A new non-negative matrix factorization method based on barycentric coordinates for endmember extraction in hyperspectral remote sensing

Luyan Ji; Xiurui Geng; Kai Yu; Yongchao Zhao

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A new non-negative matrix factorization method based on barycentric coordinates for endmember extraction in hyperspectral remote sensing

机译：基于重心坐标的非负矩阵分解新方法

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摘要

In this study, we present a new non-negative matrix factorization (NMF) method using the pixel's barycentric coordinates for endmember extraction, named BC-NMF. Our method applies the geometrical property of simplex in the calculation of abundance fraction. That is, for any pixel in an image, its abundance fractions are its barycentric coordinates within the endmember coordinate system. Experiments using both simulated and real hyperspectral images show that BC-NMF can generate endmembers with higher accuracy and lower computational complexity than NMF.

机译：在这项研究中，我们提出了一种新的非负矩阵分解（NMF）方法，该方法使用像素的重心坐标进行端成员提取，称为BC-NMF。我们的方法在丰度分数的计算中应用了单纯形的几何性质。即，对于图像中的任何像素，其丰度分数是其在端成员坐标系内的重心坐标。使用模拟和真实高光谱图像进行的实验表明，与NMF相比，BC-NMF可以生成精度更高且计算复杂度更低的端成员。

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《International journal of remote sensing》 |2013年第20期|6577-6586|共10页
作者
Luyan Ji; Xiurui Geng; Kai Yu; Yongchao Zhao;
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作者单位

Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;

Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;

Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;

Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
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正文语种 eng
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A new non-negative matrix factorization method based on barycentric coordinates for endmember extraction in hyperspectral remote sensing

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