Ground-based Cloud Detection Using Automatic Graph Cut

Abstract

Clouds are one of the most important meteorological phenomena related to the hydrological cycle and affect earth radiation balance. Ground-based cloud classification, as a key component of cloud analysis has received great concern in recent years and a number of algorithms have been proposed. However, there is no comprehensive study concerning the different classification methods. In this paper, we first make a survey on various classification methods. Further, we detail the current algorithms for classification and give theoretical analysis. Finally, we evaluate the performance of different algorithms under two ground-based cloud datasets. The experimental findings firmly justify our theoretical analysis.