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• W3094354386 abstract "In this paper, we propose a novel approach for underwater image color correction based on a Tikhonov type optimization model in the CIELAB color space. It presents a new variational interpretation of the complementary adaptation theory in psychophysics, which establishes the connection between colorimetric notions and color constancy of the human visual system (HVS). Understood as a long-term adaptive process, our method effectively removes the underwater color cast and yields a balanced color distribution. For visualization purposes, we enhance the image contrast by properly rescaling both lightness and chroma without trespassing the CIELAB gamut. The magnitude of the enhancement is hue-selective and image-based, thus our method is robust for different underwater imaging environments. To improve the uniformity of CIELAB, we include an approximate hue-linearization as the pre-processing and an inverse transform of the Helmholtz-Kohlrausch effect as the post-processing. We analyze and validate the proposed model by various numerical experiments. Based on image quality metrics designed for underwater conditions, we compare with some state-of-art approaches to show that the proposed method has consistently superior performances." @default.
• W3094354386 created "2020-10-29" @default.
• W3094354386 creator A5021356241 @default.
• W3094354386 date "2020-10-20" @default.
• W3094354386 modified "2023-09-27" @default.
• W3094354386 title "Underwater Image Color Correction by Complementary Adaptation" @default.
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• W3094354386 doi "https://doi.org/10.48550/arxiv.2010.10748" @default.
• W3094354386 hasPublicationYear "2020" @default.
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