Subjective
Image Quality Assessment
LIVE Image Quality
Assessment Database
The Quality
Assessment research at LIVE is being conducted in collaboration
with CPS
Introduction
Quality Assessment research strongly depends upon
subjective experiments to provide calibration data as well as
a testing mechanism. After all, the goal of all QA research
is to make quality predictions that are in agreement
with subjective opinion of human observers. In order to calibrate
QA algorithms and test their performance, a data set of images
and videos whose quality has been ranked by human subjects is
required. The QA algorithm may be trained on part of this data
set, and tested on the rest.
At LIVE (in collaboration with The Department
of Psychology at the University of Texas at Austin), an extensive
experiment was conducted to obtain scores from human subjects
for a number of images distorted with different distortion types.
These images were acquired in support of a research project
on generic shape matching and recognition.
We have decided
to make the data set available to the research community free
of charge. If
you use these images in your research, we kindly ask that you
reference this website and our papers listed below.
- H.R. Sheikh, Z.Wang, L. Cormack and A.C. Bovik, "LIVE Image
Quality Assessment Database Release 2", http://live.ece.utexas.edu/research/quality.
- H.R. Sheikh, M.F. Sabir and A.C. Bovik, "A statistical
evaluation of recent full reference image quality assessment
algorithms", IEEE Transactions on Image Processing,
vol. 15, no. 11, pp. 3440-3451, Nov. 2006.
- Z. Wang, A.C. Bovik, H.R. Sheikh and E.P. Simoncelli, "Image
quality assessment: from error visibility to structural similarity,"
IEEE Transactions on Image Processing , vol.13, no.4,
pp. 600- 612, April 2004.
Please scroll to
the end of the page to download the data set.
Subjective experiments are cumbersome to design
and expensive. Although great care was taken to ensure that
the testing environment was as close to the "real-world" as
possible, we cannot claim that our subjective experiments were
exhaustive, comprehensive, or precise in every respect. Hence,
any research conducted with the database should consider the
limitations imposed by the scope and methodology of our experiments.
Please contact Anish Mittal (mittal.anish@gmail.com)
if you have any questions.
The investigators on this research were:
Dr. Hamid Rahim
Sheikh (hamid.sheikh@ieee.org)
-- Formerly a student at the Department of ECE at UT Austin
Dr.
Alan C. Bovik (bovik@ece.utexas.edu)
-- Department of ECE at UT Austin
Dr.
Lawrence Cormack (cormack@psy.utexas.edu)
-- Department of Psychology at UT Austin
Dr. Zhou Wang
(zhouwang@ieee.org) -- Formerly a student at the Department
of ECE at UT Austin
What's
new in Release 2
Release 2 has the following differences from Release
1:
-
More distortion types:
-
JPEG compresses images (169 images). More
subjects than in Release 1
-
JPEG2000 compressed images (175 images)
-
NEW! Gaussian blur (145 images)
-
NEW! White noise (145 images)
-
NEW! Bit errors in JPEG2000 bit stream (145
images)
-
More subjects for JPEG distortion
-
DMOS values instead of MOS values for distorted
images
-
Different processing of raw scores than in
Release 1
-
Individual subject scores and source code
for processing raw scores will be released later.
Please read the readme.txt in the database release
for more details about the database.
Download Release
2
Subjective database
Release 2.
Please fill THIS
form and the password will be sent to you.
If you download the database,
it is assumed that you agree to the
copyright notice
Update to Release
2
Download realigned subjective quality data here.
This data was obtained by running realignment experiments on
Release 2 data. The details of the experiment can be found in
the paper.
H. R. Sheikh, M. F. Sabir, A. C. Bovik, "A Statistical
Evaluation of Recent Full Reference Quality Assessment Algorithms",
IEEE Transactions on Image Processing, vol. 15, no.
11, pp. 3440-3451, Nov. 2006.
Download Release
1
Subjective
database for JPEG2000 - README.TXT.
Subjective database
for JPEG - README.TXT.
Please fill THIS
form and the password will be sent to you.
If you download the database,
it is assumed that you agree to the
copyright notice
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