摘要
为解决复杂的室外图像进行去雾,依然会有雾气残留,甚至出现颜色失真和纹理丢失问题,提出一种基于稠密残差块与通道像素注意力的图像去雾网络,利用稠密残差块对有雾图像进行特征提取和融合,用带通道像素注意力机制的修复模块对特征图进行颜色和纹理上的修复。实验结果表明:该方法在客观评价指标和主观视觉质量上都有明显提升,有效避免了去雾过程中的颜色失真、纹理丢失和雾气残留问题。
A lot of research achievements have been made in image dehazing based on neural network,but there aiming at the fog residue,even the color distortion and texture loss,in complex outdoor image dehazing,an image dehazing network based on densely connected residual block and channel pixel attention is proposed.Densely connected residual blocks are used to extract and fuse the features of foggy images,and the repair module with channel pixel attention mechanism is used to repair the color and texture of the feature maps.The experimental results show that,compared with the existing methods,the proposed method and significantly improves the objective evaluation index and subjective visual quality,effectively avoid the color distortion,texture loss and residual fog in the process of image dehazing.
作者
金炜东
张述礼
唐鹏
张曼
Jin Weidong;Zhang Shuli;Tang Peng;Zhang Man(School of Electrical Engineering,Southwest Jiaotong University,Chengdu 610031,China;China-ASEAN International Joint Laboratory of Integrated Transport,Nanning University,Nanning 530200,China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2022年第8期1663-1673,共11页
Journal of System Simulation
基金
国家重点研发计划(2016YFB1200401-102F)。
关键词
图像去雾
稠密残差块
注意力机制
颜色失真
细节纹理
image dehazing
densely connected residual block
attention mechanism
color distortion
detail texture
