NDLI: A Fast Approach for No-Reference Image Sharpness Assessment Based on Maximum Local Variation

Content Provider	IEEE Xplore Digital Library
Author	Bahrami, K. Kot, A.C.
Copyright Year	1994
Abstract	This letter proposes a simple and fast approach for no-reference image sharpness quality assessment. In this proposal, we define the maximum local variation (MLV) of each pixel as the maximum intensity variation of the pixel with respect to its 8-neighbors. The MLV distribution of the pixels is an indicative of sharpness. We use standard deviation of the MLV distribution as a feature to measure sharpness. Since high variations in the pixel intensities is a better indicator of the sharpness than low variations, the MLV of the pixels are subjected to a weighting scheme in such a way that heavier weights are assigned to greater MLVs to make the tail end of MLV distribution thicker. The weighting leads to an improvement of the MLV distribution to be more discriminative for different blur degrees. Finally, the standard deviation of the weighted MLV distribution is used as a metric to measure sharpness. The proposed approach has a very low computational complexity and the performance analysis shows that our approach outperforms the state-of-the-art techniques in terms of correlation with human vision system on several commonly used databases.
Sponsorship	IEEE Signal Processing Society
Starting Page	751
Ending Page	755
Page Count	5
File Size	1048098
File Format	PDF
ISSN	10709908
Volume Number	21
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	TV Standards Measurement Machine vision Transforms Image edge detection Image quality sharpness/blurriness assessment Human vision system image quality assessment maximum local variation
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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