Robust underwater object tracking with image enhancement and two-step feature compression
Abstract Developing a robust algorithm for underwater object tracking (UOT) is crucial to support the sustainable development and utilization of marine resources. In addition to open-air tracking challenges, the visual object tracking (VOT) task presents further difficulties in underwater environmen...
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | Complex & Intelligent Systems |
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| Online Access: | https://doi.org/10.1007/s40747-024-01755-y |
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| _version_ | 1823861512002863104 |
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| author | Jiaqing Li Chaocan Xue Xuan Luo Yubin Fu Bin Lin |
| author_facet | Jiaqing Li Chaocan Xue Xuan Luo Yubin Fu Bin Lin |
| author_sort | Jiaqing Li |
| collection | DOAJ |
| description | Abstract Developing a robust algorithm for underwater object tracking (UOT) is crucial to support the sustainable development and utilization of marine resources. In addition to open-air tracking challenges, the visual object tracking (VOT) task presents further difficulties in underwater environments due to visual distortions, color cast issues, and low-visibility conditions. To address these challenges, this study introduces a novel underwater target tracking framework based on correlation filter (CF) with image enhancement and a two-step feature compression mechanism. Underwater image enhancement mitigates the impact of visual distortions and color cast issues on target appearance modeling, while the two-step feature compression strategy addresses low-visibility conditions by compressing redundant features and combining multiple compressed features based on the peak-to-sidelobe ratio (PSR) indicator for accurate target localization. The excellent performance of the proposed method is demonstrated through evaluation on two public UOT datasets. |
| format | Article |
| id | doaj-art-e19befaa61b04fbc90da3c3e6888d9c6 |
| institution | Kabale University |
| issn | 2199-4536 2198-6053 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Complex & Intelligent Systems |
| spelling | doaj-art-e19befaa61b04fbc90da3c3e6888d9c62025-02-09T13:01:26ZengSpringerComplex & Intelligent Systems2199-45362198-60532025-01-0111211410.1007/s40747-024-01755-yRobust underwater object tracking with image enhancement and two-step feature compressionJiaqing Li0Chaocan Xue1Xuan Luo2Yubin Fu3Bin Lin4School of Mathematics and Statistics, Guilin University of TechnologySchool of Civil Engineering, Guilin University of TechnologySchool of Civil Engineering, Guilin University of TechnologySchool of Mathematics and Statistics, Guilin University of TechnologySchool of Mathematics and Statistics, Guilin University of TechnologyAbstract Developing a robust algorithm for underwater object tracking (UOT) is crucial to support the sustainable development and utilization of marine resources. In addition to open-air tracking challenges, the visual object tracking (VOT) task presents further difficulties in underwater environments due to visual distortions, color cast issues, and low-visibility conditions. To address these challenges, this study introduces a novel underwater target tracking framework based on correlation filter (CF) with image enhancement and a two-step feature compression mechanism. Underwater image enhancement mitigates the impact of visual distortions and color cast issues on target appearance modeling, while the two-step feature compression strategy addresses low-visibility conditions by compressing redundant features and combining multiple compressed features based on the peak-to-sidelobe ratio (PSR) indicator for accurate target localization. The excellent performance of the proposed method is demonstrated through evaluation on two public UOT datasets.https://doi.org/10.1007/s40747-024-01755-yUnderwater object trackingCorrelation filterUnderwater image enhancementFeature compression |
| spellingShingle | Jiaqing Li Chaocan Xue Xuan Luo Yubin Fu Bin Lin Robust underwater object tracking with image enhancement and two-step feature compression Complex & Intelligent Systems Underwater object tracking Correlation filter Underwater image enhancement Feature compression |
| title | Robust underwater object tracking with image enhancement and two-step feature compression |
| title_full | Robust underwater object tracking with image enhancement and two-step feature compression |
| title_fullStr | Robust underwater object tracking with image enhancement and two-step feature compression |
| title_full_unstemmed | Robust underwater object tracking with image enhancement and two-step feature compression |
| title_short | Robust underwater object tracking with image enhancement and two-step feature compression |
| title_sort | robust underwater object tracking with image enhancement and two step feature compression |
| topic | Underwater object tracking Correlation filter Underwater image enhancement Feature compression |
| url | https://doi.org/10.1007/s40747-024-01755-y |
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