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基于约束非负矩阵分解的混合象元分解新方法
引用本文:吕亚丽,赵辽英.基于约束非负矩阵分解的混合象元分解新方法[J].杭州电子科技大学学报,2009,29(4).
作者姓名:吕亚丽  赵辽英
作者单位:杭州电子科技大学计算机应用研究所,浙江,杭州,310018
基金项目:浙江省高校优秀青年教师资助项目 
摘    要:针对高光谱混合象元分解中顶点成分分析要求每一端元在图像中至少存在一个纯象元的不足,以及非负矩阵分解易受初值影响产生局部最小的问题,提出了一种高光谱遥感图像混合象元分解的新方法。该方法用顶点成分分析求得的端元和最小二乘法求得的丰度作为平滑约束非负矩阵分解方法迭代的初始值来实现混合象元分解。通过对模拟高光谱数据和真实遥感影像的仿真研究,结果表明新方法分解混合象元精度略优于顶点成分分析方法,但明显好于约束的非负矩阵分解方法。

关 键 词:混合象元分解  顶点成分分析  最小二乘  约束的非负矩阵分解

New Scheme for Decomposition of Mixed Pixels Based on Constrained Nonnegative Matrix Factorization
LV Ya-li,ZHAO Liao-ying.New Scheme for Decomposition of Mixed Pixels Based on Constrained Nonnegative Matrix Factorization[J].Journal of Hangzhou Dianzi University,2009,29(4).
Authors:LV Ya-li  ZHAO Liao-ying
Affiliation:LV Ya-li; ZHAO Liao-ying(Institute of Computer Application; Hangzhou Dianzi University; Hangzhou Zhejiang 310018; China);
Abstract:In the decomposition of mixed pixels of hyperspectral remote sensing images,the vertex component analysis(VCA) needs that there is at least one pure pixel for every endmember existing in the images,and nonnegative matrix factorization(NMF) easily result in the problem of local minimum,owing to the influence of algorithm initializations.To solve the problems,this paper presents a new scheme based on the smooth constrained NMF(CNMF).We adopt the endmembers extracted by VCA,and abundance obtained by least squa...
Keywords:decomposition of mixed pixels  vertex component analysis  least squares  constrained nonnegative matrix factorization
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