Keywords: Haze removal algorithm, image enhancement, physics model, neural network.
Research progress and applications of image defogging algorithms
Yi Chen1,*, Shiju Yan1,*, Yunhua Xu1, Linping Gu2
1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. 2Shanghai Lung Cancer Center, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China.
*The authors contribute equally.
Address correspondence to: Shiju Yan, School of Health Science and Engineering, University of Shanghai for Science and Technology, No.516 Jungong Road, Shanghai 200093, China. Tel: 18956153985, E-mail: yanshiju@usst.edu.cn.
Received April 25, 2023; Accepted August 28, 2023; Published September 30, 2023
DOI: https://doi.org/10.61189/145362zgyopx
Highlights
● The mainstream defogging algorithms can be classified into three categories based on their principles: image enhancement-based, physical model-based, and neural network-based.
● This paper aims to introduce and explore these categories, as well as to provide an outlook on the application and possible future development directions of defogging algorithms.
Abstract
Keywords: Haze removal algorithm, image enhancement, physics model, neural network.