计算机工程与应用Issue(12)：133-137,5.DOI:10.3778/j.issn.1002-8331.1403-0344
基于邻域加权稀疏表示的高光谱图像目标探测
Neighborhood weighted and sparse representation for hyperspectral image target detec-tion
摘要
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.关键词
高光谱图像/目标探测/稀疏表示/邻域加权Key words
hyperspectral image/target detection/sparse representation/neighborhood weighted分类
信息技术与安全科学引用本文复制引用
李莹,杨小远..基于邻域加权稀疏表示的高光谱图像目标探测[J].计算机工程与应用,2015,(12):133-137,5.基金项目
国家自然科学基金（No.61271010）。 （）
