Robust hyperspectral data unmixing with spatial and spectral regularized NMF

2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010 - Workshop Program

Volumn , Issue , 2010, Pages

  Huck, A ^a   Guillaume, M ^a  

^a AIX MARSEILLE UNIVERSITÉ   (France)

Author keywords

Non negative matrix factorization (NMF); Projected gradient; Regularization; Spectral unmixing

Indexed keywords

ENDMEMBERS; ERROR RECONSTRUCTION FUNCTIONS; HYPERSPECTRAL DATA; ILL POSED; LINEAR SPECTRAL MIXING MODELS; LOW COMPLEXITY; NONNEGATIVE MATRIX FACTORIZATION; PHYSICAL CONSTRAINTS; PROJECTED GRADIENT; PURE PIXEL; REGULARIZATION; SPATIAL DISPERSION; SPECTRAL DISPERSIONS; SPECTRAL UNMIXING; UNMIXING;

BLIND SOURCE SEPARATION; DISPERSIONS; FACTORIZATION; REMOTE SENSING; SIGNAL PROCESSING;

MATRIX ALGEBRA;

EID: 78649269649     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WHISPERS.2010.5594915     Document Type: Conference Paper

References (17)

1. M. Winter, "Fast autonomous spectral end-member determination in hyperspectral data," Proc. of the 13th Int. Conf. on Applied Geologic Remote Sensing, vol. 2, pp. 337-344, 1999.
2. J. Boardman, F. Kruse, and R. Green, "Mapping targets signatures via partial unmixing of aviris data," in Summaries, JPL Airborne Geoscience Workshop, Pasaneda, Ed., Dec. 1997, pp. 23-26.
3. J. Nascimento and J. Dias, "Vertex component analysis: a fast algorithm to unmix hyperspectral data," Geosc. and Remote Sensing, IEEE Trans. on, vol. 43, no. 4, pp. 898-910, April 2005.
4. D. C. Heinz and C. I. Chang, "Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery," IEEE Trans. Geoscience and Remote Sensing, vol. 39, no. 3, pp. 529-545, mar 2001.
5. M. Craig, "Minimum-volume transforms for remotely sensed data," Geascience and remote sensing, IEEE trans. on, vol. 32, no. 3, pp. 542-552, 1994.
6. T. H. Chan, W. Ma, C. Chi, and Y. Wang, "A convex analysis based minimum-volume enclosing simplex algorithm for hyperspectral unmixing," Geosc. and Remote Sensing , IEEE Trans. on, 2009.
7. J. M. P. Nascimento and J. M. B. B. Dias, "Dependent component analysis: A hyperspectral unmixing algorithm," in Iberian Conf. on Patt. Recognition and Image Analysis, 2007, pp. II: 612-619.
8. S. Moussaoui, D. Brie, A. Mohammad-Djafari, and C. Carteret, "Separation of non-negative mixture of non-negative sources using a bayesian approach and mcmc sampling," Signal Processing, IEEE Trans. on, vol. 54, no. 11, pp. 4133-4145, Nov. 2006.
9. D. D. Lee and H. S. Seung, "Algorithms for non-negative matrix factorization," in Advances in Neural Information Proc. Systems 13: Proc. of the 2000 Conf. Cambridge, Massachusetts: MIT Press, 2001, pp. 556-562.
10. V. P. Pauca, J. Piper, and R. J. Plemmons, "Nonnegative matrix factorization for spectral data analysis," Linear Algebra and its Applications, vol. 416, no. 1, pp. 29-47, jul 2006.
11. L. Miao and H. Qi, "Endmember extraction from highly mixed data using minimum volume constrained nonnegative matrix factorization," Geoscience and Remote Sensing, IEEE Transactions on, vol. 45, no. 3, pp. 765-777, March 2007.
12. A. Huck and M. Guillaume, "Minimum dispersion constrained - non negative matrix factorization to unmix hyperspectral data," Geoscience and Remote Sensing, IEEE Trans., vol. 48, no. 6, pp. 2590-2602, 2010.
13. W. Wang and X. Zou, "Non-negative matrix factorization based on projected nonlinear conjugate gradient algorithm," in ICA Research Network InternationalWorkshop (ICARN 2008), pp. 5-8, Liverpool, UK, September 25-26, 2008.
14. T. H. Chan, W. Ma, C. Chi, and Y. Wang, "A convex analysis framework for bind separation of non-negative sources," Signal Processing, IEEE Trans. on, vol. 56, no. 10, pp. 5120-5134, Oct. 2008.
15. M. W. Berry, M. Browne, A. N. Langville, P. V. Pauca, and R. J. Plemmons, "Algorithms and applications for approximate nonnegative matrix factorization," Computational Statistics & Data Analysis, vol. 52, no. 1, pp. 155-173, September 2007.
16. Http://speclab.cr.usgs.gov/spectral-lib.html.
17. Http://aviris.jpl.nasa.gov/.