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An effective and robust underwater image enhancement method based on color correction and artificial multi-exposure fusion

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Abstract

Underwater images/frames are always subjected to color distortion, contrast reduction and detail loss, which degrade the visual quality severely. Current dehazing methods could not improve the visual quality of underwater images/frames robustly and effectively, especially in removing the undesired color cast. To address the issue, this paper introduces an effective and robust underwater image enhancement method without any dedicated hardware or prior knowledge. First, an adaptive reduction operation on the two stronger color-channels of inputs is employed to avoid the red over-compensated deficiency appearing in color-balanced result. Second, three kinds of color-balanced images are generated from the operation, which combines color compensation algorithms and famous Gray-World assumption. Third, a novel algorithm based on two non-reference quantitative evaluation indicators is utilized to choose the optimal color-balancing version. Then, gamma adjustment operation is employed to generate artificial over−/under-exposure visions of color-balancing image. Last, ‘exposedness’ and ‘contrast’ are set as two weights, being blended into the famous multi-scale fusion framework to generate the enhanced result. Our experimental results demonstrate the superior performance of the proposed method in both subjective and objective evaluations. Besides, the proposed method is also suitable for dehazing regular fogged images and local feature points matching.

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Data availability

Datasets (UIEB, RUIE, and NH-HAZE) used for testing relevant underwater dehazing methods have been taken from following digital object identifiers: doi:https://doi.org/10.1109/TIP.2019.2955241, doi:https://doi.org/10.1109/TCSVT.2019.2963772, and doi:https://doi.org/10.1109/CVPRW50498.2020.00230. Diving scenes dataset used for testing relevant underwater image dehazing methods in this paper, is available from the corresponding author on reasonable request.

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Acknowledgements

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This paper is supported by National Key Research and Development Program of China under Grant 2019YFB1600400. This paper is also supported in part by the Fundamental Research Funds for the Central Universities of China under Grant 3132019340 and 3132019200, and high-tech ship research project from ministry of industry and information technology of the people’s republic of China under Grant MC-201902-C01.

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Authors and Affiliations

  1. School of Information Science and Technology, Dalian Maritime University, Dalian, 116026, China

    Ye Tao, Lili Dong & Wenhai Xu

  2. Center of Technology, Liaoning Port Group Co., Ltd., Dalian, 116001, China

    Ye Tao, Luqiang Xu & Guangtong Chen

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  1. Ye Tao

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  2. Lili Dong

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  3. Luqiang Xu

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  4. Guangtong Chen

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  5. Wenhai Xu

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Correspondence toYe Tao.

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Tao, Y., Dong, L., Xu, L.et al. An effective and robust underwater image enhancement method based on color correction and artificial multi-exposure fusion.Multimed Tools Appl82, 36929–36949 (2023). https://doi.org/10.1007/s11042-023-15153-y

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