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Turbid underwater image enhancement via attenuation prior formation model
  • +4
  • Shuai Liu,
  • Peng Chen,
  • Lei Chen,
  • Yuchao Zheng,
  • Jianru Li,
  • Zhengxiang Shen,
  • Zhanshan Wang
Shuai Liu
Tongji University
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Peng Chen
Tongji University
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Lei Chen
Shenyang Jianzhu University
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Yuchao Zheng
Kyushu Kogyo Daigaku Kogakubu Daigakuin Kogakufu
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Jianru Li
Tongji University
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Zhengxiang Shen
Tongji University

Corresponding Author:[email protected]

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Zhanshan Wang
Tongji University
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Abstract

To deal with the issue of poor visibility caused by water turbidity during the operation of underwater robotics, we propose an attenuation prior formation model-guided enhancement algorithm for turbid underwater images. Specifically, we establish an imaging model suitable for turbid water by studying the influence of water turbidity on light attenuation and transmission. For this model, we first propose a scoring formula that takes into account multiple prior knowledge to estimate the global background light with the help of hierarchical searching technique. Then, we make full use of the advantages of different scale neighborhoods in image restoration, and propose an adaptive multi-scale weighted fusion transmission estimation method to balanc e brightness and contrast. In addition, to correct the color of the images with a natural appearance, a variation of white balance is introduced as post-processing. Extensive experiments on two image datasets show that our algorithm achieves better results than state-of-the-art methods.
Submitted to Journal of Field Robotics
09 Apr 2024Submission Checks Completed
09 Apr 2024Assigned to Editor
09 Apr 2024Review(s) Completed, Editorial Evaluation Pending
14 Sep 2024Reviewer(s) Assigned
24 Nov 2024Editorial Decision: Revise Major