Spatial-spectral unmixing using fuzzy local information

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn , Issue , 2011, Pages 1139-1142

  Zare, Alina ^a  

^a University of Missouri   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HYPERSPECTRAL DATA; HYPERSPECTRAL UNMIXING; LOCAL INFORMATION; SPATIAL INFORMATIONS; SPECTRAL SIGNATURE; SPECTRAL UNMIXING; UNMIXING;

ALGORITHMS; ESTIMATION; GEOLOGY; PIXELS; REMOTE SENSING;

CRYPTOGRAPHY;

EID: 80955150938     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2011.6049398     Document Type: Conference Paper

References (10)

1. D. Manolakis, D. Marden, and G. A. Shaw, "Hyperspectral image processing for automatic target detection applications," Lincoln Laboratory Journal, vol. 14, no. 1, pp. 79-116, 2003.
2. N. Keshava and J. F. Mustard, "Spectral unmixing," IEEE Signal Processing Magazine, vol. 19, pp. 44-57, 2002.
3. M. Zortea and A. Plaza, "Spatial preprocessing for endmember extraction," Geoscience and Remote Sensing, IEEE Transactions on, vol. 47, no. 8, pp. 2679-2693, 2009.
4. X. Song, X. Jiang, and X. Rui, "Spectral unmixing using linear unmixing under spatial autocorrelation constraints," in Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International, 2010, pp. 975-978.
5. S. Jia and Y. Qian, "Spectral and spatial complexity-based hyperspectral unmixing," Geoscience and Remote Sensing, IEEE Transactions on, vol. 45, no. 12, pp. 3867-3879, 2007. (Pubitemid 350157825)
6. S. Krinidis and V. Chatzis, "A robust fuzzy local information c-means clustering algorithm," Image Processing, IEEE Transactions on, vol. 19, no. 5, pp. 1328-1337, May 2010.
7. A. Zare, O. Bchir, H. Frigui, and P. Gader, "Spatially-smooth piece-wise convex endmember detection," in Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2010 2nd Workshop on, 2010, pp. 1-4.
8. M. Berman, H. Kiiveri, R. Lagerstrom, A. Ernst, R. Donne, and J. F. Huntington, "ICE: A statistical approach to identifying endmembers in hyperspectral images," IEEE Transactions on Geoscience and Remote Sensing, vol. 42, pp. 2085-2095, Oct. 2004.
9. A. Zare and P. Gader, "Sparsity promoting iterated constrained endmember detection for hyperspectral imagery," IEEE Geoscience and Remote Sensing Letters, vol. 4, no. 3, pp. 446-450, July 2007. (Pubitemid 47117457)
10. (2004, Sep) AVIRIS free standard data products. Jet Propulsion Laboratory, California Institute of Technology, Pasedena, CA. URL http://aviris.jpl.nasa.gov/html/aviris.freedata.html.