A Novel Supervised Classification Scheme based on Adaboost for Polarimetric SAR

摘要：

In this paper,a novel scheme for supervised classification problem of Polarimetric SAR images is proposed,which is based on Adaboost.Compared to traditional classifiers such as complex Wishart distribution based maximum likelihood classifier or Neural Network based classifier,the proposed method is more robust and flexible.Different features or parameters extracted from Polarimetric SAR data could be adopted into the scheme and a quantitative analysis on the significance of each parameter for classification could be achieved.Experiment results demonstrated the effectiveness of the proposed scheme.

作者: Chen Jiong Chen Yilun Yang Jian

作者单位: Tsinghua University University of Michigan

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）