华中科技大学学报（自然科学版）2025，Vol.53Issue(5)：164-170,7.DOI:10.13245/j.hust.250599
结合宽型提取和径向增强的二阶段图像去雾
Two-stage image dehazing combined with wide pattern extraction and radial enhancement
摘要
Abstract
To address the need for improving the neural network model's ability to extract features from global to local contexts and enhancing the generalization performance in haze image restoration,a two-stage image dehazing algorithm combining wide-scale extraction and radial enhancement was proposed.The proposed algorithm performed clear restoration on degraded images with haze in two stages.In the feature extraction stage,a three-branch wide-scale feature extraction structure was proposed,composed of a dual-scale Transformer module and a deformable convolution module,and this structure combined the global attention capability of the Transformer with the local perception capability of deformable convolutions to effectively perceive and extract features from hazy images.In the feature enhancement stage,a radial enhancement network consisting of dense residual blocks was utilized,and this network progressively concatenated image features from shallow to deep levels,further enhancing the extracted features.Experimental results show that the proposed network model performs exceptionally well in both synthetic datasets and real image restoration processes,showing significant haze removal effects for different haze concentrations,and the restored images exhibit natural subjective recovery and possess good generalization capabilities.关键词
图像处理/图像去雾/Transformer模型/可变形卷积/密集残差Key words
image processing/image dehazing/Transformer model/deformable convolution/dense residuals分类
计算机与自动化引用本文复制引用
杨燕,陈阳,张浩文..结合宽型提取和径向增强的二阶段图像去雾[J].华中科技大学学报（自然科学版）,2025,53(5):164-170,7.基金项目
国家自然科学基金资助项目(61561030,62063014) （61561030,62063014）
甘肃省高等学校产业支撑计划资助项目(2021CYZC-04) （2021CYZC-04）
兰州交通大学教改项目(JG201928) （JG201928）
甘肃省教育厅优秀研究生"创新之星"资助项目(2023CXZX-547). （2023CXZX-547）
