Collaborative nonnegative matrix factorization for remotely sensed hyperspectral unmixing

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn , Issue , 2012, Pages 3078-3081

  Li, Jun ^a,b   Bioucas Dias, Jose M ^b   Plaza, Antonio ^a  

^a UNIVERSITY OF EXTREMADURA   (Spain)

^b INSTITUTO DE TELECOMUNICAÇÕES   (Portugal)

Author keywords

collaborativity; Hyperspectral imaging; spectral unmixing

Indexed keywords

COLLABORATIVITY; ENDMEMBERS; HYPERSPECTRAL IMAGING; HYPERSPECTRAL UNMIXING; NONNEGATIVE MATRIX FACTORIZATION; SINGLE-STEP; SPECTRAL UNMIXING; SUBSPACE IDENTIFICATION;

ALGORITHMS; GEOLOGY; SPECTROSCOPY;

REMOTE SENSING;

EID: 84873125367     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2012.6350775     Document Type: Conference Paper

References (18)

1. A. Plaza, Q. Du, J. Bioucas-Dias, X. Jia, and F. Kruse, "Foreword to the special issue on spectral unmixing of remotely sensed data," IEEE Trans. Geo. Rem. Sens., vol. 49, no. 11, pp. 4103-4110, 2011.
2. Q. Du, N. Raksuntorn, N. H. Younan, and R. L. King, "End-member extraction for hyperspectral image analysis," Applied Optics, vol. 47, pp. 77-84, 2008.
3. M. Parente and A. Plaza, "Survey of geometric and statistical unmixing algorithms for hyperspectral images," Proceedings of the 2nd IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), pp. 1-4, Reykjavik, Iceland, Jun. 14-16, 2010.
4. J. M. Bioucas-Dias and A. Plaza, "Hyperspectral unmixing: geometrical, statistical, and sparse regression-based approaches," Proceedings of SPIE, Image and Signal Processing for Remote Sensing XVI, vol. 7830, pp. 1-15, Toulouse, France, Sept. 20-23, 2010.
5. C.-I Chang and Q. Du, "Estimation of number of spectrally distinct signal sources in hyperspectral imagery," IEEE Trans. Geo. Rem. Sens., vol. 42, no. 3, pp. 608-619, 2004.
6. J. M. Bioucas-Dias and J. M. P. Nascimento, "Hyperspectral subspace identification," IEEE Trans. Geo. Rem. Sens., vol. 46, no. 8, pp. 2435-2445, 2008.
7. N. Keshava and J. F. Mustard, "Spectral unmixing," IEEE Signal Processing Magazine, vol. 19, no. 1, pp. 44-57, 2002.
8. M. D. Craig, "Minimum-volume transforms for remotely sensed data," IEEE Trans. Geo. Rem. Sens., vol. 32, pp. 542-552, 1994.
9. L. Miao and H. Qi, "Endmember extraction from highly mixed data using minimum volume constrained nonnegative matrix factorization," IEEE Trans. Geo. Rem. Sens., vol. 45, no. 3, pp. 765-777, 2007.
10. J. Li and J. Bioucas-Dias, "Minimum volume simplex analysis: a fast algorithm to unmix hyperspectral data," Proc. IEEE International Geoscience and Remote sensing Symposium, vol. 3, pp. 250-253, 2008.
11. J. Bioucas-Dias, "A variable splitting augmented lagragian approach to linear spectral unmixing," Proceedings of the 1st IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), pp. 1-4, Grenoble, France, Aug. 26-28, 2009.
12. Tsung-Han Chan, Chong-Yung Chi, Yu-Min Huang, and Wing-Kin Ma, "A convex analysis-based minimum-volume enclosing simplex algorithm for hyperspectral unmixing," IEEE Transactions on Signal Processing, vol. 57, pp. 4418-4432, 2009.
13. A. Huck, M. Guillaume, and J. Blanc-Talon, "Minimum dispersion constrained nonnegative matrix factorization to unmix hyperspectral data," IEEE Transactions on Geoscience and Remote Sensing, vol. 48, no. 6, pp. 2590 -2602, june 2010.
14. J. M. Bioucas-Dias and J. Nascimento, "Hyperspectral unmixing based on mixtures of Dirichlet components," IEEE Trans. Geo. Rem. Sens., 2011, in press.
15. J. Bioucas-Dias and M. Figueiredo, "An alternating direction algorithm for collaborative hierarchical sparse regularization," Technical Report, IST, 2011.
16. M. Berman, H. Kiiveri, R. Lagerstrom, A. Ernst, R. Dunne, and J. F Huntington, "ICE: a statistical approach to identifying endmembers in hyperspectral images," IEEE Trans. Geo. Rem. Sens., vol. 42, no. 10, pp. 2085-2095, 2004.
17. M. Schmidt M. Arngren and J. Larsen, "Bayesian nonnegative matrix factorization with volume prior for unmixing of hyperspectral images," Journal of Signal Processing Systems, vol. 10, pp. 1-18, 2009.
18. J. M. P. Nascimento and J. M. Bioucas-Dias, "Vertex component analysis: A fast algorithm to unmix hyperspectral data," IEEE Trans. Geo. Rem. Sens., vol. 43, no. 4, pp. 898-910, 2005.