Tensor discriminative locality alignment for hyperspectral image spectral-spatial feature extraction

IEEE Transactions on Geoscience and Remote Sensing

Volumn 51, Issue 1, 2013, Pages 242-256

  Zhang, Liangpei ^a   Zhang, Lefei ^a   Tao, Dacheng ^b   Huang, Xin ^a  

^a WUHAN UNIVERSITY   (China)

^b UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

Classification; feature extraction; hyperspectral image (HSI); remote sensing; tensor

Indexed keywords

AIRBORNE VISIBLE/INFRARED IMAGING SPECTROMETERS; CLASSIFICATION ACCURACY; CLASSIFICATION RESULTS; DATA SETS; DIGITAL IMAGERY; DIMENSIONALITY REDUCTION; HYPERSPECTRAL; HYPERSPECTRAL IMAGES; IMAGING SPECTROMETERS; MULTILINEAR ALGEBRA; OPTIMAL SOLUTIONS; REDUNDANT INFORMATIONS; REFLECTIVE OPTICS;

ALGEBRA; CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; INDEPENDENT COMPONENT ANALYSIS; REMOTE SENSING; SPECTROMETERS; SPECTROMETRY; SPECTROSCOPY;

TENSORS;

DATA SET; DIGITAL IMAGE; IMAGE CLASSIFICATION; LEARNING; OPTIMIZATION; PIXEL; SPECTRAL ANALYSIS;

EID: 84871736244     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2012.2197860     Document Type: Article

References (63)

1. D. Landgrebe, "Hyperspectral image data analysis," IEEE Signal Process Mag., vol. 19, no. 1, pp. 17-28, Jan. 2002. (Pubitemid 34237205)
2. A. F. H. Goetz, G. Vane, J. E. Solomon, and B. N. Rock, "Imaging spectrometry for earth remote sensing," Science, vol. 228, no. 4704, pp. 1147-1153, Jun. 1985.
3. A. Plaza, J. A. Benediktsson, J. W. Boardman, J. Brazile, L. Bruzzone, G. Camps-Valls, J. Chanussot, M. Fauvel, P. Gamba, A. Gualtieri, M. Marconcini, J. C. Tilton, and G. Trianni, "Recent advances in techniques for hyperspectral image processing," Remote Sens. Environ., vol. 113, no. 1, pp. 110-122, Sep. 2009.
4. L. O. Jimenez and D. A. Landgrebe, "Supervised classification in highdimensional space: Geometrical, statistical, and asymptotical properties of multivariate data," IEEE Trans. Syst. Man Cybern. Part C Appl. Rev., vol. 28, no. 1, pp. 39-54, Feb. 1998. (Pubitemid 128748606)
5. J. A. Richards and X. Jia, Remote Sensing Digital Image Analysis: An Introduction. Berlin, Germany: Springer-Verlag, 2006.
6. C.-I. Chang and H. Safavi, "Progressive dimensionality reduction by transform for hyperspectral imagery," Pattern Recognit., vol. 44, no. 10, pp. 2760-2773, Oct. 2011.
7. H. Shen and L. Zhang, "A MAP-based algorithm for destriping and inpainting of remotely sensed images," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 5, pp. 1492-1502, May 2009.
8. A. R. Webb, Statistical Pattern Recognition. West Sussex, U. K. : Wiley, 2002.
9. A. Jain and D. Zongker, "Feature selection: Evaluation, application, and small sample performance," IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 2, pp. 153-158, Feb. 1997. (Pubitemid 127828334)
10. C.-I. Chang and S. Wang, "Constrained band selection for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 6, pp. 1575-1585, Jun. 2006. (Pubitemid 43824504)
11. P. M. Narendra and K. Fukunaga, "A branch and bound algorithm for feature subset selection," IEEE Trans. Comput., vol. C-26, no. 9, pp. 917-922, Sep. 1977. (Pubitemid 8550870)
12. M. L. Raymer, W. F. Punch, E. D. Goodman, L. A. Kuhn, and A. K. Jain, "Dimensionality reduction using genetic algorithms," IEEE Trans. Evol. Comput., vol. 4, no. 2, pp. 164-171, Jul. 2000.
13. L. Zhang, Y. Zhong, B. Huang, J. Gong, and P. Li, "Dimensionality reduction based on clonal selection for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 12, pp. 4172-4186, Dec. 2007. (Pubitemid 350157849)
14. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. San Diego, CA: Academic, 1990.
15. D. Tao, X. Li, X. Wu, and S. J. Maybank, "Geometric mean for subspace selection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 2, pp. 260-274, Feb. 2009.
16. W. Bian and D. Tao, "Max-min distance analysis by using sequential SDP relaxation for dimension reduction," IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 5, pp. 1037-1050, May 2011.
17. C. Lee and D. A. Landgrebe, "Feature extraction based on decision boundaries," IEEE Trans. Pattern Anal. Mach. Intell., vol. 15, no. 4, pp. 388-400, Apr. 1993.
18. I. T. Jolliffe, Principal Component Analysis. New York: Springer-Verlag, 2002.
19. A. A. Green, M. Berman, P. Switzer, and M. D. Craig, "A transformation for ordering multispectral data in terms of image quality with implications for noise removal," IEEE Trans. Geosci. Remote Sens., vol. 26, no. 1, pp. 65-74, Jan. 1988. (Pubitemid 18596008)
20. X. Jiang, "Linear subspace learning-based dimensionality reduction," IEEE Signal Process Mag., vol. 28, no. 2, pp. 16-26, Mar. 2011.
21. M. H. C. Law and A. K. Jain, "Incremental nonlinear dimensionality reduction by manifold learning," IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, no. 3, pp. 377-391, Mar. 2006. (Pubitemid 43159634)
22. D. Song and D. Tao, "Biologically inspired feature manifold for scene classification," IEEE Trans. Image Process., vol. 19, no. 1, pp. 174-184, Jan. 2010.
23. C. M. Bachmann, T. L. Ainsworth, and R. A. Fusina, " Exploitingmanifold geometry in hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 3, pp. 441-454, Mar. 2005.
24. J. He, L. Zhang, Q. Wang, and Z. Li, "Using diffusion geometric coordinates for hyperspectral imagery representation," IEEE Geosci. Remote Sens. Lett., vol. 6, no. 4, pp. 767-771, Oct. 2009.
25. T. Han and D. G. Goodenough, "Investigation of nonlinearity in hyperspectral imagery using surrogate data methods," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 10, pp. 2840-2847, Oct. 2008.
26. L. Zhang, L. Zhang, D. Tao, and X. Huang, "On combining multiple features for hyperspectral remote sensing image classification," IEEE Trans. Geosci. Remote Sens., vol. 50, no. 3, pp. 879-893, Mar. 2012.
27. M. M. Crawford, L. Ma, and W. Kim, "Exploring nonlinear manifold learning for classification of hyperspectral data," in Opt. Remote Sens., vol. 3, S. Prasad, L. M. Bruce, and J. Chanussot, Eds. Berlin, Germany: Springer-Verlag, 2011, pp. 207-234.
28. B. Du and L. Zhang, "Random-selection-based anomaly detector for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 5, pp. 1578-1589, May 2011.
29. C.-I. Chang and Q. Du, "Estimation of number of spectrally distinct signal sources in hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 42, no. 3, pp. 608-619, Mar. 2004.
30. A. Plaza, P. Martínez, J. Plaza, and R. Pérez, "Dimensionality reduction and classification of hyperspectral image data using sequences of extended morphological transformations," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 3, pp. 466-479, Mar. 2005. (Pubitemid 40320269)
31. F. Li, M. K. Ng, and R. J. Plemmons, "Coupled segmentation and denoising/deblurring models for hyperspectral material identification," Numer. Linear Algebra Appl., vol. 19, no. 1, pp. 153-173, Jan. 2012.
32. H. Li and L. Zhang, "A hybrid automatic endmember extraction algorithm based on a local window," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 11, pp. 4223-4238, Nov. 2011.
33. 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. 43, no. 3, pp. 480-491, Mar. 2005. (Pubitemid 40320270)
34. L. Zhang, X. Huang, B. Huang, and P. Li, "A pixel shape index coupled with spectral information for classification of high spatial resolution remotely sensed imagery," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 10, pp. 2950-2961, Oct. 2006.
35. 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.
36. Q. Zhang, R. Plemmons, D. Kittle, D. Brady, and S. Prasad, "Joint segmentation and reconstruction of hyperspectral data with compressed measurements," Appl. Opt., vol. 50, no. 22, pp. 4417-4435, Aug. 2011.
37. Q. Yuan, L. Zhang, and H. Shen, "Multi-frame super-resolution employing a spatially weighted total variation model," IEEE Trans. Circuits Syst. Video Technol., vol. 22, no. 3, pp. 379-392, Mar. 2012.
38. D. Tao, X. Li, X. Wu, W. Hu, and S. J. Maybank, "Supervised tensor learning," Knowl. Inf. Syst., vol. 13, no. 1, pp. 1-42, Sep. 2007.
39. S. Bourennane, C. Fossati, and A. Cailly, "Improvement of targetdetection algorithms based on adaptive three-dimensional filtering," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 4, pp. 1383-1395, Apr. 2011.
40. D. Letexier and S. Bourennane, "Estimation of N-mode ranks of hyperspectral images for tensor denoising," in Proc. Eur. Signal Process. Conf., Glasgow, Scotland, 2009, pp. 2594-2597.
41. Q. Zhang, H. Wang, R. J. Plemmonsz, and V. P. Pauca, "Tensor methods for hyperspectral data processing: A space object identification study," J. Opt. Soc. Amer. A, vol. 25, no. 12, pp. 3001-3012, Dec. 2008.
42. N. Renard and S. Bourennane, "Improvement of target detection methods by multiway filtering," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 8, pp. 2407-2417, Aug. 2008.
43. L. Zhang, L. Zhang, D. Tao, and X. Huang, "A multifeature tensor for remote-sensing target recognition," IEEE Geosci. Remote Sens. Lett., vol. 8, no. 2, pp. 374-378, Mar. 2011.
44. H. Lu, K. N. Plataniotis, and A. N. Venetsanopoulos, "A survey of multilinear subspace learning for tensor data," Pattern Recognit., vol. 44, no. 7, pp. 1540-1551, Jul. 2011.
45. L. D. Lathauwer, "Signal processing based on multilinear algebra," Ph. D. dissertation, Katholike Univ. Leuven, Leuven, Belgium, 1997.
46. S. Yan, D. Xu, Q. Yang, L. Zhang, X. Tang, and H.-J. Zhang, "Multilinear discriminant analysis for face recognition," IEEE Trans. Image Process., vol. 16, no. 1, pp. 212-220, Jan. 2007. (Pubitemid 46437483)
47. D. Xu, S. Yan, L. Zhang, S. Lin, H.-J. Zhang, and T. S. Huang, "Reconstruction and recognition of tensor-based objects with concurrent subspaces analysis," IEEE Trans. Circuits Syst. Video Technol., vol. 18, no. 1, pp. 36-47, Jan. 2008.
48. N. Renard and S. Bourennane, "Dimensionality reduction based on tensor modeling for classification methods," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 4, pp. 1123-1131, Apr. 2009.
49. D. Muti and S. Bourennane, "Multidimensional filtering based on a tensor approach," Signal Process., vol. 85, no. 12, pp. 2338-2353, Dec. 2005. (Pubitemid 41606027)
50. M. A. O. Vasilescu and D. Terzopoulos, "Multilinear analysis of image ensembles: TensorFaces," in Proc. Eur. Conf. Comput. Vis., Copenhagen, Denmark, 2002, pp. 447-460.
51. X. Li, S. Lin, S. Yan, and D. Xu, "Discriminant locally linear embedding with high-order tensor data," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 38, no. 2, pp. 342-352, Feb. 2008. (Pubitemid 351479557)
52. S. Yan, D. Xu, B. Zhang, H.-J. Zhang, Q. Yang, and S. Lin, "Graph embedding and extensions: A general framework for dimensionality reduction," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 1, pp. 40-51, Jan. 2007. (Pubitemid 46415944)
53. Y. Liu, Y. Liu, and K. C. C. Chan, "Tensor distance based multilinear locality-preserved maximum information embedding," IEEE Trans. Neural Netw., vol. 21, no. 11, pp. 1848-1854, Nov. 2010.
54. Y. Mu, D. Tao, X. Li, and F. Murtagh, "Biologically inspired tensor features," Cogn. Comput., vol. 1, no. 4, pp. 327-341, Dec. 2009.
55. T. Zhang, D. Tao, X. Li, and J. Yang, "Patch alignment for dimensionality reduction," IEEE Trans. Knowl. Data Eng., vol. 21, no. 9, pp. 1299-1313, Sep. 2009.
56. D. Tao, X. Li, X. Wu, and S. J. Maybank, "General tensor discriminant analysis and Gabor features for gait recognition," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 10, pp. 1700-1715, Oct. 2007.
57. R. Bhatia, Matrix Analysis. New York: Springer-Verlag, 1997.
58. D. Landgrebe, Signal Theory Methods in Multispectral Remote Sensing. New Jersey: Wiley, 2003.
59. G. Licciardi, F. Pacifici, D. Tuia, S. Prasad, T. West, F. Giacco, C. Thiel, 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.
60. X. He and P. Niyogi, "Locality preserving projections," in Proc. Adv. Neural Inf. Process. Syst., 2004, pp. 153-160.
61. M. D. Mura, J. A. Benediktsson, B. Waske, and L. Bruzzone, "Morphological attribute profiles for the analysis of very high resolution images," IEEE Trans. Geosci. Remote Sens., vol. 48, no. 10, pp. 3747-3762, Oct. 2010.
62. X. Huang and L. Zhang, "An adaptive mean-shift analysis approach for object extraction and classification from urban hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 46, no. 12, pp. 4173-4185, Dec. 2008.
63. S. R. Cloude and E. Pottier, "An entropy based classification scheme for land applications of polarimetric SAR," IEEE Trans. Geosci. Remote Sens., vol. 35, no. 1, pp. 68-78, Jan. 1997. (Pubitemid 127771044)