Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (12): 133-137.

### Neighborhood weighted and sparse representation for hyperspectral image target detection

LI Ying, YANG Xiaoyuan

1. School of Mathematics and System Sciences, Beihang University, Beijing 100191, China
• Online:2015-06-15 Published:2015-06-30

### 基于邻域加权稀疏表示的高光谱图像目标探测

1. 北京航空航天大学 数学与系统科学学院，北京 100191

Abstract: A hyperspectral image target detection method based on sparse representation with neighborhood weighted is proposed. In the construction of a sparse model, the similarity of pixels is represented by the inner product of the unit pixel and the constructed image is dealt with neighborhood weighted constraints, which can provide smooth space. Furthermore, orthogonal matching pursuit algorithm based on weighted least squares is proposed to solve the problem. It can ensure the effectiveness of the parameter. The experimental results show that detection algorithm in this paper is effective and feasible.