Abstract
The complex underwater environment often leads to significant image degradation, such as color distortion, low contrast, and poor visibility, which severely impacts the performance of underwater vision tasks. Existing underwater image enhancement (UIE) methods are typically designed for specific degradation conditions and exhibit limited adaptability to varying underwater environments. To address the challenges posed by diverse degradation conditions, we propose an Adaptive Color-Corrected Multicolor Space Enhancement Network (CCMSE-Net). The CCMSE-Net decomposes the UIE task into two stages: color correction and visibility enhancement, corresponding to an adaptive color correction subnetwork (ACC-Net) and a multicolor space enhancement subnetwork (MCSE-Net), respectively. The MCSE-Net achieves multicolor space feature enhancement by applying the multiscale Retinex (MSR) model to the RGB color space and incorporating a feature extraction module (FEM) for the Lab and HSV color spaces. The fusion of multicolor space features is facilitated by the convolutional residual spatial self-attention block (CRSAB), which effectively captures both local details and global context. Experimental results demonstrate that the CCMSE-Net significantly enhances underwater image quality both quantitatively and qualitatively, offering a robust and adaptable solution for diverse underwater environments. Additionally, the enhanced images substantially improve the performance of downstream underwater vision tasks.















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All data included in this study are available upon request by contact with the corresponding author.
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This work was supported by the National Natural Science Foundation of China (NSFC) under Grant No. 62203192.
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DX contributed to conceptualization, resources, supervision, and writing the review and editing. WX was responsible for conceptualization, methodology, software, investigation, and also contributed to writing of the original draft. YZ assisted with funding acquisition and wrote the review and editing. XS wrote the review and editing. QQ conducted formal analysis, and contributed to visualization. All authors reviewed the manuscript.
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Xu, D., Xu, W., Zhou, Y. et al. Adaptive color-corrected multicolor space enhancement network for underwater image enhancement. Multimedia Systems 31, 283 (2025). https://doi.org/10.1007/s00530-025-01867-6
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DOI: https://doi.org/10.1007/s00530-025-01867-6