Welcome to the LIVE Public-Domain Subjective Multiply Distorted Image Quality Database
LIVE Multiply Distorted Image Quality Database
Introduction
Subjective studies have been conducted in the past to obtain human judgments of visual quality on distorted images in order, among other things, to benchmark objective image quality assessment (IQA) algorithms. Existing subjective studies primarily have records of human ratings on images that were corrupted by only one of many possible distortions. However, images available to consumers usually reaches them after several stages - acquisition, compression, transmission and reception. In this pipeline, they may suffer multiple distortions. Towards broadening the corpora of records of human responses to visual distortions, we recently conducted a study on two types of multiply distorted images to obtain human judgments of the visual quality of such images.
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We are making the LIVE Multiply Distorted Image Quality Database available to the research community free of charge. If you use this database in your research, we kindly ask that you reference our papers listed below:
Dinesh Jayaraman, Anish Mittal, Anush K. Moorthy and Alan C. Bovik, Objective Quality Assessment of Multiply Distorted Images, Proceedings of Asilomar Conference on Signals, Systems and Computers, 2012.
Database can be obtained from the following link: Database Release .
Database is password protected, please fill THIS form and the information will be sent to you.
Database Description
A subjective study was conducted in two parts to obtain human judgments on images corrupted under two multiple distortion scenarios: 1) image storage where images are first blurred and then compressed by a JPEG encoder. 2) camera image acquisition process where images are first blurred due to narrow depth of field or other defocus and then corrupted by white Gaussian noise to simulate sensor noise.
Investigators
Quality Assessment research at LIVE is being conducted in collaboration with the Video Aware Wireless Networks ( VAWN ) program of the Intel & Cisco.
The investigators in this research are:
- Dinesh Jayaraman ( dinesh.jayaraman123@gmail.com ) -- Graduate student UT Austin in 2012
- Anish Mittal ( mittal.anish@gmail.com ) – Graduate student at UT Austin
- Dr. Anush K. Moorthy ( anushmoorthy@gmail.com ) -- Graduated from UT Austin in 2012
- Dr. Alan C. Bovik ( bovik@ece.utexas.edu ) -- Professor, Dept. of ECE, UT Austin
Copyright Notice
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Copyright (c) 2012 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 database (the images, the results and the source files) and its documentation for any purpose, provided that the copyright notice in its entirety appear in all copies of this database, and the original source of this database, 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 database.
The following papers are to be cited in the bibliography whenever the database is used as:
· Dinesh Jayaraman, Anish Mittal, Anush K. Moorthy and Alan C. Bovik, Objective Quality Assessment of Multiply Distorted Images, Proceedings of Asilomar Conference on Signals, Systems and Computers, 2012.
· URL: http://live.ece.utexas.edu/research/quality/live_multidistortedimage.html
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.
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