Hyperspectral image representation and processing with binary partition trees

IEEE Transactions on Image Processing

Volumn 22, Issue 4, 2013, Pages 1430-1443

  Valero, Silvia ^c   Salembier, Philippe ^b   Chanussot, Jocelyn ^a  

^a GIPSA LAB   (France)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

^c CNES   (France)

Author keywords

Binary partition tree; classification; hyperspectral imaging; segmentation

Indexed keywords

BINARY PARTITION TREE; BINARY PARTITION TREES (BPT); HYPER-SPECTRAL IMAGES; HYPERSPECTRAL; HYPERSPECTRAL DATA; HYPERSPECTRAL IMAGING; INCLUSION RELATION; OPTIMAL EXPLOITATION; PRUNING STRATEGY; REGION MODELS; REGION-BASED; REGION-MERGING; SIMILARITY METRICS; TREE STRUCTURES;

CLASSIFICATION (OF INFORMATION); FORESTRY; IMAGE SEGMENTATION; INDEPENDENT COMPONENT ANALYSIS; SPECTROSCOPY; TREES (MATHEMATICS);

OBJECT RECOGNITION;

CLASSIFICATION; FORESTRY; IMAGE ANALYSIS; PATTERN RECOGNITION;

EID: 84873650892     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2012.2231687     Document Type: Article

References (50)

1. A. Plaza, J. A. Benediktsson, J. Boardman, J. Brazile, L. Bruzzone, G. Camps-Valls, J. Chanussot, M. Fauvel, P. Gamba, A. Gualtieri, J. Tilton, and G. Trianni, "Recent advances in techniques for hyperspectral image processing," Remote Sens. Environ., vol. 113, no. 1, pp. S110-S122, 2009.
2. C.-I. Chang Hyperspectral Imaging: Techniques for Spectral Detection and Classification. Dordrecht, Norwell, MA: Kluwer Acad. Publ., 2003.
3. D. A. Landgrebe, Signal Theory Methods Multispectral Remote Sens. New York: Wiley, 2003.
4. 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. (Pubitemid 40811944)
5. L. Bruzzone, M. Chi, and M. Marconcini "A novel transductive SVM for semisupervised classification remote sensing images," IEEE Trans. Geosci. Remote Sen., vol. 44, no. 11, pp. 3363-3373, Nov. 2006.
6. M. Chi and L. Bruzzone "Semisupervised classification of hyperspectral images by SVMs optimized in the primal," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 6, pp. 1870-1880, Jun. 2007. (Pubitemid 46853295)
7. M. Fauvel, J. A. Benediktsson, J. Chanussot, and J. R. Sveinsson "Spectral and spatial classification of hyperspectral data using svms and morphological profiles," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 11, pp. 3804-3814, Nov. 2008.
8. 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.
9. Y. Tarabalka, J. A. Benediktsson, J. Chanussot, and J. C. Tilton, "Multiple spectral-spatial classification approach for hyperspectral data," IEEE Trans. Geosci. Remote Sens., vol. 48, no. 11, pp. 4122-4132, Nov. 2010.
10. Y. Tarabalka, J. C. Tilton, J. A. Benediktsson, and J. Chanussot, "A marker-based approach for the automated selection of a single segmentation from a hierarchical set of image segmentations," IEEE J. Sel. Topics Appl. Earth Observat. Remote Sens., vol. 5, no. 1, pp. 262-272, Jan. 2012.
11. J. Angulo and S. Velasco-Forero, "Semi-supervised hyperspectral image segmentation using regionalized stochastic watershed," Proc. SPIE, vol. 7695, pp. 1-12, May 2010.
12. A. Farag, R. Mohamed, and A. El-Baz "Unified framework for map estimation in remote sensing image segmentation," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 7, pp. 1617-1634, Jul. 2005. (Pubitemid 41164672)
13. J. Li, J. Bioucas-Dias, and A. Plaza, "Semi-supervised hyperspectral image segmentation using multinomial logistic regression with active learning," IEEE Trans. Geosci. Remote Sens., vol. 48, no. 11, pp. 4085-4098, Nov. 2010.
14. G. Martin and Plaza, A, "Spatial-spectral preprocessing prior to endmember identification and unmixing of remotely sensed hyperspectral data," IEEE J. Sel. Top. Appl. Earth Observat. Remote Sens., vol. 5, no. 2, pp. 380-395, Apr. 2012.
15. G. Camps-Valls, L. Gomez-Chova, J. Munoz-Mari, J. Vila-France, 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. M. Fauvel, J. Chanussot, and J. A. Benediktsson "Adaptive pixel neighborhood de+nition for the classi+cation of hyperspectral images with support vector machines and composite kernel," in Proc. IEEE ICIP Conf., Oct. 2008, pp. 1-5.
17. R. L. Kettig and D. A. Landgrebe, "Classification of multispectral image data by extraction and classification of homogeneous objects," IEEE Trans. Geosci. Electron., vol. 14, no. 1, pp. 19-26, Jan. 1976.
18. A. Darwish, K. Leukert, and W. Reinhardt "Image segmentation for the purpose of object-based classification," in Proc. IGARSS Conf., vol. 3. 2003, pp. 2039-2041.
19. N. Gorretta, J. M. Roger, G. Rabatel, V. Bellon-Maurel, C. Fiorio, and C. Lelong, "Hypersectral image segmentation: The butterfly approach," in Proc. IEEE Workshop Hyperspectral Image Signal Process., Aug. 2009, pp. 1-4.
20. J. A. Gualtieri and J. Tilton, "Hierarchical segmentation of hyperspectral data," in Proc. AVIRIS Earth Sci. Appl. Workshop, 2002, pp. 5-8.
21. P. Salembier and F. Marques, "Region-based representations of image and video: Segmentation tools for multimedia services," IEEE Trans. Circuits Syst. Video Technol., vol. 9, no. 8, pp. 1147-1169, Dec. 1999. (Pubitemid 32211339)
22. P. Salembier and L. Garrido, "Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval," IEEE Trans. Image Process., vol. 9, no. 4, pp. 561-576, Apr. 2000. (Pubitemid 30594737)
23. F. Van der Meer, "The effectiveness of spectral similarity measures for the analysis of hyperspectral imagery," Int. J. Appl. Earth Observat. Geoinformat., vol. 8, no. 1, pp. 3-17, 2006.
24. S. Valero, P. Salembier, and J. Chanussot, "New hyperspectral data representation using binary partition tree," in Proc. IEEE IGARSS Conf., Jul. 2010, pp. 80-83.
25. S. Valero and P. Salembier, and J. Chanussot, "Comparison of merging orders and pruning strategies for binary partition tree in hyperspectral data," in Proc. IEEE ICIP Conf., Sep. 2010, pp. 2565-2568.
26. S. Valero, P. Salembier, and J. Chanussot, "Hyperspectral image segmentation using binary partition trees," in Proc. IEEE 11th ICIP, Jun. 2011, pp. 1273-1276.
27. S. Valero, P. Salembier, J. Chanussot, and C. M. Cuadras, "Improved binary partition tree construction for hyperspectral images: Application to object detection," in Proc. IEEE 11th IGARSS, Mar. 2011, pp. 2515-2518.
28. V. N. Vapnik, Statistical Learn. Theory. New York: Wiley, 1998.
29. S. Lee and M. Crawford, "Unsupervised multistage image classification using hierarchical clustering with a Bayesian similarity measure," IEEE Trans. Image Process., vol. 14, no. 3, pp. 312-320, Mar. 2005. (Pubitemid 40351909)
30. L. Gomez-Chova, J. Calpe, G. Camps-Valls, J. D Martin, E. Soria, J. Vila, L. Alonso-Chorda, and J. Moreno "Semi-supervised classification method for hyperspectral remote sensing images," in Proc. IGARSS Conf., Sep. 2003, pp. 1776-1778.
31. F. Calderero and F. Marqués "Region-merging techniques using information theory statistical measures," IEEE Trans. Image Process., vol. 19, no. 6, pp. 1567-1586, Jun. 2010.
32. C.-I. Chang "Spectral information divergence for hyperspectral image analysis," in Proc. IEEE IGARSS, Oct. 1999, pp. 509-511.
33. M. Dimiccoli and P. Salembier "Hierarchical region-based representation for segmentation and filtering with depth in single images," in Proc. ICIP Conf., Nov. 2009, pp. 3533-3536.
34. P. Coupe, P. Yger, S. Prima, P. Hellier, C. Kervrann, and C. Barillot "An optimized blockwise nonlocal means denoising filter for 3-D magnetic resonance images," IEEE Trans. Med. Imag., vol. 27, no. 4, pp. 425-441, Apr. 2008. (Pubitemid 351479137)
35. C. M. Cuadras, A. Arenas, and J. Fortiana "Some computational aspects of a distance-based model for prediction," Communi. Stat., Simul. Comput., vol. 25, no. 3, pp. 593-609, 1996. (Pubitemid 126434226)
36. T. F. Cox and M. A. Cox, Multidimensional Scaling. Ed., K. Fernandez and A. Morineau, London, U.K.: Chapman Hal, 1994.
37. M. H. Kutner, C. J. Nachtsheim, and J. Neter, Application Linear Regression Model. New York: McGraw-Hill, 2004.
38. C. M. Cuadras, S. Valero, D. Cuadras, P. Salembier and J. Chanussot "Distance-based measures of association with applications in relating hyperspectral images," Commun. Stat., Theory Meth., vol. 41, nos. 13-14, pp. 2342-2355, 2012.
39. L. Breiman, J. Friedman, R. Olshen, and C. Stone "Classification and regression trees," in Proc. Wadsworth Int. Group Conf., 2004, pp. 1-8.
40. M. Fauvel, J. Chanussot, and J. A. Benediktsson, "A spatial-spectral kernel based approach for the classification of remote sensing images," Pattern Recognit., vol. 45, no. 1, pp. 281-392, 2011.
41. T. W. Anderson, An Introduction to Multivariate Analysis. New York: Wiley, 2003.
42. J. Benediktsson, L. Bruzzone, J. Chanussot, M. D. Mura, P. Salembier, and S. Valero "Hierarchical analysis of remote sensing data: Morphological attribute profiles and binary partition trees," in Proc. ISMM, Int. Symp. Math. Morphol., 2011, pp. 306-319.
43. C. M. Cuadras "Multidimensional and dependencies in classification and ordination," Eds. K. Fernandez and A. Morineau, 2009.
44. M. Dundar and D. Landgrebe "A model-based mixture-supervised classification approach in hyperspectral data analysis," IEEE Trans. Geosci. Remote Sens., vol. 40, no. 12, pp. 2692-2699, Dec. 2002.
45. Y. Escoufier "Le traitement des variables vectorielles," Int. Biometr. Soc., vol. 29, no. 4, pp. 751-76, 1973.
46. J. C. Gower, "Some distance properties of latent roots and vector methods used in multivariate analysis," Biometrika, vol. 53, nos. 3-4, pp. 325-338, 1966.
47. H. Ling and K. Okada, "Diffusion distance for histogram comparison," in Proc. Conf. Comput. Vis. Pattern Recognit., 2006, pp. 246-253. (Pubitemid 44931337)
48. G. Noyel, J. Angulo, and D. Jeulin, "Morphological segmentation of hyperspectral images," Image Anal. Stereol., vol. 26, no. 3, pp. 101-109, 2007.
49. K. M. Rajpoot and N. M. Rajpoot, "Wavelet based segmentation of hyperspectral colon tissue imagery," in Proc. IEEE 7th Int. Multitop. Conf. INMIC, 2003, pp. 142-149.
50. I. Silverman, S. R. Rotman, and C. E. Caefer, "Segmentation of hyperspectral images from the histograms of principal components," in Proc. Imag. Spectromet. Conf., 2002, pp. 24-29.