SAR Image Segmentation Using Kernel Density Estimation on Region Adjacency Graph

摘要：

In this paper,we propose a new synthetic aperture radar (SAR) image segmentation scheme.Firstly,the SAR image is over-segmented using the mean shift (MS) algorithm while the original image discontinuity characteristics are preserved.Secondly,we propose a novel method to estimates the probability density function of each node on region adjacency graph (RAG) using kernel density estimation (K.DE) method. This estimation includes the information of similarity and proximity of any pairs of nodes at the same time. Our approach yields superior performance and also is feasible for real-time processing.

关键词： Image segmentation synthetic aperture radar (SAR) kernel density estimation (KDE) region adjacency graph (RAG) mean shift (MS)

作者: Daming Zhang Maosheng Fu Bin Luo

作者单位: School of Computer Science and Technology,Anhui University,Hefei 230039,China Department of Mathemat School of Computer Science and Technology,Anhui University,Hefei 230039,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: 668-671

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）