电子科技2026，Vol.39Issue(10)：42-51,10.DOI:10.16180/j.cnki.issn1007-7820.2026.10.005
基于颜色校正的GAN水下图像增强网络
Underwater Image Enhancement Algorithm Based on GAN-Fused Color Correction
摘要
Abstract
In view of the problems such as color distortion and detail blurring caused by light scattering and absorption in underwater imaging technology,an improved UICEN-GAN(Underwater Image Color Correction En-hancement Network)based on GAN(Generative Adversarial Network)is proposed.Unlike traditional GAN,the proposed network adds a wide-range perception module and a dual attention mechanism at the generator header.The wide-range perception module uses a larger convolutional kernel to cover a larger receiving domain,and the du-al attention mechanism enhances the detailed information of the image by paralleling spatial and channel attention.A color correction module is added at the end.This module uses self-attention calculation to allocate relevant weights and maps image features to the RGB color space,thereby solving the problem of color distortion.The experi-mental results show that the enhancement effect of the proposed network is superior to that of other advanced net-works.The peak signal-to-noise ratio and structural similarity index of the enhanced image have increased by 10.6%and 1.8%respectively when compared with the network with the second-highest index.Good effects have been achieved in both subjective and objective evaluations.关键词
水下图像增强/生成对抗网络/颜色校正/注意力机制/卷积神经网络/深度学习/图像处理/端到端Key words
underwater image enhancement/GAN/color correction/attention mechanism/convolutional neural network/deep learning/image processing/end-to-end分类
信息技术与安全科学引用本文复制引用
亢淑洁,陈清江..基于颜色校正的GAN水下图像增强网络[J].电子科技,2026,39(10):42-51,10.基金项目
国家自然科学基金(12101482) National Natural Science Foundation of China(12101482) （12101482）
