| 利用特征选择自适应决策树的层次SAR图像分类 |
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| 引用本文： | 何楚,刘明,许连玉,刘龙珠. 利用特征选择自适应决策树的层次SAR图像分类[J]. 武汉大学学报(信息科学版), 2012, 37(1): 46-49 |
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| 作者姓名： | 何楚 刘明 许连玉 刘龙珠 |
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| 作者单位： | 武汉大学电子信息学院,武汉市珞喻路129号,430079 |
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| 基金项目： | 国家973计划资助项目，国家自然科学基金资助项目，武汉大学测绘遥感信息工程国家重点实验室专项科研经费资助项目 |
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| 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。
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| 关 键 词： | 合成孔径雷达 图像分类 层次分类算法 自适应决策树 特征选择 |
A Hierarchical Classification Method Based on Feature Selection and Adaptive Decision Tree for SAR Image |
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| HE Chu,LIU Ming,XU Lianyu,LIU Longzhu. A Hierarchical Classification Method Based on Feature Selection and Adaptive Decision Tree for SAR Image[J]. Geomatics and Information Science of Wuhan University, 2012, 37(1): 46-49 |
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| Authors: | HE Chu LIU Ming XU Lianyu LIU Longzhu |
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| Affiliation: | 1(1 School of Electronic Information,Wuhan University,129 Luoyu Road,Wuhan 430079,China) |
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| Abstract: | 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. |
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| Keywords: | synthetic aperture radar image classification hierarchical classification algorithm adaptive decision tree featureselection |
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