Underwater Image Enhancement via Piecewise Color Correction and Dual Prior Optimized Contrast Enhancement

• Published in: IEEE signal processing letters Vol. 30; pp. 1 - 5
• Main Authors: Zhang, Weidong, Jin, Songlin, Zhuang, Peixian, Liang, Zheng, Li, Chongyi
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Color; Degradation; Electronic mail; Gray-scale; Image color analysis; Image contrast; Image enhancement; Image quality; Layer decomposition; Measurement; Piecewise color correction; Serious quality degradation; Spatial and texture priors; Texture; Training data; Underwater
• ISSN: 1070-9908; 1558-2361
• DOI: 10.1109/LSP.2023.3255005

Due to the absorption and scattering of light, underwater captured images often face serious quality degradation issues. In this letter, we propose to cope with the aforementioned issues via piecewise color correction and dual prior optimized contrast enhancement. Specifically, we first present the piecewise color correction method using the maximum mean and two gain factors to correct the color cast of each color channel. Then, we propose a dual prior optimized contrast enhancement method, which relies on the spatial and texture priors to decompose the base layer and detail layer of the V channel in HSV color space. Meanwhile, we employ different enhancement strategies in different layers to enhance the contrast and texture detail of underwater images. Our extensive experiments on several benchmark datasets show that our method outperforms eleven compared state-of-the-art methods. Moreover, our method has good generalization capability for fog and low-light images. The code is available at https://github.com/Li-Chongyi/PCDE .