Integration of heterogeneous data for classification in hyperspectral satellite imagery

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 8390, Issue , 2012, Pages

  Benedetto, J ^a   Czaja, W ^a   Dobrosotskaya, J ^a   Doster, T ^a   Duke, K ^a   Gillis, D ^b  

^a UNIVERSITY OF MARYLAND   (United States)

^b NAVAL RESEARCH LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; LEARNING SYSTEMS; MODAL ANALYSIS; REMOTE SENSING; SATELLITE IMAGERY; SPECTROSCOPY;

HETEROGENEOUS DATA; HYPER-SPECTRAL IMAGERIES; HYPERSPECTRAL SATELLITE; LAPLACE OPERATOR; MACHINE LEARNING TECHNIQUES; NEW APPROACHES; SENSING MODALITIES; SPATIAL INFORMATIONS;

DATA INTEGRATION;

EID: 84869467473     PISSN: 0277786X     EISSN: 1996756X     Source Type: Conference Proceeding    
DOI: 10.1117/12.919236     Document Type: Conference Paper

References (19)

1. Schott, J., "Remote sensing: The image chain approach," Oxford University Press, New York (1997).
2. Smith, M., Johnson, P., and Adams, J., "Quantitative determination of mineral types and abundances from reectance spectra using principal components analysis," in [Lunar and Planetary Science Conference Proceedings], Lunar and Planetary Science Conference Proceedings 15, 797 (Feb. 1985).
3. Prasad, S. and Bruce, L. M., "Limitations of principal components analysis for hyperspectral target recog-nition," IEEE Geoscience and Remote Sensing Letters 5, 625 (2008).
4. Kim, D. and Finkel, L., "Hyperspectral image processing using locally linear embedding," in [Neural Engi-neering, 2003. Conference Proceedings. First International IEEE EMBS Conference on], 316-319 (March 2003).
5. Bachmann, C. M., Ainsworth, T. L., and Fusina, R. A., "Exploting manifold geometry in hyperspectral imagery," IEEE Transactions of Geoscience and Remote Sensing 43, 441-454 (March 2005).
6. Fauvel, M., Chanussot, J., and Benediktsson, J. A., "Kernel principal component analysis for the classifi-cation of hyperspectral remote sensing data over urban areas," EURASIP Journal on Advances in Signal Processing 2009.
7. Halevy, A., Extensions of Laplacian Eigenmaps for Manifold Learning, Ph.D thesis, University of Maryland, College Park (2011).
8. Belkin, M. and Niyogi, P., "Laplacian eigenmaps for dimensionality reduction and data," Computer 1396, 1373-1396 (2003).
9. Belkin, M. and Niyogi, P., "Convergence of laplacian eigenmaps," Statistics 19, 1-31 (2008).
10. Chen, J., Fang, H.-R., and Saad, Y., "Fast approximate knn graph construction for high dimensional data via recursive lanczos bisection," Journal of Machine Learning Research 10(2009), 1989-2012 (2009).
11. Benedetto, J., Czaja, W., Ehler, M., Flake, C., and Hirn, M., "Wavelet packets for multi-and hyper-spectral imagery," Proc. SPIE 7535(1), 753508 (2010).
12. Mohan, A., Sapiro, G., and Bosch, E., "Spatially coherent nonlinear dimensionality reduction and segmen-tation of hyperspectral images," IEEE Geoscience and Remote Sensing Letters 4, 206-210 (2007).
13. Tarabalka, Y., Benediktsson, J. A., and Chanussot, J., "Spectral-spatial classification of hyperspectral im-agery based on partitional clustering techniques," IEEE Transactions on Geoscience and Remote Sensing 47 (August 2009).
14. Lee, M., Bruce, L., and Prasad, S., "Concurrent spatial-spectral band grouping: Providing a spatial context for spectral dimensionality reduction," in [Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2011 3rd Workshop on], 1-4 (June 2011).
15. Camps-Valls, G., Bandos Marsheva, T. V., and Zhou, D., "Semi-supervised graph-based hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing 45(10), 3044-3054 (2007).
16. Camps-Valls, G., Gomez-Chova, L., Munoz-Mari, J., Vila-Frances, J., and Calpe-Maravilla, J., "Composite kernels for hyperspectral image classification," IEEE Geoscience and Remote Sensing Letters 3(1), 93-97 (2006).
17. Fauvel, M., Benediktsson, J. A., Chanussot, J., and Sveinsson, J. R., "Spectral and spatial classification of hyperspectral data using svms and morphological profiles," IEEE Transactions on Geoscience and Remote Sensing 46(11), 3804-3814 (2008).
18. Tarabalka, Y., Benediktsson, J. A., Chanussot, J., and Tilton, J. C., "Multiple spectral-spatial classification approach for hyperspectral data," IEEE Transactions on Geoscience and Remote Sensing 48(11), 4122-4132 (2010).
19. Bernard, K., Tarabalka, Y., Angulo, J., Chanussot, J., and Benediktsson, J. A., "Spectral-spatial classifica-tion of hyperspectral data based on a stochastic minimum spanning forest approach," IEEE Transactions on Image Processing 21(4), 2008-2021 (2012).