Unmixing of Hyperspectral Images using Bayesian Non-negative Matrix Factorization with Volume Prior-Reference-Cited by-同舟云学术

Unmixing of Hyperspectral Images using Bayesian Non-negative Matrix Factorization with Volume Prior

Published:2010-10-01 Issue:3 Volume:65 Page:479-496
ISSN:1939-8018
Container-title:Journal of Signal Processing Systems
language:en
Short-container-title:J Sign Process Syst

Author:

Arngren Morten,Schmidt Mikkel N.,Larsen Jan

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Modelling and Simulation,Information Systems,Signal Processing,Theoretical Computer Science,Control and Systems Engineering

Link

http://link.springer.com/content/pdf/10.1007/s11265-010-0533-2.pdf

Reference31 articles.

1. Arngren, M., Schmidt, M., & Larsen, J. (2009). Bayesian nonnegative matrix factorization with volume prior for unmixing of hyperspectral images. In Machine learning for signal processing, IEEE workshop on (MLSP). doi: 10.1109/MLSP.2009.5306262 .

2. Arngren, M., Schmidt, M. N., & Larsen, J. (2010). Unmixing of hyperspectral images using Bayesian nonnegative matrix factorization with volume prior. Technical note. http://www.imm.dtu.dk/pubdb/p.php?5836 .

3. Arngren, M., Schmidt, M. N., & Larsen, J. (2010). Unmixing of hyperspectral images using bayesian nonnegative matrix factorization with volume prior, Matlab toolbox. http://www.imm.dtu.dk/pubdb/p.php?5834 .

4. Berman, M., Kiiveri, H., Lagerstrom, R., Ernst, A., Dunne, R., & Huntington, J. (2004). ICE: A statistical approach to identifying endmembers in hyperspectral images. IEEE Transactions on Geoscience and Remote Sensing, 42(10), 2085–2095.

5. Bioucas-Dias, J., & Nascimento, J. (2008). Hyperspectral subspace identification. IEEE Transactions on Geoscience and Remote Sensing, 46(8), 2435–2445.

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