基于Gabor特征的屏幕内容图像质量评估模型Matlab源码.zip

function [score, SimMatrix] = GFM(Im1,Im2) % ======================================================================== % GFM Index for SCI, Version 1.0 % Copyright(c) 2017 Zhangkai Ni, Huanqiang Zeng, Lin Ma, Junhui Hou, % Jing Chen, and Kai-Kuang Ma % All Rights Reserved. % % ---------------------------------------------------------------------- % Permission to use, copy, or modify this software and its documentation % for educational and research purposes only and without fee is here % 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 % Gabor features-basedmodel (GFM) index between two images. % % Please refer to the following paper % % Z. Ni, H. Zeng, L. Ma, J. Hou, J. Chen, and K.-K. Ma, ��A Gabor % Feature-based Quality Assessment Model for the Screen Content Images,�� % IEEE Transactions on Image Processing, 2018. % %---------------------------------------------------------------------- % %Input : (1) Im1: the first image being compared, which is a RGB image % (2) Im2: the second image being compared, which is a RGB image % %Output: (1) score: is the similarty score calculated using GFM algorithm. % GFM considers the luminance component and chrominance component of images. % % (2) SimMatrix: is the local quality map of the distorted image % %----------------------------------------------------------------------- % %Usage: %Given 2 test images img1 and img2. For gray-scale images, their dynamic range should be 0-255. %For colorful images, the dynamic range of each color channel should be 0-255. % %[score, SimMatrix] = GFM(img1, img2); %----------------------------------------------------------------------- %%%%% Transform into an opponent color space L1 = 0.06 * double(Im1(:,:,1)) + 0.63 * double(Im1(:,:,2)) + 0.27 * double(Im1(:,:,3)); L2 = 0.06 * double(Im2(:,:,1)) + 0.63 * double(Im2(:,:,2)) + 0.27 * double(Im2(:,:,3)); M1 = 0.30 * double(Im1(:,:,1)) + 0.04 * double(Im1(:,:,2)) - 0.35 * double(Im1(:,:,3)); M2 = 0.30 * double(Im2(:,:,1)) + 0.04 * double(Im2(:,:,2)) - 0.35 * double(Im2(:,:,3)); N1 = 0.34 * double(Im1(:,:,1)) - 0.60 * double(Im1(:,:,2)) + 0.17 * double(Im1(:,:,3)); N2 = 0.34 * double(Im2(:,:,1)) - 0.60 * double(Im2(:,:,2)) + 0.17 * double(Im2(:,:,3)); %%%%%%%%%%%%%%%% To = 330; Tc = 100; lambda = 0.04; a2 = oddspatialgabor(L1,5,0,0.43,0.03); a5 = oddspatialgabor(L1,5,90,0.43,0.03); GO1 = a2 + a5; b2 = oddspatialgabor(L2,5,0,0.43,0.03); b5 = oddspatialgabor(L2,5,90,0.43,0.03); GO2 = b2 + b5; Pm = max(abs(GO1), abs(GO2)); GoSimMatrix = (2 * GO1 .* GO2 + To) ./(GO1.^2 + GO2.^2 + To); ISimMatrix = (2 * M1 .* M2 + Tc) ./ (M1.^2 + M2.^2 + Tc); QSimMatrix = (2 * N1 .* N2 + Tc) ./ (N1.^2 + N2.^2 + Tc); SimMatrix = GoSimMatrix .* real((ISimMatrix .* QSimMatrix) .^ lambda); score = sum(SimMatrix(:).* Pm(:))/sum(Pm(:));