Conference Proceedings

Abstract

In this paper, variety of classifiers for supervised target classification of polarimetric synthetic aperture radar (SAR) image explained. Compared to traditional classifiers such as ML classification,complex Wishart distribution or Adabo0st classifier, the SVM (Support Vector Machine) method is more robust, accurate and flexible. This algorithm not only uses a statistical classifier, but also preserves the purity of dominant polarimetric scattering properties. Different features or parameters extracted from Polarimetric SAR data could be adopted into the scheme and a quantitative analysis on the significance of each parameter for classification could be achieved. Experiment results demonstrated the effectiveness of the SVM.