Underwater image enhancement based on optimally weighted histogram framework and improved Fick’s law algorithm

Abstract The quality of underwater images is often affected by light scattering and attenuation, resulting in a loss of contrast and brightness. To address this issue, this paper proposes an underwater image enhancement method: improved Fick’s law algorithm-based optimally weighted histogram framewo...

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Main Authors: Yawen Liu, Ziteng Qiao, Zhiwei Ye, Wen Zhou, Mingwei Wang, Qiyi He, Ting Cai
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-024-81231-2
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author Yawen Liu
Ziteng Qiao
Zhiwei Ye
Wen Zhou
Mingwei Wang
Qiyi He
Ting Cai
author_facet Yawen Liu
Ziteng Qiao
Zhiwei Ye
Wen Zhou
Mingwei Wang
Qiyi He
Ting Cai
author_sort Yawen Liu
collection DOAJ
description Abstract The quality of underwater images is often affected by light scattering and attenuation, resulting in a loss of contrast and brightness. To address this issue, this paper proposes an underwater image enhancement method: improved Fick’s law algorithm-based optimally weighted histogram framework (IFLAHF). The method incorporates the bi-histogram equalization-based three plateau limits (BHE3PL) technique to enhance image contrast and details while maintaining brightness. However, its dependence on fixed parameters limits its adaptability. To overcome this limitation, the paper introduces Fick’s law algorithm (FLA) and then improves it to optimize the fixed parameters. FLA is improved by incorporating Tent chaotic mapping and reverse learning to increase population diversity, and Levy flight is introduced in the later stages to enhance exploitation. Additionally, a color correction technique is applied to correct color deviations in underwater images, leading to a more natural appearance. To verify the performance of the method, it is compared with different methods. As demonstrated by simulations, the proposed method outperforms existing algorithms in multiple underwater image enhancement metrics.
format Article
id doaj-art-236c598894c4496cb525eb17a3069ad7
institution Kabale University
issn 2045-2322
language English
publishDate 2024-12-01
publisher Nature Portfolio
record_format Article
series Scientific Reports
spelling doaj-art-236c598894c4496cb525eb17a3069ad72024-12-08T12:29:25ZengNature PortfolioScientific Reports2045-23222024-12-0114112110.1038/s41598-024-81231-2Underwater image enhancement based on optimally weighted histogram framework and improved Fick’s law algorithmYawen Liu0Ziteng Qiao1Zhiwei Ye2Wen Zhou3Mingwei Wang4Qiyi He5Ting Cai6School of Computer Science, Hubei University of TechnologySchool of Computer Science, Hubei University of TechnologySchool of Computer Science, Hubei University of TechnologySchool of Computer Science, Hubei University of TechnologySchool of Computer Science, Hubei University of TechnologySchool of Computer Science, Hubei University of TechnologySchool of Computer Science, Hubei University of TechnologyAbstract The quality of underwater images is often affected by light scattering and attenuation, resulting in a loss of contrast and brightness. To address this issue, this paper proposes an underwater image enhancement method: improved Fick’s law algorithm-based optimally weighted histogram framework (IFLAHF). The method incorporates the bi-histogram equalization-based three plateau limits (BHE3PL) technique to enhance image contrast and details while maintaining brightness. However, its dependence on fixed parameters limits its adaptability. To overcome this limitation, the paper introduces Fick’s law algorithm (FLA) and then improves it to optimize the fixed parameters. FLA is improved by incorporating Tent chaotic mapping and reverse learning to increase population diversity, and Levy flight is introduced in the later stages to enhance exploitation. Additionally, a color correction technique is applied to correct color deviations in underwater images, leading to a more natural appearance. To verify the performance of the method, it is compared with different methods. As demonstrated by simulations, the proposed method outperforms existing algorithms in multiple underwater image enhancement metrics.https://doi.org/10.1038/s41598-024-81231-2Image enhancementUnderwater imageHistogram equalizationFick’s law algorithmPlateau limit
spellingShingle Yawen Liu
Ziteng Qiao
Zhiwei Ye
Wen Zhou
Mingwei Wang
Qiyi He
Ting Cai
Underwater image enhancement based on optimally weighted histogram framework and improved Fick’s law algorithm
Scientific Reports
Image enhancement
Underwater image
Histogram equalization
Fick’s law algorithm
Plateau limit
title Underwater image enhancement based on optimally weighted histogram framework and improved Fick’s law algorithm
title_full Underwater image enhancement based on optimally weighted histogram framework and improved Fick’s law algorithm
title_fullStr Underwater image enhancement based on optimally weighted histogram framework and improved Fick’s law algorithm
title_full_unstemmed Underwater image enhancement based on optimally weighted histogram framework and improved Fick’s law algorithm
title_short Underwater image enhancement based on optimally weighted histogram framework and improved Fick’s law algorithm
title_sort underwater image enhancement based on optimally weighted histogram framework and improved fick s law algorithm
topic Image enhancement
Underwater image
Histogram equalization
Fick’s law algorithm
Plateau limit
url https://doi.org/10.1038/s41598-024-81231-2
work_keys_str_mv AT yawenliu underwaterimageenhancementbasedonoptimallyweightedhistogramframeworkandimprovedfickslawalgorithm
AT zitengqiao underwaterimageenhancementbasedonoptimallyweightedhistogramframeworkandimprovedfickslawalgorithm
AT zhiweiye underwaterimageenhancementbasedonoptimallyweightedhistogramframeworkandimprovedfickslawalgorithm
AT wenzhou underwaterimageenhancementbasedonoptimallyweightedhistogramframeworkandimprovedfickslawalgorithm
AT mingweiwang underwaterimageenhancementbasedonoptimallyweightedhistogramframeworkandimprovedfickslawalgorithm
AT qiyihe underwaterimageenhancementbasedonoptimallyweightedhistogramframeworkandimprovedfickslawalgorithm
AT tingcai underwaterimageenhancementbasedonoptimallyweightedhistogramframeworkandimprovedfickslawalgorithm