Dimensionality Reduction for Hyperspectral Data Based on Class-Aware Tensor Neighborhood Graph and Patch Alignment

IEEE Transactions on Neural Networks and Learning Systems

Volumn 26, Issue 8, 2015, Pages 1582-1593

  Gao, Yang ^a   Wang, Xuesong ^a   Cheng, Yuhu ^a,b   Wang, Z Jane ^b  

^a CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Class aware tensor neighborhood graph; dimensionality reduction (DR); hyperspectral data; patch alignment; tensor distance (TD)

Indexed keywords

ALIGNMENT; ITERATIVE METHODS; TENSORS;

BETTER PERFORMANCE; CURSE OF DIMENSIONALITY; DIMENSIONALITY REDUCTION; DISTANCE CRITERION; HYPERSPECTRAL DATA; HYPERSPECTRAL INFORMATION; NEIGHBORHOOD GRAPHS; SPATIAL INFORMATIONS;

DATA REDUCTION;

EID: 85027931296     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2014.2339222     Document Type: Article

References (35)

1. 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.
2. 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.
3. 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.
4. B. Demit, A. Celebi, and S. Erturk, "A low-complexity approach for the color display of hyperspectral remote-sensing images using onebit-transform-based band selection," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 1, pp. 97-105, Jan. 2009.
5. 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.
6. J. Chen, Z. Ma, and Y. Liu, "Local coordinates alignment with global preservation for dimensionality reduction," IEEE Trans. Neural Netw. Learn. Syst., vol. 24, no. 1, pp. 106-117, Jan. 2013.
7. S. Moon and H. R. Qi, "Hybrid dimensionality reduction method based on support vector machine and independent component analysis," IEEE Trans. Neural Netw. Learn. Syst., vol. 23, no. 5, pp. 749-761, May 2012.
8. 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.
9. 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.
10. L. Du Plessis, R. Xu, S. Damelin, M. Sears, and D. C. Wunsch, II, "Reducing dimensionality of hyperspectral data with diffusion maps and clustering with k-means and fuzzy ART," Int. J. Syst. Control Commun., vol. 3, no. 3, pp. 232-251, 2011.
11. K. A. Cawse, S. Damelin, L. du Plessis, R. Mclntyre, M. Mitchley, and M. Sears, "An investigation of data compression techniques for hyperspectral core imager data," in Proc. Math. Ind. Study Group (MISG), 2008, pp. 1-25.
12. R. Xu, S. Damelin, B. Nadler, and D. Wunsch, II, "Clustering of high-dimensional gene expression data with feature filtering methods and diffusion maps," Artif. Intell. Med., vol. 48, nos. 2-3, pp. 91-98, Feb./Mar. 2010.
13. Y. Weiwei, "Two-dimensional discriminant locality preserving projections for face recognition," Pattern Recognit., vol. 30, no. 15, pp. 1378-1383, Nov. 2009.
14. Z. H. Lai, M. H. Wan, Z. Jin, and J. Yang, "Sparse two-dimensional local discriminant projections for feature extraction," Neurocomputing, vol. 74, no. 4, pp. 629-637, Jan. 2011.
15. K. Cawse-Nicholson, S. B. Damelin, A. Robin, and M. Sears, "Determining the intrinsic dimension of a hyperspectral image using random matrix theory," IEEE Trans. Image Process., vol. 22, no. 4, pp. 1301-1310, Apr. 2013.
16. 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.
17. Q. Zhang, H. Wang, R. J. Plemmons, and V. P. Pauca, "Tensor methods for hyperspectral data analysis: A space object material identification study," J. Opt. Soc. Amer. A, vol. 25, no. 12, pp. 3001-3012, Dec. 2008.
18. 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.
19. L. D. Lathauwer, "Signal processing based on multilinear algebra," Ph.D. dissertation, Dept. Elektrotechniek, Katholike Univ. Leuven, Leuven, Belgium, 1997.
20. 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.
21. H. P. Lu, K. N. Plataniotis, and A. N. Ventsanopoulos, "MPCA: Multilinear principal component analysis of tensor objects," IEEE Trans. Neural Netw., vol. 19, no. 1, pp. 18-39, Jan. 2008.
22. J. Zhao, P. L. H. Yu, and J. T. Kwok, "Bilinear probabilistic principal component analysis," IEEE Trans. Neural Netw. Learn. Syst., vol. 23, no. 3, pp. 492-503, Mar. 2012.
23. S. C. 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.
24. P. N. Belhumeur, J. P. Hespanda, and D. Kiregeman, "Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 7, pp. 711-720, Jul. 1997.
25. S. Velasco-Forero and J. Angulo, "Classification of hyperspectral images by tensor modeling and additive morphological decomposition," Pattern Recognit., vol. 46, no. 2, pp. 566-577, Feb. 2013.
26. 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.
27. 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.
28. M. Kuroda, Y. Mori, M. Lizuka, and M. Sakakihara, "Acceleration of the alternating least squares algorithm for principal component analysis," Comput. Statist. Data Anal., vol. 55, no. 1, pp. 143-153, Jan. 2011.
29. 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.
30. J. Li, J. M. Bioucas-Dias, and A. Plaza, "Spectral-spatial classification of hyperspectral data using loopy belief propagation and active learning," IEEE Trans. Geosci. Remote Sens., vol. 51, no. 2, pp. 844-856, Feb. 2013.
31. L. Wang, Y. Zhang, and J. Feng, "On the Euclidean distance of images," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 8, pp. 1334-1339, Aug. 2005.
32. 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.
33. C.-H. Li, H.-S. Chu, B.-C. Kuo, and C.-T. Lin, "Hyperspectral image classification using spectral and spatial information based linear discriminant analysis," in Proc. IGARSS, Vancouver, BC, Canada, 2011, pp. 1716-1719.
34. B.-C. Kuo and D. A. Landgrebe, "Nonparametric weighted feature extraction for classification," IEEE Geosci. Remote Sens., vol. 42, no. 5, pp. 1096-1105, May 2004.
35. M. Belkin and P. Niyogi, "Laplacian Eigenmaps for dimensionality reduction and data representation," Neural Comput., vol. 15, no. 6, pp. 1373-1396, Jun. 2003.