4.6 Article

Underwater Image Enhancement by Attenuated Color Channel Correction and Detail Preserved Contrast Enhancement

Journal

IEEE JOURNAL OF OCEANIC ENGINEERING
Volume 47, Issue 3, Pages 718-735

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JOE.2022.3140563

Keywords

Image color analysis; Histograms; Image restoration; Optimized production technology; Attenuation; Visualization; Iterative methods; Color correction; contrast enhancement; underwater image enhancement; underwater imaging

Funding

  1. China Postdoctoral Science Foundation [2019M660438]
  2. CAAI-Huawei MindSpore Open Fund

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This article proposes a method to address the quality degradation issues in underwater images through attenuated color channel correction and detail preserved contrast enhancement. Experimental results demonstrate the effectiveness of the method in enhancing underwater images, as well as low-light images and hazy images.
An underwater image often suffers from quality degradation issues, such as color deviations, low contrast, and blurred details, due to the absorption and scattering of light. In this article, we propose to address the aforementioned degradation issues via attenuated color channel correction and detail preserved contrast enhancement. Concretely, we first propose an underwater image color correction method. Considering the differences between superior and inferior color channels of an underwater image, the inferior color channels are compensated via especially designed attenuation matrices. We then employ a dual-histogram-based iterative threshold method and a limited histogram method with Rayleigh distribution to improve the global and local contrast of the color-corrected image, thus achieving a global contrast-enhanced version and a local contrast-enhanced version, respectively. To integrate the complementary merits between the global contrast-enhanced version and the local contrast-enhanced version, we adopt a multiscale fusion strategy to fuse them. Finally, we propose a multiscale unsharp masking strategy to further sharpen the fused image for better visual quality. Extensive experiments on four underwater image enhancement benchmark data sets demonstrate that our method effectively enhances underwater images qualitatively and quantitatively. Besides, our method also generalizes well to the enhancement of low-light images and hazy images.

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