EVALUATION OF POLSAR SIMILARITY MEASURES WITH SPECTRAL CLUSTERING

被引：0

作者：

Hu, Jingliang ^{[1
]}

Wang, Yuanyuan ^{[2
]}

Ghamisi, Pedram ^{[1
,2
]}

Zhu, Xiao Xiang ^{[1
,2
]}

机构：

[1] German Aerosp Ctr DLR, Remote Sensing Technol Inst IMF, Cologne, Germany

[2] Tech Univ Munich, Signal Proc Earth Observat SiPEO, Munich, Germany

来源：

2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2017年

关键词：

Polarimetric SAR; similarity measures; spectral clustering;

D O I：

暂无

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Polarimetric Synthetic Aperture Radar (PolSAR) is a valuable remote sensing data source. It is usually challenging to interpret PolSAR data, especially in urban areas, and hense, spatial clustering comes as a powerful tool for the application of PolSAR data. In data clustering, similarity measurement indexes are of great importance. By far, there are quite some similarity measures of PolSAR data. However, to our knowledge, there has no practical and systematic evaluation of the performances of these measures. In this paper, we evaluate seven different similarity measurements of PolSAR data in the context of clustering using the conventional spectral clustering algorithm.

引用

页码：3254 / 3257

页数：4

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