When pixels team up: Spatially weighted sparse coding for hyperspectral image classification

IEEE Geoscience and Remote Sensing Letters

Volumn 12, Issue 1, 2015, Pages 107-111

  Soltani Farani, Ali ^a   Rabiee, Hamid R ^a  

^a SHARIF UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Classification; dictionary learning; hyperspectral imagery (HSI); linear support vector machines (SVMs)

Indexed keywords

CLASSIFICATION (OF INFORMATION); IMAGE CLASSIFICATION; SPECTROSCOPY; SUPPORT VECTOR MACHINES;

DICTIONARY LEARNING; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL IMAGE CLASSIFICATION; HYPERSPECTRAL IMAGERY; LINEAR SUPPORT VECTOR MACHINES; SIMILAR MATERIAL; SPARSITY PATTERNS; SPATIAL NEIGHBORHOODS;

PIXELS;

EID: 84906786467     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2014.2328319     Document Type: Article

References (25)

1. J. Bioucas-Dias et al., "Hyperspectral unmixing overview: Geometrical, statistical, sparse regression-based approaches," IEEE J. Sel. Topics Appl. Earth Observ., vol. 5, no. 2, pp. 354-379, Apr. 2012.
2. I. Tosic and P. Frossard, "Dictionary learning," IEEE Signal Process. Mag., vol. 28, no. 2, pp. 27-38, Mar. 2011.
3. B. Olshausen and D. Field, "Sparse coding with an overcomplete basis set: A strategy employed by v1?" Vis. Res., vol. 37, no. 23, pp. 3311-3325, Dec. 1997. (Pubitemid 27493805)
4. M. Iordache, J. Bioucas-Dias, and A. Plaza, "Sparse unmixing of hyperspectral data," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 6, pp. 2014-2039, Jun. 2011.
5. M. Iordache, J. Bioucas-Dias, and A. Plaza, "Collaborative sparse unmixing of hyperspectral data," in Proc. IEEE Int. Geosci. Remote Sens. Symp., Jul. 2012, pp. 7488-7491.
6. M. Iordache, J. Bioucas-Dias, and A. Plaza, "Total variation spatial regularization for sparse hyperspectral unmixing," IEEE Trans. Geosci. Remote Sens., vol. 50, no. 11, pp. 4484-4502, Nov. 2012.
7. A. Charles, B. Olshausen, and C. Rozell, "Learning sparse codes for hyperspectral imagery," IEEE J. Sel. Topics Signal Process., vol. 5, no. 5, pp. 963-978, Sep. 2011.
8. J. Greer, "Sparse demixing of hyperspectral images," IEEE Trans. Image Process., vol. 21, no. 1, pp. 219-228, Jan. 2012.
9. A. Castrodad et al., "Learning discriminative sparse representations for modeling, source separation, mapping of hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 11, pp. 4263-4281, Nov. 2011.
10. A. Gualtieri, S. Chettri, R. Cromp, and L. Johnson, "Support vector machine classifiers as applied to AVIRIS data," in Proc. Airborne Geosci. Workshop, Feb. 1999, pp. 217-227.
11. G. Camps-Valls, L. Gomez-Chova, J. Munoz-Mari, J. Vila-Frances, and J. Calpe-Maravilla, "Composite kernels for hyperspectral image classification," IEEE Geosci. Remote Sens. Lett., vol. 3, no. 1, pp. 93-97, Jan. 2006. (Pubitemid 43131904)
12. J. Li, P. Reddy Marpu, A. Plaza, J. Bioucas-Dias, and J. Atli Benediktsson, "Generalized composite kernel framework for hyperspectral image classification," IEEE Trans. Geosci. Remote Sens., vol. 51, no. 9, pp. 4816-4829, Sep. 2013.
13. J. Yang, K. Yu, Y. Gong, and T. Huang, "Linear spatial pyramid matching using sparse coding for image classification," in Proc. IEEE Conf. CVPR, Jun. 2009, pp. 1794-1801.
14. B. Culpepper, J. Sohl-Dickstein, and B. Olshausen, "Building a better probabilistic model of images by factorization," in Proc. IEEE ICCV, Nov. 2011, pp. 2011-2017.
15. J. Mairal, F. Bach, and J. Ponce, "Task-driven dictionary learning," IEEE Trans. Pattern Anal. Mach. Intell., vol. 34, no. 4, pp. 791-804, Apr. 2012.
16. D. Dai and W. Yang, "Satellite image classification via two-layer sparse coding with biased image representation," IEEE Geosci. Remote Sens. Lett., vol. 8, no. 1, pp. 173-176, Jan. 2011.
17. Y. Chen, N. Nasrabadi, and T. Tran, "Hyperspectral image classification using dictionary-based sparse representation," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 10, pp. 3973-3985, Oct. 2011.
18. H. Zhang, J. Li, Y. Huang, and L. Zhang, "A nonlocal weighted joint sparse representation classification method for hyperspectral imagery," IEEE J. Sel. Topics Appl. Earth Observ., to be published.
19. P. Garrigues and B. A. Olshausen, "Group sparse coding with a Laplacian scale mixture prior," in Proc. 24th Annu. Conf. NIPS, 2010, vol. 23, pp. 1-9.
20. B. Efron et al., "Least angle regression," Ann. Statist., vol. 32, no. 2, pp. 407-499, 2004. (Pubitemid 41250302)
21. J. Mairal, F. Bach, J. Ponce, and G. Sapiro, "Online learning for matrix factorization and sparse coding," J. Mach. Learn. Res., vol. 11, pp. 19-60, Mar. 2010.
22. A. Charles and C. Rozell, "Spectral superresolution of hyperspectral imagery using reweighted-1 spatial filtering," IEEE Geosci. Remote Sens. Lett., vol. 11, no. 3, pp. 602-606, Mar. 2014.
23. C. Chih-Chung and L. Chih-Jen, "LIBSVM: A library for support vector machines," ACMTrans. Intell. Syst. Technol., vol. 2, no. 3, pp. 271-2727, Apr. 2011.
24. J. A. Richards, Remote Sensing Digital Image Analysis: An Introduction, 5th ed. New York, NY, USA: Springer-Verlag, 2013.
25. F. Girosi, "An equivalence between sparse approximation and support vector machines," Neural Comput., vol. 10, no. 6, pp. 1455-1480, Aug. 1998. (Pubitemid 128464285)