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SGM to solve NMF – Application to Hyperspectral Data

Published online by Cambridge University Press:  13 March 2013

C. Theys ,
H. Lantéri  and
C. Richard
C. Theys
Affiliation:
Laboratoire Lagrange, Université de Nice Sophia-Antipolis, Observatoire de la Côte d’Azur, CNRS, Nice, France
H. Lantéri
Affiliation:
Laboratoire Lagrange, Université de Nice Sophia-Antipolis, Observatoire de la Côte d’Azur, CNRS, Nice, France
C. Richard
Affiliation:
Laboratoire Lagrange, Université de Nice Sophia-Antipolis, Observatoire de la Côte d’Azur, CNRS, Nice, France
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Abstract

This article deals with the problem of minimization of a general cost function under non-negativity and flux conservation constraints. The proposed algorithm is founded on the Split Gradient Method (SGM) adapted here to solve the Non Negative Matrix Factorization (NMF). We show that SGM can be easily regularized, allowing to introduce some physical constraints. Finally, to validate the algorithm, we propose an example of application to hyperspectral data unmixing.

Type
Research Article
Information
European Astronomical Society Publications Series , Volume 59: New Concepts in Imaging: Optical and Statistical Models , 2013 , pp. 357 - 379
Copyright
© EAS, EDP Sciences 2013

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