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Remote Sensing
Volume 15
Issue 19
10.3390/rs15194699
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Article

Underwater Image Restoration via Adaptive Color Correction and Contrast Enhancement Fusion

by
Weihong Zhang
1,2,3,†,
Xiaobo Li
1,2,†,
Shuping Xu
4,
Xujin Li
3,
Yiguang Yang
3,
Degang Xu
1,4,
Tiegen Liu
4 and
Haofeng Hu
1,4,*
1
School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
2
Key Laboratory of Equipment and Informatization in Environment Controlled Agriculture, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China
3
Joint Laboratory for Ocean Observation and Detection, Qingdao Marine Science and Technology Center, Qingdao 266237, China
4
School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Remote Sens. 2023, 15(19), 4699; https://doi.org/10.3390/rs15194699
Submission received: 21 August 2023 / Revised: 14 September 2023 / Accepted: 22 September 2023 / Published: 25 September 2023
(This article belongs to the Special Issue Advanced Techniques for Water-Related Remote Sensing)
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Abstract

When light traverses through water, it undergoes influence from the absorption and scattering of particles, resulting in diminished contrast and color distortion within underwater imaging. These effects further constrain the observation of underwater environments and the extraction of features from submerged objects. To address these challenges, we introduce an underwater color image processing approach, which amalgamates the frequency and spatial domains, enhancing image contrast in the frequency domain, adaptively refining image color within the spatial domain, and ultimately merging the contrast-enhanced image with the color-corrected counterpart within the CIE L*a*b* color space. Experiments conducted on standard underwater image benchmark datasets highlight the significant improvements our proposed method achieves in terms of enhancing contrast and rendering more natural colors compared to several state-of-the-art methods. The results are further evaluated using four commonly used image metrics, consistently showing that our method yields the highest average value. The proposed method effectively addresses challenges related to low contrast, color distortion, and obscured details in underwater images, a fact especially evident in various scenarios involving color-affected underwater imagery.
Keywords: image enhancement; contrast improvement; color correction; image fusion image enhancement; contrast improvement; color correction; image fusion
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MDPI and ACS Style

Zhang, W.; Li, X.; Xu, S.; Li, X.; Yang, Y.; Xu, D.; Liu, T.; Hu, H. Underwater Image Restoration via Adaptive Color Correction and Contrast Enhancement Fusion. Remote Sens. 2023, 15, 4699. https://doi.org/10.3390/rs15194699

AMA Style

Zhang W, Li X, Xu S, Li X, Yang Y, Xu D, Liu T, Hu H. Underwater Image Restoration via Adaptive Color Correction and Contrast Enhancement Fusion. Remote Sensing. 2023; 15(19):4699. https://doi.org/10.3390/rs15194699

Chicago/Turabian Style

Zhang, Weihong, Xiaobo Li, Shuping Xu, Xujin Li, Yiguang Yang, Degang Xu, Tiegen Liu, and Haofeng Hu. 2023. "Underwater Image Restoration via Adaptive Color Correction and Contrast Enhancement Fusion" Remote Sensing 15, no. 19: 4699. https://doi.org/10.3390/rs15194699

APA Style

Zhang, W., Li, X., Xu, S., Li, X., Yang, Y., Xu, D., Liu, T., & Hu, H. (2023). Underwater Image Restoration via Adaptive Color Correction and Contrast Enhancement Fusion. Remote Sensing, 15(19), 4699. https://doi.org/10.3390/rs15194699

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