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: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-12-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-81231-2 |
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| _version_ | 1846137082619101184 |
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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 |
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