NDLI: Unsupervised classification based on H/alpha decomposition and Wishart classifier for compact polarimetric SAR

Content Provider	IEEE Xplore Digital Library
Author	Shenglong Guo Yurun Tian Yang Li Shiqiang Chen Wen Hong
Copyright Year	2015
Description	Author affiliation: Inst. of Electron., Beijing, China (Shenglong Guo; Yurun Tian; Yang Li; Shiqiang Chen; Wen Hong)
Abstract	In this paper, an unsupervised classification for compact polarimetry SAR (C-PolSAR) image is proposed by combining the H/α decomposition with the Wishart classifier. Firstly, H/α decomposition method is applied to the compact polarimetry (CP) data. By analyzing the different (H, a) values corresponding to the three compact polarimetry mode: the π/4, CL, and CC modes, we find that only in the CC mode, different scattering targets are distinguished well by (H, α) values. The decomposition results are used as the initial classification. Then the maximum likelihood classifier based on the complex Wishart distribution is adopted to classify the image iteratively. After four iterations, the classification results are much improved, and the classification details can be identified clearly. We use the AirSAR of San Francisco L-band data to illustrate the effectiveness of the proposed classification method.
Starting Page	1614
Ending Page	1617
File Size	1126268
Page Count	4
File Format	PDF
e-ISBN	9781479979295
DOI	10.1109/IGARSS.2015.7326093
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-26
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Scattering Entropy Training Matrix decomposition Image color analysis Synthetic aperture radar Oceans Wishart classifier Compact polarimetry SAR (C-PolSAR) Unsupervised classification classification H/α decomposition
Content Type	Text
Resource Type	Article

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