alexa Detecting Foggy Images and Estimating the Haze Degree Factor
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
Open Access

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Research Article

Detecting Foggy Images and Estimating the Haze Degree Factor

Jun Mao1,2*, Uthai Phommasak2, Shinya Watanabe2 and Hiroyuki Shioya2

1College of Computer Science and Technology, Henan Polytechnic University, 2001, Century Avenue, Jiaozuo (454003), Henan, P.R. China

2Department of Information and Electronic Engineering, Muroran Institute of Technology, Mizumoto, Muroran 050-8585, Japan

*Corresponding Author:
Jun Mao
Department of Information and Electronic Engineering
Muroran Institute of Technology
Mizumoto, Muroran 050-8585,Japan
E-mail: 12092002@mmm.muroran-it.ac.jp

Received Date: September 06, 2014; Accepted Date: September 25, 2014; Published Date: September 28, 2014

Citation: Mao J, Phommasak U, Watanabe S, Shioya H (2014) Detecting Foggy Images and Estimating the Haze Degree Factor. J Comput Sci Syst Biol 7:226-228.doi:10.4172/jcsb.1000161

Copyright: 2014 Mao J, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Limited visibility in haze weather strongly influences the accuracy and the general functions of almost outdoor video surveillance or driver assistance systems. Actual weather condition is valuable information to invoke corresponding approaches. Based on the atmospheric scattering model analysis and the statistics of various outdoor images, for most foggy images, we find that the lowest and highest value in color channels tends to be the same value of atmospheric light. A function for estimating the haze degree is developed for the automatic detection of the foggy image with different haze degrees. Experimental results show that our haze classification method achieves high performance.

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