SAR Image Segmentation using Quantum Clonal Selection Clustering

摘要：

A novel clustering algorithm is proposed,which is derived from physical intuition of quantum mechanics and biological principle based on immune clonal selection. As extension ideas of scale-space clustering and support vector clustering,quantum clustering method deduces the clustering allocation by gradient descent,which is prone to getting stuck in local extremes.By designing a novel and highefficiency affinity function,we adopt an immune clonal selection algorithm with elite preservation strategy to search the global optimum. The experimental results on texture images and SAR images segmentation we demonstrate show that quantum clonal selection clustering method performs well both in precision and efficiency.

关键词： quantum clustering quantum clonal selection clustering tezture image segmentation SAR image segmentation

作者: Shuiping Gou Xiong Zhuang Licheng Jiao

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: 817-820

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）