Urban Area Extraction from Polarimetric SAR Imagery Using Only Positive Samples

摘要：

In this paper, we present a study of extracting urban areas from Polarimetric Synthetic Aperture Radar (PolSAR) images using only positive samples. We solve this problem by learning a standard binary classifier (urban/non-urban) given an incomplete set of positive samples (urban) and a set of unlabeled samples (some of which are urban and some of which are nonurban) based on the work of Elkan and Noto. Our experiments on RADARSAT-2 fully PolSAR data show that learning with only positive samples can significantly reduces the manual work to select completed positive and negative samples that required by a traditional binary classifier, while providing satisfactory results. Meanwhile, multiple diverse features can be effectively combined for better extraction accuracy.

关键词： PolSAR positive samples urban extraction

作者: Ying Liu Wen Yang Xin Xu Hong Sun

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

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 2332-2335

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）