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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Main Authors: Mohd Hanafi Ahmad Hijazi, Leong Jing Mei
Format: Proceedings
Language:English
English
Published: IEEE Xplore 2022
Subjects:
Online Access: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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Institution: Universiti Malaysia Sabah
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id my.ums.eprints.41737
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spelling 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
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic Q300-390 Cybernetics
TR590-620 Lighting
spellingShingle 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
description 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
format Proceedings
author Mohd Hanafi Ahmad Hijazi
Leong Jing Mei
author_facet Mohd Hanafi Ahmad Hijazi
Leong Jing Mei
author_sort 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
title_sort comparison of dark channel prior and contrast limited histogram equalization for the enhancement of underwater fish image
publisher IEEE Xplore
publishDate 2022
url 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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