SAR Image Segmentation Method Using DP Mixture Models

被引:2
作者
Sun Li [1 ]
Zhang Yanning [1 ]
Ma Miao [1 ]
Tian Guangjian [1 ,2 ]
机构
[1] Northwest Polytech Univ, Sch Comp Sci, Xian 710072, Peoples R China
[2] Hong Kong Polytech Univ, Ctr Multimedia Signal Proc, Hong Kong, Hong Kong, Peoples R China
来源
ISCSCT 2008: INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE AND COMPUTATIONAL TECHNOLOGY, VOL 2, PROCEEDINGS | 2008年
基金
中国博士后科学基金;
关键词
Non-parametric Bayesian model; SAR image segmentation; Dirichlet process mixture model; infinite mixture model;
D O I
10.1109/ISCSCT.2008.20
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper presents a new method for segmentation of Synthetic Aperture Radar (SAR) images. Based on a non-parametric Bayesian infinite mixture model, Drichlet process mixture model cluster method is proposed to segment SAR image. The traditional finite mixture model segmentation method is adapted extensively in SAR image segmentation, but the performance and the robustness is not good enough. However, the proposed infinite mixture model can simulate the intrinsic property of SAR image and the segmentation method can determine the cluster number automatically. The experiment results on the simulated data and real data show that the proposed method gets comparative performance and robustness with the traditional methods.
引用
收藏
页码:598 / +
页数:3
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