Dark Channel Based Visibility Measuring from Daytime Scene Videos

Xiao-Han Chen,
Zhao Li,


Visibility is one of the most important factors of meteorological observation. Low visibility caused by fog often has a great impact on human production and daily life. Therefore, visibility measurements and warnings are given as early as possible to avoid accidents. This paper proposes a new visibility measuring method based on dark channel characteristics of digital images in natural scenes. It uses the means of dark channel values obtained from foggy images and high visibility reference images as inputs of a deep fully connected neural network, and then the trained model is applied to estimate visibility. Experiments conducted on a dataset contained two foggy scenes. The results demonstrate the effectiveness of our proposed method for daytime visibility measurement. At the same time, this paper proposes and designs an automatic detection system based on our algorithm. It implements the real time visibility measuring through edge computing.


Meteorological visibility, Dark channel prior, Transmission factor, Edge computing

Citation Format:
Xiao-Han Chen, Zhao Li, "Dark Channel Based Visibility Measuring from Daytime Scene Videos," Journal of Internet Technology, vol. 23, no. 3 , pp. 593-599, May. 2022.

Full Text:



  • There are currently no refbacks.

Published by Executive Committee, Taiwan Academic Network, Ministry of Education, Taipei, Taiwan, R.O.C
JIT Editorial Office, Office of Library and Information Services, National Dong Hwa University
No. 1, Sec. 2, Da Hsueh Rd., Shoufeng, Hualien 974301, Taiwan, R.O.C.
Tel: +886-3-931-7314  E-mail: jit.editorial@gmail.com