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Underwater image enhancement based on color correction and complementary dual image multi-scale fusion

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Abstract

Underwater images often suffer from color cast, poor contrast, and detail loss owing to the scattering and absorption of light in water. To solve these problems, we propose what we believe to be a novel underwater image enhancement method based on color correction and dual image multi-scale fusion. We first use the color correction method to solve the problem of color cast, and we compensate the other two-color channels with the highest mean value color channel; further, all the color channels are dynamically stretched. Next, a complementary dual image multi-scale fusion method is used to improve the contrast, pairs of complementary adaptive gamma correction with weighted distribution enhanced images are used as the two inputs of multi-scale fusion, and appropriate weight maps are selected. Then, a multi-scale detail-sharpening method is used to enhance the image details. Qualitative and quantitative evaluations prove that the proposed method can produce high-quality underwater images. Moreover, the proposed method has relatively high evaluator values compared to the state-of-the-art methods.

© 2022 Optica Publishing Group

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Data availability

Publicly available datasets analyzed in this study can be found in Ref. [46].

46. C. Li, “Project benchmark,” Github, (2019), https://li-chongyi.github.io/proj_benchmark.html.

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