Enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods
Prior to this work, Human Visual Perception (HVP)-based Image Quality Analyzer (IQA) has been proposed. The HVP-based IQA correlates with human judgment better than the existing IQAs which are commonly used for the assessment of contrast enhancement techniques. This paper highlights the shortcomings...
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Zarka Private University
2023
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| author | Chen S. Janahiraman T. Suliman A. |
| author2 | 7410253413 |
| author_facet | 7410253413 Chen S. Janahiraman T. Suliman A. |
| author_sort | Chen S. |
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| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Prior to this work, Human Visual Perception (HVP)-based Image Quality Analyzer (IQA) has been proposed. The HVP-based IQA correlates with human judgment better than the existing IQAs which are commonly used for the assessment of contrast enhancement techniques. This paper highlights the shortcomings of the HVP-based IQA such as high computational complexity, excessive (six) threshold parameter tuning and high performance sensitivity to the change in the threshold parameters� value. In order to overcome the aforementioned problems, this paper proposes several enhancements such as replacement of local entropy with edge magnitude in sub-image texture analysis, down-sampling of image spatial resolution, removal of luminance masking and incorporation of famous Weber-Fechner Law on human perception. The enhanced HVP-based IQA requires far less computation (>189 times lesser) while still showing excellent correlation (Pearson Correlation Coefficient, PCC > 0.90, Root Mean Square Error, RMSE<0.3410) with human judgment. Besides, it requires fewer (two) threshold parameter tuning while maintaining consistent performance across wide range of threshold parameters� value, making it feasible for real-time video processing. � 2019, Zarka Private University. All rights reserved. |
| format | Article |
| id | my.uniten.dspace-25002 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Zarka Private University |
| record_format | dspace |
| spelling | my.uniten.dspace-250022023-05-29T15:30:11Z Enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods Chen S. Janahiraman T. Suliman A. 7410253413 35198314400 25825739000 Prior to this work, Human Visual Perception (HVP)-based Image Quality Analyzer (IQA) has been proposed. The HVP-based IQA correlates with human judgment better than the existing IQAs which are commonly used for the assessment of contrast enhancement techniques. This paper highlights the shortcomings of the HVP-based IQA such as high computational complexity, excessive (six) threshold parameter tuning and high performance sensitivity to the change in the threshold parameters� value. In order to overcome the aforementioned problems, this paper proposes several enhancements such as replacement of local entropy with edge magnitude in sub-image texture analysis, down-sampling of image spatial resolution, removal of luminance masking and incorporation of famous Weber-Fechner Law on human perception. The enhanced HVP-based IQA requires far less computation (>189 times lesser) while still showing excellent correlation (Pearson Correlation Coefficient, PCC > 0.90, Root Mean Square Error, RMSE<0.3410) with human judgment. Besides, it requires fewer (two) threshold parameter tuning while maintaining consistent performance across wide range of threshold parameters� value, making it feasible for real-time video processing. � 2019, Zarka Private University. All rights reserved. Final 2023-05-29T07:30:10Z 2023-05-29T07:30:10Z 2019 Article 2-s2.0-85067830674 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067830674&partnerID=40&md5=52cfa84fb52f5bd18ce4c62c695bf7a1 https://irepository.uniten.edu.my/handle/123456789/25002 16 1 41 47 Zarka Private University Scopus |
| spellingShingle | Chen S. Janahiraman T. Suliman A. Enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods |
| title | Enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods |
| title_full | Enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods |
| title_fullStr | Enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods |
| title_full_unstemmed | Enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods |
| title_short | Enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods |
| title_sort | enhancement of human visual perception-based image quality analyzer for assessment of contrast enhancement methods |
| url_provider | http://dspace.uniten.edu.my/ |