publication . Article . 2016

Prototype Theory Based Feature Representation for PolSAR Images

Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen;
Open Access English
  • Published: 01 Apr 2016 Journal: Journal of Radars (issn: 2095-283X, eissn: 2095-283X, Copyright policy)
  • Publisher: Chinese Academy of Sciences
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.
arXiv: Computer Science::Computer Vision and Pattern RecognitionComputer Science::Graphics
free text keywords: Polarimetric Synthetic Aperture Radar (PolSAR), Feature representation, Prototype theory Unsupervised classification, Technology (General), T1-995
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