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An analysis of image quality assessment algorithm to detect the presence of unnatural contrast enhancement

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dc.citedby5
dc.contributor.authorIsmail N.H.B.en_US
dc.contributor.authorChen S.-D.en_US
dc.contributor.authorNg L.S.en_US
dc.contributor.authorRamli A.R.en_US
dc.contributor.authorid57089831500en_US
dc.contributor.authorid7410253413en_US
dc.contributor.authorid57189577624en_US
dc.contributor.authorid26428905000en_US
dc.date.accessioned2023-05-29T06:12:47Z
dc.date.available2023-05-29T06:12:47Z
dc.date.issued2016
dc.description.abstractImage contrast enhancement purposely aim the visibility of image to be increased. Most of these problems may happen after contrast enhancement: amplification of noise artifacts, saturation-loss of details, excessive brightness change and unnatural contrast enhancement. The main objective of this paper is to present an extensive review on existing Image Quality Assessment Algorithm (IQA) in order to detect the presence of unnatural contrast enhancement. Basically, the IQA used produced quality rating of the image while consistently with human visual perception. Current IQA to detect presence of unnatural contrast enhancement: Lightness Order Error (LOE), Structure Measure Operator (SMO) and Statistical Naturalness Measure (SNM). However, result of current IQA evaluation shows it may not giving consistent quality rating with human visual perception. Among three IQAs, SNM demonstrate better performance compared to LOE and SMO. But, it suffers with consistent rating for different spatial image resolution in same image content. Thus, an improvement suggested in this paper to overcome such problem occurred. � 2005 - 2016 JATIT & LLS. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.epage422
dc.identifier.issue3
dc.identifier.scopus2-s2.0-84956706871
dc.identifier.spage415
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84956706871&partnerID=40&md5=a4ef20e9ff5173560cd3f31795b5d3f7
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22857
dc.identifier.volume83
dc.publisherAsian Research Publishing Networken_US
dc.sourceScopus
dc.sourcetitleJournal of Theoretical and Applied Information Technology
dc.titleAn analysis of image quality assessment algorithm to detect the presence of unnatural contrast enhancementen_US
dc.typeArticleen_US
dspace.entity.typePublication
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