Combining multiple classification methods for hyperspectral data interpretation

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 6, Issue 3, 2013, Pages 1450-1459

  Santos, Andrey Bicalho ^a   Araujo, Arnaldo De Albuquerque ^a   Menotti, David ^b  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b FEDERAL UNIVERSITY OF OURO PRETO   (Brazil)

Author keywords

Conscious combiners; ensemble of classifiers; genetic algorithm; hyperspectral image; multiple classification systems

Indexed keywords

CONSCIOUS COMBINERS; ENSEMBLE OF CLASSIFIERS; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL IMAGE ANALYSIS; LAND COVER CLASSIFICATION; MULTILAYER PERCEPTRON NEURAL NETWORKS; MULTIPLE CLASSIFICATION SYSTEMS; WEIGHTED LINEAR COMBINATIONS;

DATA PROCESSING; EXPERIMENTS; GENETIC ALGORITHMS; MAPS; SUPPORT VECTOR MACHINES;

SPECTROSCOPY;

ACCURACY ASSESSMENT; DATA INTERPRETATION; GENETIC ALGORITHM; IMAGE ANALYSIS; IMAGE CLASSIFICATION; LAND COVER; REMOTE SENSING; VEGETATION COVER;

EID: 84880277002     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2013.2251969     Document Type: Article

References (50)

1. C. I. Chang Hyperspectral Data Exploitation: Theory and Applications. New York, NY, USA: Wiley, 2007.
2. Y. Tarabalka, J. Benediktsson, J. Chanussot, and J. Tilton, "Multiple spectral-spatial classification approach for hyperspectral data, " IEEE Trans. Geosci. Remote Sens., vol. 48, no. 11, pp. 4122-4132, 2010.
3. A. Plaza, J. Benediktsson, J. Boardman, J. Brazile, L. Bruzzone, G. Camps-Valls, J. Chanussot, M. Fauvel, P. Gamba, A. Gualtieri, M. Marconcini, J. Tilton, and G. Trianni, "Recent advances in techniques for hyperspectral image processing, " Remote Sens. Environ., vol. 113, no. 1, pp. 110-122, 2009.
4. G. Hughes, "On the mean accuracy of statistical pattern recognizers, " IEEE Trans. Inf. Theory, vol. 14, no. 1, pp. 55-63, 1968.
5. B.-C. Kuo, C.-H. Li, and J.-M. Yang, "Kernel nonparametric weighted feature extraction for hyperspectral image classification, " IEEE Trans. Geosci. Remote Sens., vol. 47, no. 4, pp. 1139-1155, 2009.
6. Y. Bazi and F. Melgani, "Toward an optimal SVM classification system for hyperspectral remote sensing images, " IEEE Trans. Geosci. Remote Sens., vol. 44, no. 11, pp. 3374-3385, 2006. (Pubitemid 44711679)
7. L.ShenandS.Lia, "Three-dimensionalgaborwaveletsforpixel-based hyperspectral imagery classification, " IEEE Trans. Geosci. Remote Sens., vol. 49, no. 12, pp. 5039-5046, 2011.
8. P. R. Marpu, P. Gamba, and I. Niemeyer, "Hyperspectral data classification using an ensemble of class-dependent neural networks, " inProc. Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2009, pp 1-4.
9. K. Bakos and P. Gamba, "Hierarchical hybrid decision tree fusion of multiple hyperspectral data processing chains, " IEEE Trans. Geosci. Remote Sens., vol. 49, no. 1, pp. 388-394, 2011.
10. F. Melgani and L. Bruzzone, "Classification of hyperspectral remote sensing images with support vector machines, " IEEE Trans. Geosci. Remote Sens., vol. 42, no. 8, pp. 1778-1790, 2004.
11. 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, 2005. (Pubitemid 40811944)
12. G. Camps-Valls, L. Gomez-Chova, J. Munoz-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, 2006. (Pubitemid 43131904)
13. Y. Tarabalka, M. Fauvel, J. Chanussot, and J. Benediktsson, "SVM-and MRF-based method for accurate classification of hyperspectral images, " IEEE Geosci. Remote Sens. Lett, vol. 7, no. 4, pp 736-740, 2010.
14. Y. Tarabalka, J. Chanussot, and J. Benediktsson, "Segmentation and classification of hyperspectral images using minimum spanning forest grown from automatically selected markers, " IEEE Trans. Syst, Man Cybern, vol. 40, no. 5, pt. B, pp. 1267-1279, 2010.
15. M. Fauvel, Y. Tarabalka, J. A. Benediktsson, J. Chanussot, and J. C Tilton, "Advances in spectral-spatial classification of hyperspectral im-ages, "Proc. IEEE, vol. 101, no. 3, pp. 652-675, 2013.
16. J. Benediktsson, J. Palmason, and J. Sveinsson, "Classification of hyperspectral data from urban areas based on extended morphological profiles, " IEEE Trans. Geosci. Remote Sens., vol. 43, no. 3, pp. 480-491, 2005. (Pubitemid 40320270)
17. J. A. Palmason, J. A. Benediktsson, J. R. Sveinsson, and J. Chanussot, "Classification of hyperspectral data from urban areas using morphological preprocessing and independent component analysis, " in Proc. IGARSS, 2005, vol. 1, 4.
18. M. Fauvel, J. Chanussot, J. Benediktsson, and J. Sveinsson, "Spectral and spatial classification of hyperspectral data using svms and morphological profiles, " IEEETrans. Geosc. Remote Sens., vol. 46, no. 11, pp. 3804-3814, 2008.
19. J. Benediktsson and P. Swain, "Consensus theoretic classification methods, "IEEE Trans. Syst. Man Cybern., vol. 22, no. 4, pp. 688-704, Jul./Aug. 1992.
20. J. Benediktsson and I. Kanellopoulos, "Classification of multisource and hyperspectral data based on decision fusion, " IEEE Trans. Geosc. Remote. Sens., vol. 37, no. 3, pp. 1367-1377, May 1999.
21. G. Briem, J. Benediktsson, and J. Sveinsson, "Multiple classifiers applied to multisource remote sensing data, " IEEE Trans. Geosci. Remote. Sens., vol. 40, no. 10, pp. 2291-2299, Oct. 2002.
22. M. Dalponte, L. Bruzzone, and D. Gianelle, "Fusion of hyperspec-tral and lidar remote sensing data for classification of complex forest areas, " IEEE Trans. Geosci. Remote. Sens., vol. 46, no. 5, pp. 1416-1427, May 2008.
23. G. Thoonen, Z. Mahmood, S. Peeters, and P. Scheunders, "Multisource classification of color and hyperspectral images using color attribute profiles and composite decision fusion, " IEEE Sel. Topics Appl. Earth Observ. Remote Sens., vol. 5, no. 2, pp. 510-521, Apr. 2012.
24. J. Benediktsson, J. Sveinsson, and P. Swain, "Hybrid consensus theoretic classification, " IEEE Trans. Geosci. Remote. Sens., vol. 35, no. 4, pp. 833-843, Jul. 1997. (Pubitemid 127771123)
25. G. Licciardi, F. Pacifici, D. Tuia, S. Prasad, T. West, F. Giacco, C. Thiel, J. Inglada, E. Chritophe, 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, 2009.
26. L. Kuncheva, Combining Pattern Classifiers: Methods and Algorithms. Hoboken, NJ, USA: Wiley-Interscience, 2004.
27. 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, 1998. (Pubitemid 128741312)
28. T. Weise, Global Optimization Algorithms-Theory and Application. Online: e-book freely, 2008 [Online]. Available: www.it-weise.de
29. D. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. San Diego, CA, USA: Addison-Wesley, 1989.
30. B. Gabrys and D. Ruta, "Genetic algorithms in classifier fusion, " Appl. Soft Computing, vol. 6, no. 4, pp. 337-347, 2006. (Pubitemid 44160505)
31. A. Frank and A. Asuncion, UCI Machine Learning Repository 2010 [Online]. Available: http://archive.ics.uci.edu/ml
32. M. Awad, K. Chehdi, and A. Nasri, "Multicomponent image segmentation using a genetic algorithm and artificial neural network, " IEEE Geosci. Remote Sens. Lett., vol. 4, no. 4, pp. 571-575, 2007. (Pubitemid 47588032)
33. R. Green, M. Eastwood, C. Sarture, T. Chrien, M. Aronsson, B. Chippendale, J. Faust, B. Pavri, C. Chovit, and M. Solis et al., "Imaging spectroscopy and the airborne visible/infrared imaging spectrometer (AVIRIS), " Remote Sens. Environ., vol. 65, no. 3, pp. 227-248, 1998. (Pubitemid 29360700)
34. P. Gege, D. Beran, W. Mooshuber, J. Schulz, and H. Van Der Piepen, "System analysis and performance of the new version of the imaging spectrometer rosis, " in Proc. 1st EARSeL Workshop Imaging Spec-troscopy, 1998, pp. 29-35.
35. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification and Scene Analysis, 2nd ed. New York, NY, USA: Wiley, 1995.
36. A. B. Santos, C. S. F. de S. Celes, A. de A. Araújo, and D. Menotti, "Feature selection for classification of remote sensed hyperspectral images: A filter approach using genetic algorithm and cluster validity, " in Proc. IPCV, 2012, vol. 2, pp. 675-681.
37. J. Dunn, "Well separated clusters and optimal fuzzy partitions, " J. Cy-bern., vol. 4, pp. 95-104, 1974.
38. M. Halkidi, Y. Batistakis, and M. Vazirgiannis, "On clustering validation techniques, " J. Intell. Inf. Syst., vol. 17, no. 40, pp. 107-145, 2001. (Pubitemid 34050790)
39. J. Serra, Image Analysis and Mathematical Morphology.: Academic Press, 1982.
40. C. M. Bishop, Pattern Recognition and Machine Learning. New York, NY, USA: Springer, 2006.
41. J. B. L. I. Kuncheva and R. Duin, "Decision templates for multiple classifier fusion: An experimental comparison, " Pattern Recognit., vol. 34, no. 2, pp. 299-314, 2001. (Pubitemid 32871876)
42. A. Ghosh, B. Shankar, L. Bruzzone, and S. Meher, "Neuro-fuzzy-com- biner: An effective multiple classifier system, " Int. J. Knowledge Eng. Soft Data Paradigms, vol. 2, no. 2, pp. 107-129, 2010.
43. D. Wolpert, "Stacked generalization, " Neural Netw., vol. 5, no. 2, pp. 241-259, 1992.
44. A. B. Santos, A. de A. Araújo, and D. Menotti, "Combiner of classifiers using genetic algorithm for classification of remote sensed hyperspec-tral images, " in Proc. IEEE IGARSS, 2012, pp. 4146-4149.
45. M. Fauvel, "Spectral and Spatial Methods for the Classification of Urban Remote Sensing Datas, " Ph.D. dissertation, University of Iceland and Grenoble Institute of Technology, Grenoble, France, 2007.
46. Y. Tarabalka, "Classification of Hyperspectral Data Using Spectral-Spatial Approaches, " Ph.D. dissertation, University of Iceland and Grenoble Institute of Technology, Grenoble, France, 2010.
47. C. D. Manning, P. Raghavan, and H. Schütze, Introduction to Information Retrieval. Cambridge, U.K.: Cambridge University Press, 2008 [Online]. Available: http://nlp.stanford.edu/IR-book/
48. S. Theodoridis and K. Koutroumbas, Pattern Recognition. New York, NY, USA: Academic, 2003.
49. C-C. Chang and C.-J. Lin, "LIBSVM: A library for support vector machines, " ACM Trans. Intell. Syst. Technol, vol. 2, no. 3, pp. 1-27, 2011 [Online]. Available: http://www.csie.ntu.edu.tw/cjlin/libsvm
50. R. Jain, Art of Computer Systems Performance Analysis Techniques For Experimental Design Measurements Simulation and Modeling. New York, NY, USA: Wiley, 1991.