SAR Image Segmentation Based on Immune Greedy Spectral Clustering

摘要：

In this paper we propose a novel spectral clustering algorithm called Immune Greedy Spectral Clustering Algorithm,which introduces immune clone selection algorithm instead of greedy selection to choose a subset before greedy spectral embedding without any prior experiment know ledge. As we know,Nystrom algorithm is a random selecting method which depends so much on the selecting result so that the clustering result fluctuates obviously.Greedy spectral clustering algorithm acquires a subset called dictionary by greedy selection algorithm so that the result could be more stable and better.I low ever,to choose an appropriate input tolerance,we need prior experiment knowledge about the relationship between tolerance and select number.Moreover,since the criterion used for greedy selection is the distance in feature space between a candidate example and its projection on the subspace spanned by selected examples,we need to compute every example point one by one to get the error of using the selected examples to approximate the candidate example and then decide whether to choose it.So the time expense increases inevitable.Considering all above,we present a new method called Immune Greedy spectral Clustering Algorithm. The experimental results show that Immune Greedy Spectral Clustering Algorithm need no prior experiment knowledge and could save time compared with greedy spectral clustering while getting a better accuracy rate compared with Nystrom algorithm.

关键词： spectral clustering Immune Clone Selection Nystrom algorithm greedy spectral embedding

作者: S.P.Gou J.Zhang L.C.Jiao

作者单位: Key laboratory of Intelligent Perception and Image Understanding for the Ministry of Education,Institute of Intelligent Information Processing.Xidian University.Xian 710071.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: 672-675

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）