中文摘要：

提出了一种新的基于特征选择自适应决策树的层次分类算法,用于合成孔径雷达（synthetic apertureradar,SAR）图像的分类。采用Joint Boosting算法选择出最适用于各类的特征组合,并自适应地搜索构造出一个由两类分类器构成的层次分类器,利用特征选择结果和自适应决策树进行了SAR图像的学习和推理,实现了自动分类,在国内首批极化干涉SAR数据上的实验证明了本算法的有效性。

英文摘要：

In this paper,we propose a novel hierarchical classification algorithm based on feature selection and adaptive decision tree in SAR image classification.Firstly,Joint Boosting selects feature combination most suitable for each class;Secondly,a hierarchical classifier is searched adaptively using binary classifiers based on feature combination;finally,we perform SAR image study and inference based on feature selection results and adaptive decision tree,leading to automatic classification.Experimental results on the first batch of PolInSAR data prove the proposed approach＇s efficiency.