图像质量评价matlab代码与参考文献大全（包含有参考和无参考图像质量评价，最新更新到2018）

Robust BRISQUE Software release. ======================================================================= -----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------ Copyright (c) 2011 The University of Texas at Austin All rights reserved. Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute this code (the source files) and its documentation for any purpose, provided that the copyright notice in its entirety appear in all copies of this code, and the original source of this code, Laboratory for Image and Video Engineering (LIVE, http://live.ece.utexas.edu) and Center for Perceptual Systems (CPS, http://www.cps.utexas.edu) at the University of Texas at Austin (UT Austin, http://www.utexas.edu), is acknowledged in any publication that reports research using this code. The research is to be cited in the bibliography as: 1) A. Mittal, A. K. Moorthy and A. C. Bovik, "Robust BRISQUE Software Release", URL: http://live.ece.utexas.edu/research/quality/robustbrisque.zip, 2012. 2) A. Mittal, A. K. Moorthy and A. C. Bovik, "Making image quality assessment robust", Forty-Sixth Annual Asilomar Conference on Signals, Systems, and Computers, Monterey, California, November 04-07, 2012 IN NO EVENT SHALL THE UNIVERSITY OF TEXAS AT AUSTIN BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OF THIS DATABASE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY OF TEXAS AT AUSTIN HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. THE UNIVERSITY OF TEXAS AT AUSTIN SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE DATABASE PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF TEXAS AT AUSTIN HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. -----------COPYRIGHT NOTICE ENDS WITH THIS LINE------------% Author : Anish Mittal Version : 1.0 The authors are with the Laboratory for Image and Video Engineering (LIVE), Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX. Kindly report any suggestions or corrections to mittal.anish@gmail.com ======================================================================= This is a demonstration of the Robust BRISQUE index. The algorithm is described in: A. Mittal, A. K. Moorthy and A. C. Bovik, "Making image quality assessment robust", Forty-Sixth Annual Asilomar Conference on Signals, Systems, and Computers, Monterey, California, November 04-07, 2012 You can change this program as you like and use it anywhere, but please refer to its original source (cite our paper and our web page at http://live.ece.utexas.edu/research/quality/robustbrisque_release.zip. ======================================================================= Running on Matlab Usage: Run main.m It asks for the path of LIVE database as input and outputs spearman and pearson correlation performance for each distortion category and all images together for 1000 train test combinations where the train and test combination as 80-20. It was made sure that the train and test content are disjoint. ============================================================================================================================================== MATLAB files: (provided with release): calculatepearsoncorr.m computefeatures.m lmom.m logistic_fun.m main.m trainandtest_live.m Dependencies (provided with release): 1) LIVE database aux files dmos.mat dmos_realigned.mat refnames_all.mat 2) train_test_splits_1000.mat for 1000 train-test combinations of LIVE IQA database. Dependencies (not provided with release): LIVE image database can be accessed here: http://live.ece.utexas.edu/research/quality/subjective.htm ======================================================================= This program uses LibSVM binaries. Below is the requried copyright notice for the binaries distributed with this release. ==================================================================== LibSVM tools: svm-train, svm-predict, svm-scale (binaries) -------------------------------------------------------------------- Copyright (c) 2000-2009 Chih-Chung Chang and Chih-Jen Lin All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither name of copyright holders nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ====================================================================