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Real-Time Underwater Image Enhancement Using Adaptive Full-Scale Retinex

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Abstract

Current Retinex-based image enhancement methods with fixed scale filters cannot adapt to situations involving various depths of field and illuminations. In this paper, a simple but effective method based on adaptive full-scale Retinex (AFSR) is proposed to clarify underwater images or videos. First, we design an adaptive full-scale filter that is guided by the optical transmission rate to estimate illumination components. Then, to reduce the computational complexity, we develop a quantitative mapping method instead of non-linear log functions for directly calculating the reflection component. The proposed method is capable of real-time processing of underwater videos using temporal coherence and Fourier transformations. Compared with eight state-of-the-art clarification methods, our method yields comparable or better results for image contrast enhancement, color-cast correction and clarity.

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Authors and Affiliations

  1. School of Information, Yunnan University of Finance and Economics, Kunming, 650221, China

    Xing-Gui Xu

  2. School of Electrical Electronics and Computer Science, Guangxi University of Science and Technology, Liuzhou, 545006, China

    Xiang-Suo Fan

  3. Department of Information and Communication, College of the Chinese People’s Armed Police Force, Chengdu, 610213, China

    Yong-Li Liu

Authors
  1. Xing-Gui Xu
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  2. Xiang-Suo Fan
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  3. Yong-Li Liu
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Correspondence to Xiang-Suo Fan.

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Xu, XG., Fan, XS. & Liu, YL. Real-Time Underwater Image Enhancement Using Adaptive Full-Scale Retinex. J. Comput. Sci. Technol. 38, 885–898 (2023). https://doi.org/10.1007/s11390-022-1115-z

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  • DOI: https://doi.org/10.1007/s11390-022-1115-z

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