Title: Review of single image defogging

Authors: Baowei Wang; Bin Niu; Peng Zhao; Neal N. Xiong

Addresses: School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), NUIST, Nanjing, 210044, China; Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing, 210044, China ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), NUIST, Nanjing, 210044, China; Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing, 210044, China ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), NUIST, Nanjing, 210044, China; Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing, 210044, China ' Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK, 74464, USA

Abstract: With the great advance of computer vision technology, the application of images in daily production work is more and more extensive. However, fairly substantial images collected in foggy weather show significant degradation. Image defogging technology is developed to solve this problem. After the defogging operation, the visual effect will be obviously improved, and it will also bring convenience to subsequent processing. This paper discusses the research background and current status of single image defogging strategies, and discusses the advantages and disadvantages of some classical algorithms. At the same time, combined with the analysis of these algorithms, some expectations are proposed.

Keywords: image defogging; image enhancement; image restoration; fusion strategy; Retinex theory; atmospheric scattering model.

DOI: 10.1504/IJSNET.2021.113630

International Journal of Sensor Networks, 2021 Vol.35 No.2, pp.111 - 120

Received: 27 Apr 2020
Accepted: 09 May 2020
Published online: 15 Mar 2021 *

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