Comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image
The application of artificial intelligence (AI) in aquaculture may improve the efficiency of fish farming management. Computer vision is one of the fields in AI beneficial for aquaculture. However, the underwater image quality is usually low due to light scattering through the water. Therefore, imag...
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2022
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my.ums.eprints.417372024-11-05T06:19:28Z https://eprints.ums.edu.my/id/eprint/41737/ Comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image Mohd Hanafi Ahmad Hijazi Leong Jing Mei Q300-390 Cybernetics TR590-620 Lighting The application of artificial intelligence (AI) in aquaculture may improve the efficiency of fish farming management. Computer vision is one of the fields in AI beneficial for aquaculture. However, the underwater image quality is usually low due to light scattering through the water. Therefore, image enhancement is necessary before any further processing can be done. There are numerous image enhancement techniques for underwater images reported in the literature. In this paper, the comparison of the two most common image enhancement techniques for underwater images, the Dark Channel Prior (DCP) and Histogram Equalization (HE), is presented. The strength and weaknesses of each technique pertaining to the underwater images are also described IEEE Xplore 2022 Proceedings PeerReviewed text en https://eprints.ums.edu.my/id/eprint/41737/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/41737/2/FULL%20TEXT.pdf Mohd Hanafi Ahmad Hijazi and Leong Jing Mei (2022) Comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image. https://ieeexplore.ieee.org/document/9936796 |
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Q300-390 Cybernetics TR590-620 Lighting Mohd Hanafi Ahmad Hijazi Leong Jing Mei Comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image |
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The application of artificial intelligence (AI) in aquaculture may improve the efficiency of fish farming management. Computer vision is one of the fields in AI beneficial for aquaculture. However, the underwater image quality is usually low due to light scattering through the water. Therefore, image enhancement is necessary before any further processing can be done. There are numerous image enhancement techniques for underwater images reported in the literature. In this paper, the comparison of the two most common image enhancement techniques for underwater images, the Dark Channel Prior (DCP) and Histogram Equalization (HE), is presented. The strength and weaknesses of each technique pertaining to the underwater images are also described |
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Proceedings |
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Mohd Hanafi Ahmad Hijazi Leong Jing Mei |
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Mohd Hanafi Ahmad Hijazi Leong Jing Mei |
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Mohd Hanafi Ahmad Hijazi |
title |
Comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image |
title_short |
Comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image |
title_full |
Comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image |
title_fullStr |
Comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image |
title_full_unstemmed |
Comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image |
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comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image |
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IEEE Xplore |
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2022 |
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https://eprints.ums.edu.my/id/eprint/41737/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/41737/2/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/41737/ https://ieeexplore.ieee.org/document/9936796 |
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