Improved ISOMAP Algorithm for Anomaly Detection in Hyperspectral Images

摘要：

In this paper, ISOMAP algorithm is applied into anomaly detection on the basis of feature analysis in hyperspectral images. Then an improved ISOMAP algorithm is developed against the limitation existed in ISOMAP algorithm. The improved ISOMAP algorithm selects neighborhood according to spectral angel, thus avoiding the instability of the neighborhood in the high-dimension spectral space. Experimental results show the effectiveness of the algorithm in improving the detection performance.

关键词： manifold learning ISOMAP anomaly detection hyperspectral RX spectrum ananlysis

作者: Liangliang Wang Zhiyong Li Jixiang Sun Chun Du

作者单位: School of Electronic Science and Engineering National University of Defense Technology Changsha, 410073, Hunan, China

会议类型: 国际会议

会议名称: 2010 International Conference on Software and Computing Technology(2010年软件与计算机技术国际会议 ICSCT 2010)

会议地点: 昆明

会议语种:英文

页码: 875-878

在线出版日期: 2010-10-17（万方平台首次上网日期，不代表论文的发表时间）