bm3d.m

BM3D去噪算法的实现和相关文档

function [PSNR, y_est] = BM3D(y, z, sigma, profile, print_to_screen)
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%
%  BM3D is algorithm for attenuation of additive white Gaussian noise from 
%  grayscale images. This algorithm reproduces the results from the article:
%
%  [1] K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, "Image denoising 
%   by sparse 3D transform-domain collaborative filtering," 
%   IEEE Transactions on Image Processing, December, 2006, in review,
%   preprint at http://www.cs.tut.fi/~foi/GCF-BM3D.
%
%  FUNCTION INTERFACE:
%
%  [PSNR, y_est] = BM3D(y, z, sigma, profile, print_to_screen)
%
%  ! The function can work without any of the input arguments, 
%   in which case, the internal default ones are used !
% 
%  BASIC USAGE EXAMPLES:
%
%     Case 1) Using the default parameters (i.e., image name, sigma, etc.)
% 
%      [PSNR, y_est] = BM3D;
% 
%     Case 2) Using an external noisy image:
%
%      % Read a grayscale image and scale its intensities in range [0,1]
%      y = im2double(imread('Cameraman256.png')); 
%      % Generate the same seed used in the experimental results of [1]
%      randn('seed', 0);
%      % Standard deviation of the noise --- corresponding to intensity 
%      %  range [0,255], despite that the input was scaled in [0,1]
%      sigma = 25;
%      % Add the AWGN with zero mean and standard deviation 'sigma'
%      z = y + (sigma/255)*randn(size(y));
%      % Denoise 'z'. The denoised image is 'y_est', and 'NA = 1' because 
%      %  the true image was not provided
%      [NA, y_est] = BM3D(1, z, sigma); 
%      % Compute the putput PSNR
%      PSNR = 10*log10(1/mean((y(:)-y_est(:)).^2))
%      % show the noisy image 'z' and the denoised 'y_est'
%      figure; imshow(z);   
%      figure; imshow(y_est);
% 
%     Case 3) If the original image y is provided as the first input 
%      argument, then some additional information is printed (PSNRs, 
%      figures, etc.). That is, "[NA, y_est] = BM3D(1, z, sigma);" in the
%      above code should be replaced with:
% 
%      [PSNR, y_est] = BM3D(y, z, sigma);
% 
% 
%  INPUT ARGUMENTS (OPTIONAL):
%
%     1) y (matrix M x N): Noise-free image (needed for computing PSNR),
%                           replace with the scalar 1 if not available.
%     2) z (matrix M x N): Noisy image (intensities in range [0,1] or [0,255])
%     3) sigma (double)  : Std. dev. of the noise (corresponding to intensities
%                          in range [0,255] even if the range of z is [0,1])
%     4) profile (char)  : 'np' --> Normal Profile 
%                          'lc' --> Fast Profile
%     5) print_to_screen : 0 --> do not print output information (and do 
%                                not plot figures)
%                          1 --> print information and plot figures
%
%  OUTPUTS:
%     1) PSNR (double)          : Output PSNR (dB), only if the original 
%                                 image is available, otherwise PSNR = 0                                               
%     2) y_est (matrix M x N): Final estimate (in the range [0,1])
%
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% Copyright