Non-negative Matrix Factorization Features from Spectral Signatures of AVIRIS Images

被引：9

作者：

Kaarna, Arto ^{[1
]}

机构：

[1] Lappeenranta Univ Technol, Dept Informat Technol, FIN-53851 Lappeenranta, Finland

来源：

2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8 | 2006年

关键词：

D O I：

10.1109/IGARSS.2006.145

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

In this study we use non-negative matrix factorization (NMF) in deriving feature vectors from a set of spectral signatures. The purpose is to demonstrate the differences between the NMF and PCA feature vectors. The experiments show that NMF feature vectors are providing local features in spectral domain compared to the holistic features of PCA.

引用

页码：549 / 552

页数：4

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