Multi-Module Combination for Underwater Image Enhancement
Underwater observation and operation for divers and underwater robots still largely depend on optic methods, such as cameras videos, etc. However, due to the poor quality of images captured in murky waters, underwater operations in such areas are greatly hindered. In order to solve the issue of degr...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/9/5200 |
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| author | Zhe Jiang Huanhuan Wang Gang He Jiawang Chen Wei Feng Gaosheng Luo |
| author_facet | Zhe Jiang Huanhuan Wang Gang He Jiawang Chen Wei Feng Gaosheng Luo |
| author_sort | Zhe Jiang |
| collection | DOAJ |
| description | Underwater observation and operation for divers and underwater robots still largely depend on optic methods, such as cameras videos, etc. However, due to the poor quality of images captured in murky waters, underwater operations in such areas are greatly hindered. In order to solve the issue of degraded images, this paper proposes a multi-module combination method (UMMC) for underwater image enhancement. This is a new solution for processing a single image. Specifically, the process consists of five modules. With five separate modules working in tandem, UMMC provides the flexibility to address key challenges such as color distortion, haze, and low contrast. The UMMC framework starts with a color deviation detection module that intelligently separates images with and without color deviation, followed by a color and white balance correction module to restore accurate color. Effective defogging is then performed using a rank-one prior matrix-based approach, while a reference curve transformation adaptively enhances the contrast. Finally, the fusion module combines the visibility and contrast functions with reference to two weights to produce clear and natural results. A large number of experimental results demonstrate the effectiveness of the method proposed in this paper, which shows good performance compared to existing algorithms, both on real and synthetic data. |
| format | Article |
| id | doaj-art-56d1409520a74406a8686b5bc9e6df99 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-56d1409520a74406a8686b5bc9e6df992025-08-20T03:52:58ZengMDPI AGApplied Sciences2076-34172025-05-01159520010.3390/app15095200Multi-Module Combination for Underwater Image EnhancementZhe Jiang0Huanhuan Wang1Gang He2Jiawang Chen3Wei Feng4Gaosheng Luo5Shanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, ChinaShanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, ChinaShanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, ChinaCollege of Oceanography, Zhejiang University, Zhejiang 316021, ChinaShenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen 518110, ChinaShanghai Engineering Research Center of Hadal Science and Technology, College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, ChinaUnderwater observation and operation for divers and underwater robots still largely depend on optic methods, such as cameras videos, etc. However, due to the poor quality of images captured in murky waters, underwater operations in such areas are greatly hindered. In order to solve the issue of degraded images, this paper proposes a multi-module combination method (UMMC) for underwater image enhancement. This is a new solution for processing a single image. Specifically, the process consists of five modules. With five separate modules working in tandem, UMMC provides the flexibility to address key challenges such as color distortion, haze, and low contrast. The UMMC framework starts with a color deviation detection module that intelligently separates images with and without color deviation, followed by a color and white balance correction module to restore accurate color. Effective defogging is then performed using a rank-one prior matrix-based approach, while a reference curve transformation adaptively enhances the contrast. Finally, the fusion module combines the visibility and contrast functions with reference to two weights to produce clear and natural results. A large number of experimental results demonstrate the effectiveness of the method proposed in this paper, which shows good performance compared to existing algorithms, both on real and synthetic data.https://www.mdpi.com/2076-3417/15/9/5200underwater image enhancementimage fusioncolor correctionwhite balancecolor bias detection |
| spellingShingle | Zhe Jiang Huanhuan Wang Gang He Jiawang Chen Wei Feng Gaosheng Luo Multi-Module Combination for Underwater Image Enhancement Applied Sciences underwater image enhancement image fusion color correction white balance color bias detection |
| title | Multi-Module Combination for Underwater Image Enhancement |
| title_full | Multi-Module Combination for Underwater Image Enhancement |
| title_fullStr | Multi-Module Combination for Underwater Image Enhancement |
| title_full_unstemmed | Multi-Module Combination for Underwater Image Enhancement |
| title_short | Multi-Module Combination for Underwater Image Enhancement |
| title_sort | multi module combination for underwater image enhancement |
| topic | underwater image enhancement image fusion color correction white balance color bias detection |
| url | https://www.mdpi.com/2076-3417/15/9/5200 |
| work_keys_str_mv | AT zhejiang multimodulecombinationforunderwaterimageenhancement AT huanhuanwang multimodulecombinationforunderwaterimageenhancement AT ganghe multimodulecombinationforunderwaterimageenhancement AT jiawangchen multimodulecombinationforunderwaterimageenhancement AT weifeng multimodulecombinationforunderwaterimageenhancement AT gaoshengluo multimodulecombinationforunderwaterimageenhancement |