哈尔滨工程大学学报Issue(5)：637-641,5.DOI:10.3969/j.issn.1006-7043.201304077
利用独立性约束非负矩阵分解的高光谱解混算法
Hyperspectral unmixing algorithm using the independent constrained nonnegative matrix factorization
杨秀坤 1王东辉1
作者信息
- 1. 哈尔滨工程大学 信息与通信工程学院，黑龙江 哈尔滨 150001
- 折叠
摘要
Abstract
In order to overcome the drawbacks of local minima caused by non-convexity of the classical nonnegative matrix factorization(NMF)objective function,and to achieve the optimal solution of hyperspectral unmixing,a new hyperspectral unmixing algorithm based on the NMF of independently constrained endmember(I-NMF)is pro-posed by introducing the constraints of the fourth order cumulant of endmember spectrum mathematical expectation and negentropy. Projected gradient is utilized as the iterative method for the NMF. The proposed I-NMF algorithm not only takes advantage of the NMF but also considers the independence of the endmember spectra,and is suitable for mixed pixel decomposition of non pure pixels. Simulation and real data experiments show that the I-NMF algo-rithm can accurately decompose mixed pixels,and the anti-noise ability is superior.关键词
高光谱混合像元分解/非负矩阵分解/独立性/四阶累积量/负熵Key words
hyperspectral unmixing/nonnegative matrix factorization(NMF)/independence/fourth order cumu-lant/negentropy分类
信息技术与安全科学引用本文复制引用
杨秀坤,王东辉..利用独立性约束非负矩阵分解的高光谱解混算法[J].哈尔滨工程大学学报,2014,(5):637-641,5.
