摘要
图像去雾技术根据算法的处理方式分为两类:一类是图像增强去雾算法,涉及直方图均衡化、小波变换和基于色彩恒常理论的Retinex算法等;另一类是图像复原去雾算法,主要包括传统基于光偏振特性的多幅图像复原和基于先验假设的单幅图像复原等方法,以及基于深度学习的图像复原算法。为了今后更好地研究图像去雾技术,本文系统地回顾了图像去雾算法的发展情况,对图像去雾算法研究中存在的问题进行了分析,并尝试探讨了其发展趋势。
According to the algorithm processing method,image dehazing technology can be divided into two categories.One is image enhancement algorithm,which involves histogram equalization,wavelet transform and Retinex algorithm based on color constancy theory.The other is the image restoration and defogging algorithm,which mainly includes the traditional multi-image restoration based on the characteristics of optical polarization and the single image restoration based on a priori assumption,and the emerging image restoration algorithm based on deep learning.In order to better study the image dehazing algorithm in the future,the main development process of image dehazing techniques was reviewed in this paper,the existing problems for the study on image dehazing algorithm was analyzed,and the development trend was tried to explore.
作者
蒋华伟
杨震
张鑫
董前林
JIANG Hua-wei;YANG Zhen;ZHANG Xin;DONG Qian-lin(Key Laboratory of Grain Information Processing and Control Ministry of Education,Henan University of Technology,Zhengzhou 450001,China;College of Information Science and Engineering,Henan University of Technology,Zhengzhou 450001,China;State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines,Anhui University of Science and Technology,Huainan 232001,China)
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2021年第4期1169-1181,共13页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金项目(51677055)
河南省自然科学基金项目(162300410055)
河南省高校科技创新团队计划项目(16IRTSTHN026)
深部煤矿采动响应与灾害防控国家重点实验室开放基金项目(SKLMRDPC19KF10).
关键词
信息处理技术
雾霾图像
图像去雾
图像增强
图像复原
information processing technology
fog-degraded image
image dehazing
image enhancement
image restoration
