Anyone can teach me about SSIM.m?

Hi,I'm new to Matlab and i need a method to compare the quality of the images.

I heard about SSIM and i have the code downloaded from the web as well. However i do not understand how it works. How can i choose the images that i want to compare and what is the parameters means. I have tried to include img1=imread('filename') and img2 but the results is -Inf. Anyone can help me?

The code are like:

    function [mssim, ssim_map] = ssim(img1, img2, K, window, L)%might delete k window n L

% ========================================================================
% SSIM Index with automatic downsampling, Version 1.0
% Copyright(c) 2009 Zhou Wang
% All Rights Reserved.
%
% ----------------------------------------------------------------------
% Permission to use, copy, or modify this software and its documentation
% for educational and research purposes only and without fee is hereby
% granted, provided that this copyright notice and the original authors'
% names appear on all copies and supporting documentation. This program
% shall not be used, rewritten, or adapted as the basis of a commercial
% software or hardware product without first obtaining permission of the
% authors. The authors make no representations about the suitability of
% this software for any purpose. It is provided "as is" without express
% or implied warranty.
%----------------------------------------------------------------------
%
% This is an implementation of the algorithm for calculating the
% Structural SIMilarity (SSIM) index between two images
%
% Please refer to the following paper and the website with suggested usage
%
% Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image
% quality assessment: From error visibility to structural similarity,"
% IEEE Transactios on Image Processing, vol. 13, no. 4, pp. 600-612,
% Apr. 2004.
%
% http://www.ece.uwaterloo.ca/~z70wang/research/ssim/
%
% Note: This program is different from ssim_index.m, where no automatic
% downsampling is performed. (downsampling was done in the above paper
% and was described as suggested usage in the above website.)
%
% Kindly report any suggestions or corrections to [e-mail]
%
%----------------------------------------------------------------------
%
%Input : (1) img1: the first image being compared
%        (2) img2: the second image being compared
%        (3) K: constants in the SSIM index formula (see the above
%            reference). defualt value: K = [0.01 0.03]
%        (4) window: local window for statistics (see the above
%            reference). default widnow is Gaussian given by
%            window = fspecial('gaussian', 11, 1.5);
%        (5) L: dynamic range of the images. default: L = 255
%
%Output: (1) mssim: the mean SSIM index value between 2 images.
%            If one of the images being compared is regarded as 
%            perfect quality, then mssim can be considered as the
%            quality measure of the other image.
%            If img1 = img2, then mssim = 1.
%        (2) ssim_map: the SSIM index map of the test image. The map
%            has a smaller size than the input images. The actual size
%            depends on the window size and the downsampling factor.
%
%Basic Usage:
%   Given 2 test images img1 and img2, whose dynamic range is 0-255
%
%   [mssim, ssim_map] = ssim(img1, img2);
%
%Advanced Usage:
%   User defined parameters. For example
%
%   K = [0.05 0.05];
%   window = ones(8);
%   L = 100;
%   [mssim, ssim_map] = ssim(img1, img2, K, window, L);
%
%Visualize the results:
%
%   mssim                        %Gives the mssim value
%   imshow(max(0, ssim_map).^4)  %Shows the SSIM index map
%========================================================================

if (nargin < 2 || nargin > 5)
   mssim = -Inf;
   ssim_map = -Inf;
   return;
end

if (size(img1) ~= size(img2))
   mssim = -Inf;
   ssim_map = -Inf;
   return;
end

[M N] = size(img1);

if (nargin == 2)
   if ((M < 11) || (N < 11))
     mssim = -Inf;
     ssim_map = -Inf;
      return
   end
   window = fspecial('gaussian', 11, 1.5);  %
   K(1) = 0.01;          % default settings
   K(2) = 0.03;          %
   L = 255;                                     %
end

if (nargin == 3)
   if ((M < 11) || (N < 11))
     mssim = -Inf;
     ssim_map = -Inf;
      return
   end
   window = fspecial('gaussian', 11, 1.5);
   L = 255;
   if (length(K) == 2)
      if (K(1) < 0 || K(2) < 0)
       mssim = -Inf;
       ssim_map = -Inf;
       return;
      end
   else
     mssim = -Inf;
     ssim_map = -Inf;
     return;
   end
end

if (nargin == 4)
   [H W] = size(window);
   if ((H*W) < 4 || (H > M) || (W > N))
     mssim = -Inf;
     ssim_map = -Inf;
      return
   end
   L = 255;
   if (length(K) == 2)
      if (K(1) < 0 || K(2) < 0)
       mssim = -Inf;
       ssim_map = -Inf;
       return;
      end
   else
     mssim = -Inf;
     ssim_map = -Inf;
     return;
   end
end

if (nargin == 5)
   [H W] = size(window);
   if ((H*W) < 4 || (H > M) || (W > N))
     mssim = -Inf;
     ssim_map = -Inf;
      return
   end
   if (length(K) == 2)
      if (K(1) < 0 || K(2) < 0)
       mssim = -Inf;
       ssim_map = -Inf;
       return;
      end
   else
     mssim = -Inf;
     ssim_map = -Inf;
     return;
   end
end

img1 = double(img1);
img2 = double(img2);

% automatic downsampling
f = max(1,round(min(M,N)/256));
%downsampling by f
%use a simple low-pass filter 
if(f>1)
    lpf = ones(f,f);
    lpf = lpf/sum(lpf(:));
    img1 = imfilter(img1,lpf,'symmetric','same');
    img2 = imfilter(img2,lpf,'symmetric','same');

      img1 = img1(1:f:end,1:f:end);
      img2 = img2(1:f:end,1:f:end);
  end

C1 = (K(1)*L)^2;
C2 = (K(2)*L)^2;
window = window/sum(sum(window));

mu1   = filter2(window, img1, 'valid');
mu2   = filter2(window, img2, 'valid');
mu1_sq = mu1.*mu1;
mu2_sq = mu2.*mu2;
mu1_mu2 = mu1.*mu2;
sigma1_sq = filter2(window, img1.*img1, 'valid') - mu1_sq;
sigma2_sq = filter2(window, img2.*img2, 'valid') - mu2_sq;
sigma12 = filter2(window, img1.*img2, 'valid') - mu1_mu2;

if (C1 > 0 && C2 > 0)
   ssim_map = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))./((mu1_sq + mu2_sq + C1).*(sigma1_sq + sigma2_sq + C2));
else
   numerator1 = 2*mu1_mu2 + C1;
   numerator2 = 2*sigma12 + C2;
  denominator1 = mu1_sq + mu2_sq + C1;
   denominator2 = sigma1_sq + sigma2_sq + C2;
   ssim_map = ones(size(mu1));
   index = (denominator1.*denominator2 > 0);
   ssim_map(index) = (numerator1(index).*numerator2(index))./(denominator1(index).*denominator2(index));
   index = (denominator1 ~= 0) & (denominator2 == 0);
   ssim_map(index) = numerator1(index)./denominator1(index);
end

mssim = mean2(ssim_map);

return

[Anu Lajide]

Hi Jin, any solution to your question? I am in the samee dilemma as you and no understanding of how to use the SSIM code to carry out my comparison test

Answer 1

[Wayne King]

Have you read the paper and worked through the demos on the authors' website?

http://www.ece.uwaterloo.ca/~z70wang/research/ssim/

It looks like they have gone to great lengths there to make material public.

[Yipeng Liu]

Do you know why there are negative value in the ssim_map using the SSIM_index.m? It is not consistent to the paper description.

Thank you!