信息与控制2024，Vol.53Issue(3)：353-364,12.DOI:10.13976/j.cnki.xk.2024.3113
基于语义感知的多特征协同水下图像增强
Multi-feature Collaborative Underwater Image Enhancement Based on Semantic Perception
摘要
Abstract
A semantic-aware multifeature collaborative underwater image enhancement network is pro-posed for existing underwater image enhancement methods with poor defogging and color recovery effects.First,the texture and structure features of the original underwater image are fully extracted using the semantic-aware feature extraction module.Meanwhile,the degraded underwater image is input to the multiscale enhancement module for contrast enhancement and multiscale feature refine-ment,and global features of the enhanced image are extracted.Second,the multifeature fusion module modulates and fuses multibranch features in parallel to enhance the effective connection and feature.Finally,a clear underwater image is reconstructed by connecting residuals.Experi-mental results on real-world underwater datasets UIEB,EUVP,and UFO show that the proposed method has a better enhancement effect than classical algorithms based on pixel processing,physical models,and other deep learning algorithms.In terms of objective evaluation indicators,the peak signal-to-noise ratio and structural similarity of full-reference evaluation indexes are improved by 1.72％and 4.3％,respectively,and the information entropy of the no-reference evaluation index is improved by 0.32％.关键词
深度学习/图像增强/特征提取/直方图拉伸Key words
deep learning/image enhancement/feature extraction/histogram stretch分类
信息技术与安全科学引用本文复制引用
陶志勇,杨煜,林森..基于语义感知的多特征协同水下图像增强[J].信息与控制,2024,53(3):353-364,12.基金项目
辽宁省科技厅应用基础研究项目(2022JH2/101300274) （2022JH2/101300274）
辽宁省教育厅项目(LJKZ0349) （LJKZ0349）
辽宁省高等学校基本科研项目(LJKMZ20220679) （LJKMZ20220679）
