Multiple spectral spatial classification approach for hyperspectral data

IEEE Transactions on Geoscience and Remote Sensing

Volumn 48, Issue 11, 2010, Pages 4122-4132

  Tarabalka, Yuliya ^a,b   Benediktsson, Jón Atli ^a   Chanussot, Jocelyn ^b   Tilton, James C ^c  

^a UNIVERSITY OF ICELAND   (Iceland)

^b GIPSA LAB   (France)

^c NASA GODDARD SPACE FLIGHT CENTER   (United States)

Author keywords

Classification; hyperspectral images; minimum spanning forest (MSF); multiple classifiers (MCs); segmentation

Indexed keywords

CLASSIFICATION; HYPERSPECTRAL IMAGES; MINIMUM SPANNING FOREST (MSF); MULTIPLE CLASSIFIERS; SEGMENTATION;

CLASSIFIERS; PIXELS;

IMAGE SEGMENTATION;

ACCURACY ASSESSMENT; AIRBORNE SENSING; DATA SET; FOREST ECOSYSTEM; IMAGE CLASSIFICATION; MAPPING METHOD; PIXEL; SEED; SEGMENTATION; SPATIAL ANALYSIS; SPECTRAL ANALYSIS; TREE;

EID: 78049241977     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2010.2062526     Document Type: Article

References (45)

1. C.-I Chang, Hyperspectral Data Exploitation: Theory and Applications. New York: Wiley-Interscience, 2007.
2. R. O. Green, M. L. Eastwood, C. M. Sarture, T. G. Chrien, M. Aronsson, B. J. Chippendale, J. A. Faust, B. E. Pavri, C. J. Chovit, M. S. Solis, M. R. Olah, and O. Williams, "Imaging spectroscopy and the Airborne Visible Infrared Imaging Spectrometer (AVIRIS)," Remote Sens. Environ., vol. 65, no. 3, pp. 227-248, Sep. 1998.
3. D. A. Landgrebe, Signal Theory Methods in Multispectral Remote Sensing. New York: Wiley, 2003.
4. P. K. Goel, S. O. Prasher, R. M. Patel, J. A. Landry, R. B. Bonnell, and A. A. Viau, "Classification of hyperspectral data by decision trees and artificial neural networks to identify weed stress and nitrogen status of corn," Comput. Electron. Agric., vol. 39, no. 2, pp. 67-93, May 2003.
5. 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.
6. J.-M. Yang, P.-T. Yu, and B.-C. Kuo, "A nonparametric feature extraction and its application to nearest neighbor classification for hyperspectral image data," IEEE Trans. Geosci. Remote Sens., vol. 48, no. 3, pp. 1279-1293, Mar. 2010.
7. R. L. Kettig and D. A. Landgrebe, "Classification of multispectral image data by extraction and classification of homogeneous objects," IEEE Trans. Geosci. Electron., vol. GE-14, no. 1, pp. 19-26, Jan. 1976.
8. A. Farag, R. Mohamed, and A. El-Baz, "A unified framework for MAP estimation in remote sensing image segmentation," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 7, pp. 1617-1634, Jul. 2005.
9. M. Fauvel, "Spectral and spatial methods for the classification of urban remote sensing data," Ph.D. dissertation, Grenoble Inst. Technol., Grenoble, France, 2007.
10. M. Fauvel, J. Chanussot, J. A. Benediktsson, and J. R. Sveinsson, "Spectral and spatial classification of hyperspectral data using SVMs and morphological profiles," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 10, pp. 3804-3814, Oct. 2008.
11. R. Gaetano, G. Moser, G. Poggi, G. Scarpa, and S. B. Serpico, "Region-based classification of multisensor optical-SAR images," in Proc. IGARSS, Boston, MA, 2008, pp. IV-81-IV-84.
12. Y. Tarabalka, J. A. Benediktsson, and J. Chanussot, "Classification of hyperspectral data using support vector machines and adaptive neighborhoods," in Proc. 6th EARSeL SIG IS Workshop, Tel Aviv, Israel, 2009.
13. R. Gonzalez and R. Woods, Digital Image Processing, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 2002.
14. Y. Tarabalka, J. A. Benediktsson, and J. Chanussot, "Spectral- spatial classification of hyperspectral imagery based on partitional clustering techniques," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 8, pp. 2973-2987, Aug. 2009.
15. Y. Tarabalka, J. Chanussot, J. A. Benediktsson, J. Angulo, and M. Fauvel, "Segmentation and classification of hyperspectral data using watershed," in Proc. IGARSS, Boston, MA, 2008, pp. III-652-III-655.
16. P. Soille, Morphological Image Analysis, 2nd ed. Berlin, Germany: Springer-Verlag, 2003.
17. Y. Tarabalka, J. Chanussot, and J. A. Benediktsson, "Segmentation and classification of hyperspectral images using minimum spanning forest grown from automatically selected markers," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 40, no. 5, pp. 1267-1279, Oct. 2010.
18. S. Tadjudin and D. A. Landgrebe, "Covariance estimation with limited training samples," IEEE Trans. Geosci. Remote Sens., vol. 37, no. 4, pp. 2113-2118, Jul. 1999.
19. L. Xu, A. Krzyzak, and C. Y. Suen, "Methods of combining multiple classifiers and their applications to handwriting recognition," IEEE Trans. Syst., Man, Cybern., vol. 22, no. 3, pp. 418-435, May/Jun. 1992.
20. J. Kittler, M. Hatef, R. P. W. Duin, and J. Matas, "On combining classifiers," IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 3, pp. 226-239, Mar. 1998.
21. G. Briem, J. A. Benediktsson, and J. R. Sveinsson, "Multiple classifiers applied to multisource remote sensing data," IEEE Trans. Geosci. Remote Sens., vol. 40, no. 10, pp. 2291-2299, Oct. 2002.
22. G. Fumera and F. Roli, "A theoretical and experimental analysis of linear combiners for multiple classifier systems," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 6, pp. 942-956, Jun. 2005.
23. Y.-C. Tzeng, "Remote sensing images classification/data fusion using distance weighted multiple classifiers systems," in Proc. PDCAT, Taipei, Taiwan, Dec. 2006.
24. S. Beucher and C. Lantuejoul, "Use of watersheds in contour detection," in Proc. Int. Workshop Image Process. Real-Time Edge Motion Detection/Estimation, Rennes, France, Sep. 1979.
25. G. Noyel, J. Angulo, and D. Jeulin, "Morphological segmentation of hyperspectral images," Image Anal. Stereol., vol. 26, pp. 101-109, 2007.
26. A. Evans and X. Liu, "A morphological gradient approach to color edge detection," IEEE Trans. Image Process., vol. 15, no. 6, pp. 1454-1463, Jun. 2006.
27. L. Vincent and P. Soille, "Watersheds in digital spaces: An efficient algorithm based on immersion simulations," IEEE Trans. Pattern Anal. Mach. Intell., vol. 13, no. 6, pp. 583-598, Jun. 1991.
28. J. Astola, P. Haavisto, and Y. Neuvo, "Vector median filters," Proc. IEEE, vol. 78, no. 4, pp. 678-689, Apr. 1990.
29. P. Masson and W. Pieczynski, "SEM algorithm and unsupervised segmentation of satellite images," IEEE Trans. Geosci. Remote Sens., vol. 31, no. 3, pp. 618-633, May 1993.
30. L. Shapiro and G. Stockman, Computer Vision. Englewood Cliffs, NJ: Prentice-Hall, 2002.
31. A. Jensen and A. Solberg, "Fast hyperspectral feature reduction using piecewise constant function approximations," IEEE Geosci. Remote Sens. Lett., vol. 4, no. 4, pp. 547-551, Oct. 2007.
32. J. C. Tilton, HSEG/RHSEG, HSEGViewer and HSEGReader User's Manual (Version 1.40), 2008, Provided With the Evaluation Version of RHSEG. [Online]. Available: http://techtransfer.gsfc.nasa.gov/ft-tech-rhseg.shtm
33. J. Tilton, "Analysis of hierarchically related image segmentations," in Proc. IEEE Workshop Adv. Tech. Anal. Remotely Sensed Data, 2003, pp. 60-69.
34. Y. Tarabalka, J. Chanussot, and J. A. Benediktsson, "Spectral- spatial classification of hyperspectral images using segmentation-derived adaptive neighborhoods," in Multivariate Image Processing. New York: Wiley, 2009, pp. 341-374.
35. A. J. Plaza and J. C. Tilton, "Automated selection of results in hierarchical segmentations of remotely sensed hyperspectral images," in Proc. IGARSS, Jul. 2005, vol. 7, pp. 4946-4949.
36. G. Licciardi, F. Pacifici, D. Tuia, S. Prasad, T. West, F. Giacco, J. Inglada, E. Christophe, J. Chanussot, and P. Gamba, "Decision fusion for the classification of hyperspectral data: Outcome of the 2008 GRS-S data fusion contest," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 11, pp. 3857-3865, Nov. 2009.
37. V. Vapnik, Statistical Learning Theory. New York: Wiley, 1998.
38. J. Stawiaski, "Mathematical morphology and graphs: Application to interactive medical image segmentation," Ph.D. dissertation, Paris School Mines, Paris, France, 2008.
39. R. C. Prim, "Shortest connection networks and some generalizations," Bell Syst. Technol. J., vol. 36, no. 6, pp. 1389-1401, Nov. 1957.
40. T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, 2nd ed. Cambridge, MA: MIT Press, 2001.
41. J. A. Richards and X. Jia, Remote Sensing Digital Image Analysis: An Introduction. New York: Springer-Verlag, 1999.
42. 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, 2004.
43. N. Cristianini and J. Shawe-Taylor, Support Vector Machines and Other Kernel-Based Learning Methods. Cambridge, U.K.: Cambridge Univ. Press, 2000.
44. N. Keshava, "A survey of spectral unmixing algorithms," Lincoln Lab. J., vol. 14, no. 1, pp. 55-78, Jan. 2003.
45. C. Rouquet and P. Bonton, "Region-based segmentation of textured images," in Proc. ICIAP, London, U.K., 1995, pp. 11-16.