Automatic cloud and cloud shadow detection in GF-1 WFV imagery using multiple features
Zhiwei Li, Huanfeng Shen, Huifang Li, Liangpei Zhang · 2016
The cloud and cloud shadow are difficult to capture accurately in optical imagery because of insufficient spectral information. In this paper, an automatic multiple features combined (MFC) method is proposed for cloud and cloud shadow detection in GF-1 WFV imagery which includes three visible and one near-infrared bands. The local optimization strategy with guided filtering, and the proposed object-based filter combining geometry and texture features are used in the proposed method to refine cloud detection results and exclude non-cloud bright objects. The experimental results indicate that MFC performs well under different conditions.