Underwater Image Color Correction by Complementary Adaptation

• URL: http://arxiv.org/abs/2010.10748v1
• Date: Wed, 21 Oct 2020 03:59:22 GMT
• Title: Underwater Image Color Correction by Complementary Adaptation
• Authors: Yuchen He
• Abstract summary: We propose a novel approach for underwater image color correction based on a Tikhonov type optimization model in the CIELAB color space. Understood as a long-term adaptive process, our method effectively removes the underwater color cast and yields a balanced color distribution.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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