A novel unsupervised iteration classification method for fully polarimetric SAR Image - 文章详情页

作者：

Yang, L. (Yang, L..) (学者：杨璐) | Zhao, Y.J. (Zhao, Y.J..) | Wang, Z.G. (Wang, Z.G..)

收录：

Scopus

摘要：

Based　on　the　theory　of　eigen-decomposition　of　fully　polarimetric　synthetic　aperture　radar　(SAR)　and　scatter　criterion　clustering　method,　an　unsupervised　iteration　classification　method　is　proposed.　It　is　simple,　flexible　and　with　high　precision.　Several　schemes　of　the　iteration　classification　method　are　given　in　this　paper.　The　characteristic　of　each　scheme　is　carefully　analyzed　according　to　the　properties　of　eigen-decomposition　and　scatter　criterion,　and　each　scheme　holds　its　own　merit.　Experiments　are　done　on　SIR-C/X-SAR　data　near　Tien　Mountains　and　perfect　classification　results　are　obtained.　More　importantly,　this　method　is　robust　and　has　high　adaptability.

关键词：

Eigen-decomposition; Fully polarimetic SAR; Scatter criterion; Unsupervised classification

作者机构：

[ 1 ] [Yang, L.]Institute of Information Engineering, Information Engineering University, Zhengzhou, China
[ 2 ] [Zhao, Y.J.]Department of Electronic Engineering, Beijing University of Technology, Beijing, China
[ 3 ] [Wang, Z.G.]Institute of Information Engineering, Information Engineering University, Zhengzhou, China

通讯作者信息：

杨璐
[Yang, L.]Institute of Information Engineering, Information Engineering University, Zhengzhou, China

电子邮件地址：

goldstone18@126.com

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