Unsupervised Image Segmentation Based On Nonsubsampled Contourlet Hidden Markov Trees Model

摘要：

Based on the shift invariance and multidirectional expansion properties of Nonsubsampled Contourlet Transform,a new image segmentation combining hidden Markov trees model with Bayesian approaches is proposed here. The training blocks can be got in presegmentation by using histogram approximation. to integrated use the information of different scales,we use the contextual model to segment raw segmentations and fuse them to get the final image.We compared our result with Wavelet domain HMTseg method and contourlet domain HMTseg method,the result shows that our method has better performance in edges but lower missed classed probability. The simulation results of synthetic mosaic image,aerial image and SAR image are showed to prove the generalization of this method.

关键词： Nonsubsampled Contourlet Hidden Markov Trees Image segmentation

作者: Fangfang Xin LiCheng Jiao Honglin Wan

作者单位: Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China,Institute of Intelligent Information Processing,Xidian University,Xian 710071,P.R.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: 485-488

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）