classdef SSIMImageMetricItem < MetricItem
    methods
        function obj=SSIMImageMetricItem
            obj=obj@MetricItem('SSIM');
        end
        
        
        function val=calc(obj,item1,item2)
            fprintf('Calculating SSIM ... \n');
            A1=uint8(imread(item1.getfilename));
            A2=uint8(imread(item2.getfilename));
            if size(A1,3)>1
                A1=rgb2gray(A1);
            end
            if size(A2,3)>1
                A2=rgb2gray(A2);
            end
            [val, ssim_mapy] = ssim(A1,A2);
        end
        
        function [mssim, ssim_map] = ssim(img1, img2, K, window, 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 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 = 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
            
        end
    end
    
end