An Unsupervised Segmentation Using the Data Log-Likelihood for Fully Polarimetric SAR Data Analysis
Konferenz: EUSAR 2008 - 7th European Conference on Synthetic Aperture Radar
02.06.2008 - 05.06.2008 in Friedrichshafen, Germany
Tagungsband: EUSAR 2008
Seiten: 4Sprache: EnglischTyp: PDFPersönliche VDE-Mitglieder erhalten auf diesen Artikel 10% Rabatt
Fang, Cao; Wen, Hong; Yirong, Wu; Yanping, Wang (National Key Laboratory of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing, China)
In this paper, an unsupervised segmentation method is proposed for fully polarimetric SAR data. The SPAN is used to separate the data into 3 parts. Then, in each of the 3 parts, we perform the H/(R)/A initialization, the merging algorithm and the estimation of the number of clusters to achieve an unsupervised segmentation. We try to keep the definition of the SPAN as long as possible during the procedure. The experimental results show that the proposed segmentation algorithm is very fast, and the performance of the segmentation still need further investigation.