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

Image 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 pap...

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Main Authors: Ismail N.H.B., Chen S.-D., Ng L.S., Ramli A.R.
Other Authors: 57089831500
Format: Article
Published: Asian Research Publishing Network 2023
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spelling my.uniten.dspace-228572023-05-29T14:12:47Z An analysis of image quality assessment algorithm to detect the presence of unnatural contrast enhancement Ismail N.H.B. Chen S.-D. Ng L.S. Ramli A.R. 57089831500 7410253413 57189577624 26428905000 Image 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. Final 2023-05-29T06:12:47Z 2023-05-29T06:12:47Z 2016 Article 2-s2.0-84956706871 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84956706871&partnerID=40&md5=a4ef20e9ff5173560cd3f31795b5d3f7 https://irepository.uniten.edu.my/handle/123456789/22857 83 3 415 422 Asian Research Publishing Network Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
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description Image 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.
author2 57089831500
author_facet 57089831500
Ismail N.H.B.
Chen S.-D.
Ng L.S.
Ramli A.R.
format Article
author Ismail N.H.B.
Chen S.-D.
Ng L.S.
Ramli A.R.
spellingShingle Ismail N.H.B.
Chen S.-D.
Ng L.S.
Ramli A.R.
An analysis of image quality assessment algorithm to detect the presence of unnatural contrast enhancement
author_sort Ismail N.H.B.
title An analysis of image quality assessment algorithm to detect the presence of unnatural contrast enhancement
title_short An analysis of image quality assessment algorithm to detect the presence of unnatural contrast enhancement
title_full An analysis of image quality assessment algorithm to detect the presence of unnatural contrast enhancement
title_fullStr An analysis of image quality assessment algorithm to detect the presence of unnatural contrast enhancement
title_full_unstemmed An analysis of image quality assessment algorithm to detect the presence of unnatural contrast enhancement
title_sort analysis of image quality assessment algorithm to detect the presence of unnatural contrast enhancement
publisher Asian Research Publishing Network
publishDate 2023
_version_ 1806427958629367808
score 13.214268