ICSA based Projection Pursuit Clustering with LDA indez and its Application in SAR Image Segmentation

摘要：

The performance of the traditional clustering algorithm is not always satisfied with the highdimensional datasets,which make clustering method limited in many application. To solve this problem,Projection Pursuit with LDA index based on Immune Clonal Selection Algorithm is proposed in this paper.Projection pursuit strategy can maintain consistent Euclidean distances between points in the low-dimensional embeddings where the ICSA is used to search optimal projection direction.In the proposed algorithm,k-mean clustering algorithm is used to partition the reduced data and give labels to LDA index,and iterations have been done for several times can converge quickly to obtain a clustering result. The experimental results on UCI data show that the present method has better clustering accuracy compared with traditional linear dimension reduction method for principle component analysis (PCA). And the experiments on SAR image segmentation also have a good performance.

关键词： Projection Pursuit LDA indez Immune Clonal select Algorithm K-means SAR image segmentation

作者: Shuiping Gou Jing Feng Licheng Jiao Xiao He

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: 701-704

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）