A structured sub-pixel target detection method base on manifold learning method

摘要：

The manifold learning theory is firstly used to transform the hyperspectral images into a low-dimension feature spaces. The reconstruction error is computed to get discriminative information. Then a structured matched subspace detector is developed. This method can effectively avoid the contamination by targets and spectral anomalies to backgrounds subspace and detect sub-pixel targets with better performance than traditional methods.

关键词： Manifold Learning target detection hyperspectral images

作者: Bo Du Dengyi Zhang Pingxiang Li Tao Chen Ke Wu

作者单位: School of Computer, Wuhan University, Wuhan, China LIESMARS, Wuhan University, Wuhan, China Institute of Geophysics and Geomatics,China University of Geosciences, Wuhan, Chinaa

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）