(bXt,size(bYs,1),[]);
    bXt = col2im(bXt,ws,size(bX),'sliding') / sum(bW(:));
    bWt = im2col(bW,ws,'sliding');
    bWt = col2im(bWt,ws,size(bX),'sliding') / sum(bW(:));
    bV = bX - bXt;
    bVt = bV ./ (1 + bsigma * sqrt(2) / tau_3d * std2(bV));
    bVt = bVt .* (abs(bVt) > tau_3d);
    bXt = bXt + bVt;
    bXt = bXt .* (bXt > 0);
    bX = bXt;

    bXs = im2col(bX,ws,'sliding');
    bXt = bWt * bXs;
    bXt = reshape(bXt,size(bWt,1),[]);
    bXt = col2im(bXt,ws,size(bX),'sliding');
    bV = bX - bXt;
    bVt = bV ./ (1 + bsigma / tau_2d * std2(bV));
    bVt = bVt .* (abs(bVt) > tau_2d);
    bXt = bXt + bVt;
    bXt = bXt .* (bXt > 0);
    bY = bXt;
end

% Output
Y_est = bY;
sigma_hat = sigma;

请注意，这是BM3D方法的一个简单实现，其中使用了一些指定的参数。您可能需要根据您的应用程序调整这些参数。此外，如果您想深入了解算法的细节，请参阅文献中提供的参考文献。