Unsupervised classification of polarimetric SAR Image by Quad-tree Segment and SVM

@article{Yong2007UnsupervisedCO,
  title={Unsupervised classification of polarimetric SAR Image by Quad-tree Segment and SVM},
  author={Jiang Yong and Zhang Xiao-ling and Shi Jun},
  journal={2007 1st Asian and Pacific Conference on Synthetic Aperture Radar},
  year={2007},
  pages={480-483}
}
This paper presents a new method for unsupervised terrain classification using fully polarimetric synthetic aperture radar image based on quad-tree segment and support vector machine techniques. This unsupervised classification method begins with quad-tree segment technique that ensures each segment contains the data of only one cluster. Then, the feature vectors are constructed by sampling those segments using polarimetric covariance matrix. Then, the feature vectors of the samples of every… CONTINUE READING

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