Ground-based Cloud Classification Using Multiple Random Projections

摘要：

　　Ground-based cloud classification plays an essential role in meteorological research and has received great concern in recent years.In this paper,a novel algorithm named multiple random projections (MRP) is proposed for ground-based cloud classification.The proposed algorithm uses an ensemble approach of MRP to obtain an optimized textons.Based on the textons,discriminative features can be obtained for classification.A series of experiments on two ground-based cloud databases (Kiel and IapCAS-E) are conducted to evaluate the efficiency of our proposed method.In addition,three current state-of-the-art methods,which include Patch,PCA,single random projection (SRP),are selected for comparison purpose.The experimental results show that our MRP method can achieved the best classification performance.

关键词： ground-based cloud classificaiton textons multiple random projections

作者: Shuang Liu Chunheng Wang Baihua Xiao Zhong Zhang Yunxue Shao

作者单位: State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences Beijing, China

会议类型: 国际会议

会议名称: 2012年遥感中的计算机视觉国际会议

会议地点: 厦门

会议语种:英文

页码: 1-6

在线出版日期: 2012-12-16（万方平台首次上网日期，不代表论文的发表时间）