Two-Stage Sequence Classification of PoIInSAR Imagery

摘要：

In this paper,we present a two-stage scheme for supervised classification of Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) imagery.In the first stage,a regularized logistic regression classifier is employed to generate probability vectors of object labels with polarimetric and interferometric features,respectively. The soft outputs (probability map) of previous logistic classifier with different features are concatenated as the input features of the second stage classifier-SVM classifier,which provides the final classification.We compare the twostage methods against the baseline method and show its effectiveness.

关键词： PolInSAR Scene Classification Logistic Regression Support Vector Machine

作者: Jun Wu Wen Yang Dengxin Dai Tongyuan Zou

作者单位: Signal Processing Lab,School of Electronic Information,Wuhan University,Wuhan,430079,China

会议类型: 国际会议

会议名称: 2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar(第二届亚太合成孔径雷达会议)

会议地点: 西安

会议语种:英文

页码: 494-497

在线出版日期: 2009-10-26（万方平台首次上网日期，不代表论文的发表时间）