图像清晰度评价指标Matlab 熵、交叉熵、峰值信噪比、Qabf、平均梯度、SSIM、互信息、NMI.zip

function ssim % ======================================================================== % SSIM Index with automatic downsampling, Version 1.0 % Copyright(c) 2009 Zhou Wang % All Rights Reserved. % % ---------------------------------------------------------------------- % 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 %======================================================================== [name,path]=uigetfile({'*.*','请选择原图像'},'请打开原图像'); file1=strcat(path,name); [name,path]=uigetfile({'*.*','请选择融合图像F'},'请打开融合图像F'); file2=strcat(path,name); img1=imread(file1); img2=imread(file2); if size(img1,3)==3 img1=rgb2gray(img1); end if size(img2,3)==3 img2=rgb2gray(img2); end [M N] = size(img1); img1 = double(img1); img2 = double(img2); K = [0.01 0.03]; window = fspecial('gaussian', 11, 1.5);L = 255; % 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 SSIM = mean2(ssim_map)