Hyperspectral image segmentation using spatial-spectral graphs

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 8390, Issue , 2012, Pages

  Gillis, David B ^a   Bowles, Jeffrey H ^a  

^a NAVAL RESEARCH LABORATORY   (United States)

Author keywords

Classification; Graph; Hyperspectral; Nonlinear; Segmentation; Spatial spectral

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); GRAPHIC METHODS; IMAGE SEGMENTATION; INDEPENDENT COMPONENT ANALYSIS; LAPLACE TRANSFORMS; SPECTROSCOPY;

GRAPH; HIGH DIMENSIONAL DATA; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL; HYPERSPECTRAL IMAGE DATAS; NONLINEAR; SPATIAL-SPECTRAL; SPECTRAL GRAPH THEORY;

GRAPH THEORY;

EID: 84881180148     PISSN: 0277786X     EISSN: 1996756X     Source Type: Conference Proceeding    
DOI: 10.1117/12.919743     Document Type: Conference Paper

References (13)

1. Mardia K.V, Kent J.T., and Bibby J.M., [Multivariate Analysis], Academic Press, San Diego, CA, 397-404 (2003).
2. Bachmann, C.M., Ainsworth, T.L., Fusina, R.A., "Exploiting manifold geometry in hyperspectral imagery," IEEE Transactions on Geoscience and Remote Sensing, 43 (3), 441-454 (2005).
3. Roweis, S.T., Saul, L.K., "Nonlinear dimensionality reduction by locally linear embedding," Science, 290 (5500), pp. 2323-2326 (2000).
4. Tenenbaum, J.B., De Silva, V., Langford, J.C., "A global geometric framework for nonlinear dimensionality reduction," Science, 290 (5500), pp. 2319-2323 (2000).
5. Belkin, M., Niyogi, P., "Laplacian eigenmaps for dimensionality reduction and data representation," Neural Computation, 15 (6), pp. 1373-1396 (2003).
6. Shi, J., Malik, J., "Normalized cuts and image segmentation," IEEE Transactions on Pattern Analysis and Machine Intelligence, 22 (8), pp. 888-905 (2000).
7. Camps-Valls, G., Bandos Marsheva, T.V., Zhou, D., "Semi-supervised graph-based hyperspectral image classification," IEEE Transactions on Geoscience and Remote Sensing, 45 (10), pp. 3044-3054 (2007).
8. Basener, B., Ientilucci, E.J., Messinger, D.W., "Anomaly detection using topology," Proc. SPIE 6565 (2007).
9. Camps-Valls, G., Shervashidze, N., Borgwardt, K.M. "Spatio-spectral remote sensing image classification with graph kernels" IEEE Geoscience and Remote Sensing Letters, 7 (4), pp. 741-745 (2010).
10. http://www.agc.army.mil/hypercube
11. Lucke, R.L., et al., "Hyperspectral Imager for the Coastal Ocean: Instrument description and first images," Applied Optics, 50 (11), pp. 1501-1516 (2011).
12. Hartigan, J. A. and Hartigan P. M., "The Dip Test of Unimodality," Annals of Statistics, 13 (1) pp. 70-84 (1985)
13. Chung, F. [Spectral Graph Theory], American Mathematical Society, 1996.