A New Method for Polarimetric SAR Image Classification
In this paper,the authors propose a new method for supervised target classification of polarimetric synthetic aperture radar (SAR) image,by using the optimization of polarimetric contrast enhancement (OPCE).First,using the idea of the generalized optimization of polarimetric contrast enhancement (GOPCE),the authors modify the model with three polarimetric parameters which are related to the physics of the scattering mechanisms.It leads to enlarge the difference between two categories and improve the classification results. A new classification approach is then proposed,it is similar to a single binary tree,which the misclassification between the classes with a big power difference is minimal. After the classified results are obtained by the combination of FisherOPCE and polarimetric parameters,the coefficients of the scattering parameters information of every two adjacent classes will be used as the last discrimination for final classification results. The effectiveness of the proposed algorithm is demonstrated by using a NASA/JPL AIRSAR L-band image over San Francisco.
Fisher criterion optimization of polarimetric contrast enhancement polarimetric SAR supervised classification
J.J.Yin J.Yang Y.Yamaguchi
Department of Electronic Engineering,Tsinghua University,Beijing,100084,China Department of Information Engineering,Niigata University,Niigata,950-2181,Japan
国际会议
2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar(第二届亚太合成孔径雷达会议)
西安
英文
733-737
2009-10-26（万方平台首次上网日期，不代表论文的发表时间）