基于原型理论的极化SAR图像特征表达

黄晓菁; 杨祥立; 黄平平; 杨文

doi:10.12000/JR15071

基于原型理论的极化SAR图像特征表达

DOI: 10.12000/JR15071

1.
(武汉大学电子信息学院武汉 430072)
2.
(内蒙古工业大学雷达技术研究所呼和浩特 010051)

基金项目:

国家自然科学基金(61271401, 61461040),内蒙古自治区科技计划项目(20140155, 20131108)

详细信息

通讯作者:
杨文yangwen@whu.edu.cn

计量
- 文章访问数: 2648
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- 被引次数: 0
出版历程
- 收稿日期: 2015-06-04
- 修回日期: 2015-12-22
- 网络出版日期: 2016-04-28

Prototype Theory Based Feature Representation for PolSAR Images

1.
(School of Electronic Information, Wuhan University, Wuhan 430072, China)
2.
(Radar Research Institute, Inner Mongolia University of Technology, Hohhot 010051, China)

Funds:

The National Natural Science Foundation of China (61271401, 61461040), The Projects of Inner Mongolia Science Technology Plan (20140155, 20131108)

摘要

摘要: 该文提出一种基于原型理论的极化SAR图像表达方法。该方法首先利用原型理论构建原型集,然后以正则化逻辑回归函数计算测试样本与每个原型集的相似度,最后通过集成投影获得图像的特征表达。在极化SAR数据上的非监督分类实验结果表明,该方法能够准确表达图像中各类地物的极化特性,达到较好的分类效果。
- 极化合成孔径雷达 /
- 特征表达 /
- 原型理论 /
- 非监督分类
Abstract: This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our method can efficiently represent polarimetric signatures of different land covers and yield satisfactory classification results.
- Polarimetric Synthetic Aperture Radar (PolSAR) /
- Feature representation /
- Prototype theory /
- Unsupervised classification

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参考文献(25)

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