Spatio-spectral remote sensing image classification with graph kernels

IEEE Geoscience and Remote Sensing Letters

Volumn 7, Issue 4, 2010, Pages 741-745

  Camps Valls, Gustavo ^a   Shervashidze, Nino ^b   Borgwardt, Karsten M ^b  

^a UNIVERSITY OF VALENCIA   (Spain)

^b MAX PLANCK INSTITUTE   (Germany)

Author keywords

Graphs; kernel methods; spatio spectral image classification; support vector machine (SVM)

Indexed keywords

AGRICULTURAL AREAS; GRAPH KERNELS; GRAPHS; HIGHER ORDER; HYPERSPECTRAL REMOTE SENSING IMAGE; KERNEL MATRICES; KERNEL METHODS; REMOTE SENSING IMAGE CLASSIFICATION; SPATIAL RELATIONS; SPECTRAL IMAGES; SUPPORT VECTOR MACHINE (SVM);

AGRICULTURAL MACHINERY; GEARS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGE RECONSTRUCTION; REMOTE SENSING;

SUPPORT VECTOR MACHINES;

EID: 77957993814     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2010.2046618     Document Type: Article

References (31)

1. T. M. Lillesand, R. W. Kiefer, and J. W. Chipman, Remote Sensing and Image Interpretation, 5th ed. New York: Wiley, 2004.
2. G. Camps-Valls and L. Bruzzone, "Kernel-based methods for hyperspectral image classification", IEEE Trans. Geosci. Remote Sens., vol. 43, no. 6, pp. 1351-1362, Jun. 2005.
3. G. Camps-Valls and L. Bruzzone, Eds., Kernel Methods for Remote Sensing Data Analysis. Oxford, U. K.: Wiley, Dec. 2009.
4. A. Plaza, J. A. Benediktsson, J. Boardman, J. Brazile, L. Bruzzone, G. Camps-Valls, J. Chanussot, M. Fauvel, P. Gamba, A. Gualtieri, and J. C. Tilton, "Recent advances in techniques for hyperspectral image processing", Remote Sens. Environ., vol. 113, no. S1, pp. 110-122, Sep. 2009.
5. P. Soille, Morphological Image Analysis: Principles and Applications. Berlin, Germany: Springer-Verlag, 2003.
6. J. A. Benediktsson, M. Pesaresi, and K. Arnason, "Classification and feature extraction for remote sensing images from urban areas based on morphological transformations", IEEE Trans. Geosci. Remote Sens., vol. 41, no. 9, pp. 1940-1949, Sep. 2003.
7. J. A. Benediktsson, J. A. Palmason, and J. R. Sveinsson, "Classification of hyperspectral data from urban areas based on extended morphological profiles", IEEE Trans. Geosci. Remote Sens., vol. 42, no. 3, pp. 480-491, Mar. 2005.
8. J. Inglada, "Automatic recognition of man-made objects in high resolution optical remote sensing images by SVM classification of geometric image features", ISPRS J. Photogramm. Remote Sens., vol. 62, pp. 236-248, 2007.
9. R. C. Dubes and A. K. Jain, "Random field models in image analysis", J. Appl. Stat., vol. 16, no. 2, pp. 131-163, 1989.
10. Q. Jackson and D. Landgrebe, "Adaptive Bayesian contextual classification based on Markov random fields", IEEE Trans. Geosci. Remote Sens., vol. 40, no. 11, pp. 2454-2463, Mar. 2002.
11. I. Tomas, "Spatial postprocessing of spectrally classified Landsat data", Photogramm. Eng. Remote Sens., vol. 46, no. 9, pp. 1201-1206, 1980.
12. J. Ton, J. Sticklen, and A. Jain, "Knowledge-based segmentation of Landsat images", IEEE Trans. Geosci. Remote Sens., vol. 29, no. 2, pp. 222-231, Mar. 1991.
13. B. Solaiman, R. Koffi, M. Mouchot, and A. Hillion, "An information fusion method for multispectral image classification postprocessing", IEEE Trans. Geosci. Remote Sens., vol. 36, no. 2, pp. 395-406, Mar. 1998.
14. Y. Zhang, "Detection of urban housing development by fusing multisensor satellite data and performing spatial feature post- classification", Int. J. Remote Sens., vol. 22, no. 17, pp. 3339-3355, Nov. 2001.
15. G. Camps-Valls, L. Gómez-Chova, J. Muñoz-Mari, J. Vila-Francés, 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)
16. G. Camps-Valls, L. Gómez-Chova, M. Muñoz Mari, J. Martinez-Ramón, and J. L. Rojo-Álvarez, "Kernel-based framework for multitemporal and multisource remote sensing data classification and change detection", IEEE Trans. Geosci. Remote Sens., vol. 46, no. 6, pp. 1822-1835, Jun. 2008.
17. M. Marconcini, G. Camps-Valls, and L. Bruzzone, "A composite semisupervised SVM for classification of hyperspectral images", IEEE Geosci. Remote Sens. Lett., vol. 6, no. 2, pp. 234-238, Feb. 2009.
18. D. Tuia, F. Ratle, A. Pozdnoukhov, and G. Camps-Valls, "Multisource composite kernels for urban-image classification", IEEE Geosci. Remote Sens. Lett., vol. 7, no. 1, pp. 88-92, Jan. 2009.
19. C. M. Bachmann, T. L. Ainsworth, and R. A. Fusina, "Exploiting manifold geometry in hyperspectral imagery", IEEE Trans. Geosci. Remote Sens., vol. 43, no. 3, pp. 441-454, Mar. 2005.
20. T. Gärtner, P. A. Flach, and S. Wrobel, "On graph kernels: Hardness results and efficient alternatives", in Proc. COLT, B. Schölkopf and M. K. Warmuth, Eds., 2003, pp. 129-143.
21. H. Kashima, K. Tsuda, and A. Inokuchi, "Marginalized kernels between labeled graphs", in Proc. ICML, San Francisco, CA, 2003, pp. 321-328.
22. N. Shervashidze and K. Borgwardt, "Fast subtree kernels on graphs", in Proc. 23rd Ann. Conf. Neural Inf. Processing Syst., Vancouver, BC, Canada, Dec. 7-10, 2009, pp. 1660-1668.
23. A. J. Smola and R. I. Kondor, "Kernels and regularization on graphs", in Proc. COLT, 2003, pp. 144-158.
24. F. Fouss, L. Yen, A. Pirotte, and M. Saerens, "An experimental investigation of graph kernels on a collaborative recommendation task", in Proc. IEEE Int. Conf. Data Mining, Los Alamitos, CA, 2006, pp. 863-868.
25. R. I. Kondor and J. D. Lafferty, "Diffusion kernels on graphs and other discrete input spaces", in Proc. ICML, 2002, pp. 315-322.
26. G. Camps-Valls, T. Bandos, and D. Zhou, "Semisupervised graph-based hyperspectral image classification", IEEE Trans. Geosci. Remote Sens., vol. 45, no. 10, pp. 3044-3054, Oct. 2007.
27. L. Gómez-Chova, G. Camps-Valls, J. Muñoz-Mari, and J. Calpe-Maravilla, "Semisupervised image classification with Laplacian support vector machines", IEEE Geosci. Remote Sens. Lett., vol. 5, no. 3, pp. 336-340, Jul. 2008.
28. L. Gómez-Chova, G. Camps-Valls, L. Lorenzo Bruzzone, and J. Calpe-Maravilla, "Mean map kernels for semisupervised cloud classification", IEEE Trans. Geosci. Remote Sens., vol. 48, no. 1, pt. 1, pp. 207-220, Jan. 2010.
29. D. Tuia and G. Camps-Valls, "Semisupervised remote sensing image classification with cluster kernels", IEEE Geosci. Remote Sens. Lett., vol. 6, no. 2, pp. 224-228, Feb. 2009.
30. L. L. Lapin, Probability and Statistics for Modern Engineering. Long Grove, IL: Waveland Press, 1998.
31. G. M. Foody, "Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy", Photogramm. Eng. Remote Sens., vol. 70, no. 5, pp. 627-633, May 2004.