Manifold Regularized Sparse NMF for Hyperspectral Unmixing

Hyperspectral unmixing is one of the most important techniques in analyzing hyperspectral images, which decomposes a mixed pixel into a collection of constituent materials weighted by their proportions. Recently, many sparse nonnegative matrix factorization (NMF) algorithms have achieved advanced pe...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2013-05, Vol.51 (5), p.2815-2826
Hauptverfasser:	Lu, Xiaoqiang, Wu, Hao, Yuan, Yuan, Yan, Pingkun, Li, Xuelong
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Applied geophysics Cost function Earth sciences Earth, ocean, space Exact sciences and technology Hyperspectral imaging Hyperspectral unmixing Internal geophysics manifold regularization mixed pixel nonnegative matrix factorization (NMF) Signal to noise ration Sparse matrices
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