NDLI: No-reference quality assessment using natural scene statistics: JPEG2000

Content Provider	IEEE Xplore Digital Library
Author	Sheikh, H.R. Bovik, A.C. Cormack, L.
Copyright Year	1992
Abstract	Measurement of image or video quality is crucial for many image-processing algorithms, such as acquisition, compression, restoration, enhancement, and reproduction. Traditionally, image quality assessment (QA) algorithms interpret image quality as similarity with a "reference" or "perfect" image. The obvious limitation of this approach is that the reference image or video may not be available to the QA algorithm. The field of blind, or no-reference, QA, in which image quality is predicted without the reference image or video, has been largely unexplored, with algorithms focussing mostly on measuring the blocking artifacts. Emerging image and video compression technologies can avoid the dreaded blocking artifact by using various mechanisms, but they introduce other types of distortions, specifically blurring and ringing. In this paper, we propose to use natural scene statistics (NSS) to blindly measure the quality of images compressed by JPEG2000 (or any other wavelet based) image coder. We claim that natural scenes contain nonlinear dependencies that are disturbed by the compression process, and that this disturbance can be quantified and related to human perceptions of quality. We train and test our algorithm with data from human subjects, and show that reasonably comprehensive NSS models can help us in making blind, but accurate, predictions of quality. Our algorithm performs close to the limit imposed on useful prediction by the variability between human subjects.
Sponsorship	IEEE Signal Processing Society
Page Count	10
File Size	677483
Starting Page	1918
Ending Page	1927
File Format	PDF
ISSN	10577149
Volume Number	14
Issue Number	11
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Quality assessment Layout Statistics Video compression Image coding Image quality Humans Transform coding Distortion measurement Image restoration no reference (NR) image QA Blind quality assessment (QA) image QA JPEG2000 natural scene statistics (NSS)
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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