Comprehensive evaluation of restoration quality for weak image signals with fuzzy logic
Natural images captured in hazy, sandy or low-light conditions degrade significantly and are termed weak image signals (WIS) in this paper. Evaluating their restoration using multiple single-factor indices is challenging due to potential mutual exclusivity, hindering a holistic understanding. A nove...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Systems Science & Control Engineering |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/21642583.2024.2437257 |
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| author | Shunyuan Yu Xinghui Zhang |
| author_facet | Shunyuan Yu Xinghui Zhang |
| author_sort | Shunyuan Yu |
| collection | DOAJ |
| description | Natural images captured in hazy, sandy or low-light conditions degrade significantly and are termed weak image signals (WIS) in this paper. Evaluating their restoration using multiple single-factor indices is challenging due to potential mutual exclusivity, hindering a holistic understanding. A novel no-reference image quality evaluation approach has been devised specifically to assess the visibility enhancement of restored WIS images. This approach constructs a comprehensive index, based on fuzzy theory, to holistically evaluate the restoration effect of WIS. The index is derived from five carefully selected single-factor indices: new visible edge, visible edge gradient, contrast gain, colour naturalness and colour richness. These indices capture improvements in contrast and colour post-restoration. Fuzzy logic is employed to meticulously analyze the contribution of each factor to the overall image performance. The weights assigned to each individual evaluation index are determined through a rigorous analytic hierarchy process (AHP) analysis, utilizing a judgment matrix. The comprehensive evaluation index, denoted as CNC, surpasses the limitations of single-factor indices by capturing even the subtlest changes across all factors, offering a more comprehensive and nuanced assessment. Experimental validation confirms its alignment with subjective evaluations, confirming its effectiveness in comprehensively evaluating the restoring effect of WIS images. |
| format | Article |
| id | doaj-art-f912af4ac0884c66a6c45d98c63449c5 |
| institution | Kabale University |
| issn | 2164-2583 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Systems Science & Control Engineering |
| spelling | doaj-art-f912af4ac0884c66a6c45d98c63449c52024-12-17T09:06:12ZengTaylor & Francis GroupSystems Science & Control Engineering2164-25832024-12-0112110.1080/21642583.2024.2437257Comprehensive evaluation of restoration quality for weak image signals with fuzzy logicShunyuan Yu0Xinghui Zhang1College of Electronics and Information Engineering, Ankang University, Ankang, People’s Republic of ChinaCollege of Electronics and Information Engineering, Ankang University, Ankang, People’s Republic of ChinaNatural images captured in hazy, sandy or low-light conditions degrade significantly and are termed weak image signals (WIS) in this paper. Evaluating their restoration using multiple single-factor indices is challenging due to potential mutual exclusivity, hindering a holistic understanding. A novel no-reference image quality evaluation approach has been devised specifically to assess the visibility enhancement of restored WIS images. This approach constructs a comprehensive index, based on fuzzy theory, to holistically evaluate the restoration effect of WIS. The index is derived from five carefully selected single-factor indices: new visible edge, visible edge gradient, contrast gain, colour naturalness and colour richness. These indices capture improvements in contrast and colour post-restoration. Fuzzy logic is employed to meticulously analyze the contribution of each factor to the overall image performance. The weights assigned to each individual evaluation index are determined through a rigorous analytic hierarchy process (AHP) analysis, utilizing a judgment matrix. The comprehensive evaluation index, denoted as CNC, surpasses the limitations of single-factor indices by capturing even the subtlest changes across all factors, offering a more comprehensive and nuanced assessment. Experimental validation confirms its alignment with subjective evaluations, confirming its effectiveness in comprehensively evaluating the restoring effect of WIS images.https://www.tandfonline.com/doi/10.1080/21642583.2024.2437257No reference image quality assessmentfuzzy logiccomprehensive evaluationweak image signals |
| spellingShingle | Shunyuan Yu Xinghui Zhang Comprehensive evaluation of restoration quality for weak image signals with fuzzy logic Systems Science & Control Engineering No reference image quality assessment fuzzy logic comprehensive evaluation weak image signals |
| title | Comprehensive evaluation of restoration quality for weak image signals with fuzzy logic |
| title_full | Comprehensive evaluation of restoration quality for weak image signals with fuzzy logic |
| title_fullStr | Comprehensive evaluation of restoration quality for weak image signals with fuzzy logic |
| title_full_unstemmed | Comprehensive evaluation of restoration quality for weak image signals with fuzzy logic |
| title_short | Comprehensive evaluation of restoration quality for weak image signals with fuzzy logic |
| title_sort | comprehensive evaluation of restoration quality for weak image signals with fuzzy logic |
| topic | No reference image quality assessment fuzzy logic comprehensive evaluation weak image signals |
| url | https://www.tandfonline.com/doi/10.1080/21642583.2024.2437257 |
| work_keys_str_mv | AT shunyuanyu comprehensiveevaluationofrestorationqualityforweakimagesignalswithfuzzylogic AT xinghuizhang comprehensiveevaluationofrestorationqualityforweakimagesignalswithfuzzylogic |