Sparse Representation based Spectral Clustering for SAR Image Segmentation

摘要：

A new method，sparse representation based spectral clustering(SC)with Nystr6m method，is proposed for synthetic aperture radar(SAR)image segmentation．Different from the conventional SC，this proposed technique is developed by using the sparse coefficients which obtained by solving Z l minimization problem to construct the affinity matrix and the Nystr6m method is applied to alleviate the segmentation process．The advantage of our proposed method is that we do not need to select the scaling parameter in the Gaussian kernel function artificially．We apply the proposed method，k-means and the classic spectral clustering algorithm with Nystr6m method to SAR image segmentation．The results show that compared with the other two methods，the proposed method can obtain much better segmentation results．

关键词： sparse representation spectral clustering synthetic aperture radar t1 minimization

作者: Xiangrong Zhang Zhengli Wei Jie Feng Licheng Jiao

作者单位: Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education，Xidian Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education，Xidian

会议类型: 国际会议

会议名称: 第七届多光谱图象处理与模式识别国际学术会议

会议地点: 桂林

会议语种:英文

页码: 1-6

在线出版日期: 2011-11-01（万方平台首次上网日期，不代表论文的发表时间）