FRIQUEE Software release. ======================================================================== -----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------ Copyright (c) 2016 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) D. Ghadiyaram and A. C. Bovik, "FRIQUEE Software Release" URL: http://live.ece.utexas.edu/research/quality/FRIQUEE_release.zip, 2016 2) D. Ghadiyaram and A. C. Bovik, "Perceptual Quality Prediction on Authentically Distorted Images Using a Bag of Features Approach," http://arxiv.org/abs/1609.04757 (under review) 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 : Deepti Ghadiyaram 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 deeptigp9@gmail.com ======================================================================== This is a demonstration of a new Feature Maps Driven No-Reference Image Quality Evaluator Engine (FRIQUEE) The algorithm is described in detail in : D. Ghadiyaram and A. C. Bovik, "Perceptual Quality Prediction on Authentically Distorted Images Using a Bag of Features Approach," http://arxiv.org/abs/1609.04757 (under review) You can change this program as you like and use it anywhere, but please refer to its original source cite our paper as given below: D. Ghadiyaram and A. C. Bovik, "Perceptual Quality Prediction on Authentically Distorted Images Using a Bag of Features Approach," http://arxiv.org/abs/1609.04757 (under review) ======================================================================== Running on Matlab Input : A test image loaded in a 3 dimensional array Output: a) A set of 560 image quality features (FRIQUEE-ALL features, as described in the paper) b) A quality score of the image. The score typically has a value between 0 and 100 (0 represents the worst quality, 100 the best). Usage: Please see example.m for details on how to use this script Dependencies: We are also making a trained model publicly available. This model is trained on all the 1162 test images of the LIVE-Challenge Database using a Support Vector Regressor (SVR) with a radial basis function. The parameters used for training arE: C (cost) = 2^8; gamma = 2^-6; Binaries: - Two mex files svmpredict and svmtrain are also provided with the release. These are compiled on a UNIX environment. If you are on a different OS, please download LIBSVM and compile the files appropriately. ======================================================================== Note on training: This release version of FRIQUEE was trained on the entire LIVE database. This program uses LibSVM binaries. Below is the requried copyright notice for the binaries distributed with this release. ==================================================================== LibSVM tools: svmpredict, svmtrain (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. ====================================================================