湖南大学学报（自然科学版）2024，Vol.51Issue(6)：10-19,10.DOI:10.16339/j.cnki.hdxbzkb.2024262
基于双支特征联合映射的端到端图像去雾算法
End-to-end Image Dehazing Algorithm Based on Joint Mapping of Two-Branch Features
摘要
Abstract
To address the issues of high model complexity and poor feature extraction performance in Convolutional neural network-based dehazing algorithms,this paper proposes an end-to-end image dehazing algorithm based on joint mapping of two-branch features.Firstly,the atmospheric scattering model is transformed to separate the mixed-parameter feature and the single-parameter feature model.Then two feature extraction networks,MPFEM and SPFEM are designed according to the two-branch features and the outputs are weighted by two attention mechanisms.Finally,the extracted two-branch features are sent to the restoration module to restore the clear image and perform color-enhancing to obtain the final restored effect.To avoid the loss of texture details caused by using a single loss function in the model training process,multi-scale structure similarity and mean absolute error weighting are used as the loss function.Experimental results show that the proposed algorithm has a simple network structure,obvious dehazing effect,accurate color brightness restoration,and strong edge preservation.关键词
图像去雾/卷积神经网络/双支特征/注意力机制Key words
image dehazing/convolutional neural network/two-branch features/attention mechanism分类
信息技术与安全科学引用本文复制引用
杨燕,陈阳..基于双支特征联合映射的端到端图像去雾算法[J].湖南大学学报（自然科学版）,2024,51(6):10-19,10.基金项目
国家自然科学基金资助项目(61561030),National Natural Science Foundation of China(61561030) （61561030）
甘肃省高等学校产业支撑计划项目(2021CYZC-04),Industrial Support Program of Colleges and Universities in Gansu Province(2021CYZC-04) （2021CYZC-04）
兰州交通大学教改项目(JG201928),Lanzhou Jiaotong University Teaching Reform Project(JG201928) （JG201928）
