Learning Based Visibility Measuring with Images

Xu-Cheng Yin, Tian-Tian He, Hong-Wei Hao, Xi Xu, Xiao-Zhong Cao, Qing Li

Abstract: Visibility is one of the major items of meteorological observation. Its accuracy is very important to air, sea and highways and transport. A method of visibility calculation based on image analysis and learning is introduced in this paper. First, visibility image is effectively represented by contrast based vision features. Then, a Supported Vector Regression (SVR) based learning system is constructed between image features and the target visibility. Consequently, visibility can be measured directly from a single inputting image with this learning system. The method makes use of the existing video cameras to calculate visibility in real time. Specific experiments show that this method has the characteristic of low cost, fast calculation, and convenience. Moreover, our proposed technology can be used anywhere to measure visibility.