SAR Image Segmentation Method Using DP Mixture Models
Sun Li, Zhang Yanning, Tian Guangjian, Miao Ma · 2008
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.