基于颜色先验引导和注意力机制的水下图像增强

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中图分类号：TP391.4 文献标识码：A doi：10.37188/CJLCD.2025-0072 CSTR：32172.14.CJLCD.2025-0072

Underwater image enhancement based on color prior guidance and attention mechanism

LI Wenbiao，TAO Yang，DONG Yuan，ZHOU Liqun （School of Communications and Information Engineering，Chongqing Unioersity of Posts and Telecommunications，Chongqing 4Ooo65，China）

Abstract：To address the degradation issues in underwater images，such as color distortion，contrast reduction，and detail blurring，we propose an underwater image enhancement algorithm based on color prior guidance and attention mechanisms. We designed a Bayesian posterior feature extraction module to fuse color-prior-corrected image with the original image，and a color prior guided attention Transformer to utilize the prior information to guide the image enhancement process，which reduces the burden of color restoration during training.We constructed a hybrid multi-scale attention module to enhance feature representation in key regions.A dual-axis decoupled attntion module was introduced to eliminate feature redundancy at the botleneck layer，suppress overfiting，and improve the detail restoration. The proposed algorithm achieves PSNR/SSIM scores of 24.33/0.910 9 on UIEB，28.40/0.885 9 on UFO，and

29.00/0.8991 on EUVP，demonstrating superior performance compared to state-of-the-art approaches on all three benchmarks. In addition，the proposed algorithm improves the UIQM and UCIQE metrics by 12.81% and 5.19% ，respectively，compared to the original images. These results verify the effectiveness of the proposed algorithm in improving image sharpness， structural similarity，and overall visual quality. Key words： underwater image enhancement；color prior guidance；attention mechanism

1引言

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