GPU Parallel Implementation of Spatially Adaptive Hyperspectral Image Classification

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

Volumn 11, Issue 4, 2018, Pages 1131-1143

  Wu, Zebin ^a,b,c   Shi, Linlin ^a   Li, Jun ^d   Wang, Qicong ^a   Sun, Le ^a   Wei, Zhihui ^a   Plaza, Javier ^c   Plaza, Antonio ^c  

^a NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b JIANGSU HIGH TECHNOLOGY RESEARCH KEY LABORATORY FOR WIRELESS SENSOR NETWORKS   (China)

^c UNIVERSITY OF EXTREMADURA   (Spain)

^d SUN YAT SEN UNIVERSITY   (China)

Author keywords

Graphics processing units (GPUs); hyperspectral image; parallel; sparse multinomial logistic regression (SMLR); spatially adaptive Markov random fields (MRFs); spectral spatial classification

Indexed keywords

COMPUTER GRAPHICS; COMPUTER GRAPHICS EQUIPMENT; GRAPHICS PROCESSING UNIT; HYPERSPECTRAL IMAGING; IMAGE CLASSIFICATION; IMAGE CODING; IMAGE PROCESSING; MARKOV PROCESSES; MEMORY ARCHITECTURE; PROGRAM PROCESSORS; REGRESSION ANALYSIS; SPECTROSCOPY;

COMPUTATIONALLY EFFICIENT; COMPUTE UNIFIED DEVICE ARCHITECTURES; CONTEXTUAL INFORMATION; MARKOV RANDOM FIELD; MULTINOMIAL LOGISTIC REGRESSION; PARALLEL; PARALLEL IMPLEMENTATIONS; SPECTRAL-SPATIAL CLASSIFICATION;

CLASSIFICATION (OF INFORMATION);

ALGORITHM; IMAGE CLASSIFICATION; IMAGE PROCESSING; NUMERICAL METHOD; REGRESSION ANALYSIS; REMOTE SENSING;

EID: 85031812286     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2017.2755639     Document Type: Article

References (45)

1. M. Fauvel, Y. Tarabalka, J. A. Benediktsson, J. Chanussot, and J. C. Tilton, "Advances in spectral-spatial classification of hyperspectral images, " Proc. IEEE, vol. 101, no. 3, pp. 652-675, Mar. 2013.
2. A. Plaza et al., "Recent advances in techniques for hyperspectral image processing, " Remote Sens. Environ., vol. 113, pp. S110-S122, Sep. 2009.
3. A. Plaza, J. M. Bioucas-Dias, A. Simic, andW. J. Blackwell, "Foreword to the special issue on hyperspectral image and signal processing, " IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 5, no. 2, pp. 347-353, Apr. 2012.
4. 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.
5. B. Krishnapuram, L. Carin, M. A. Figueiredo, and A. J. Hartemink, "Sparse multinomial logistic regression: Fast algorithms and generalization bounds, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 6, pp. 957-968, Jun. 2005.
6. J. Li, J. M. Bioucas-Dias, and A. Plaza, "Semisupervised hyperspectral image classification using soft sparse multinomial logistic regression, " IEEE Geosci. Remote Sens. Lett., vol. 10, no. 2, pp. 318-322, Mar. 2013.
7. Z. Wu, Q. Wang, A. Plaza, J. Li, L. Sun, and Z. Wei, "Real-Time implementation of the sparse multinomial logistic regression for hyperspectral image classification on GPUs, " IEEE Geosci. Remote Sens. Lett., vol. 12, no. 7, pp. 1456-1460, Jul. 2015.
8. F. Xiao, G. Ge, L. Sun, and R. Wang, "An energy-efficient data gathering method based on compressive sensing for pervasive sensor networks, " Pervasive Mobile Comput., 2017. doi: 10.1016/j.pmcj.2017.02.005, to be published.
9. A. Plaza, Q. Du, Y. Chang, and R. L. King, "High performance computing for hyperspectral remote sensing, " IEEE J. Sel. Topics Signal Process., vol. 4, no. 3, pp. 528-544, Sep. 2011.
10. F. Xiao, Z. Jiang, X. Xie, L. Sun, and R. Wang, "An energy-efficient data transmission protocol for mobile crowd sensing, " Peer-To-Peer Netw. Appl., vol. 10, no. 3, pp. 510-518, 2017.
11. C. Gonzalez, D. Mozos, J Resano, and A. Plaza, "FPGA implementation of the N-FINDR algorithm for remotely sensed hyperspectral image analysis, " IEEE Trans. Geosci. Remote Sens., vol. 50, no. 2, pp. 374-388, Feb. 2012.
12. A. Plaza, D. Valencia, J. Plaza, and P. Martinez, "Commodity clusterbased parallel processing of hyperspectral imagery, " J. Parallel Distrib. Comput., vol. 66, no. 3, pp. 345-358, 2006.
13. S. Bernabe, S. Sanchez, A. Plaza, S. Lopez, J. A. Benediktsson, and R. Sarmiento, "Hyperspectral unmixing on GPUs and multi-core processors: A comparison, " IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 6, no. 3, pp. 1386-1398, Mar. 2013.
14. A. Barberis, G. Danese, F. Leporati, A. Plaza, and E. Torti, "Real-Time implementation of the vertex component analysis algorithm on GPUs, " IEEE Geosci. Remote Sens. Lett., vol. 10, no. 2, pp. 251-255, Feb. 2013.
15. J. M. P. Nascimento, J.M. Bioucas-Dias, J.M. Rodriguez Alves, V. Silva, and A. Plaza, "Parallel hyperspectral unmixing on GPUs, " IEEE Geosci. Remote Sens. Lett., vol. 11, no. 3, pp. 666-670, Mar. 2014.
16. Y. Wu and L. Gao, "Graphics processing unit-Accelerated computation of the Markov random fields and loopy belief propagation algorithms for hyperspectral image classification, " J. Appl. Remote Sens., vol. 9, no. 1, 2015, Art. no. 097295.
17. Z. Wu, S. Ye, J. Liu, L. Sun, and Z. Wei, "Sparse nonnegative matrix factorization on GPUs for hyperspectral unmixing, " IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 7, no. 8, pp. 3640-3649, Aug. 2014.
18. R. Ji, Y. Gao, R. Hong, Q. Liu, D. Tao, and X. Li, "Spectral-spatial constraint hyperspectral image classification, " IEEE Trans. Geosci. Remote Sens., vol. 52, no. 3, pp. 1811-1824, Mar. 2014.
19. J. Li, P. Reddy Marpu, A. Plaza, J. Bioucas-Dias, and J. Atli Benediktsson, "Generalized composite kernel framework for hyperspectral image classification, " IEEE Trans.Geosci. Remote Sens., vol. 51, no. 9, pp. 4816-4829, Sep. 2013.
20. J. Liu, Z. Wu, Z. Wei, L. Xiao, and L. Sun, "Spatial-spectral kernel sparse representation for hyperspectral image classification, " IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 6, no. 6, pp. 2462-2471, Dec. 2013.
21. G. Camps-Valls, N. Shervashidze, and K. M. Borgwardt, "Spatio-spectral remote sensing image classification with graph kernels, " IEEE Geosci. Remote Sens. Lett., vol. 7, no. 4, pp. 741-745, Oct. 2010.
22. 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.
23. X. Kang, S. Li, and J. Benediktsson, "Spectral-spatial hyperspectral image classificationwith edge-preserving filtering, " IEEE Trans. Geosci. Remote Sens., vol. 52, no. 5, pp. 2666-2677, May 2014.
24. Y. Tarabalka, J. Chanussot, and J. A. Benediktsson, "Segmentation and classification of hyperspectral images using watershed transformation, " Pattern Recognit., vol. 43, no. 7, pp. 2367-2379, Jul. 2010.
25. S. Li, B. Zhang, A. Li, X. Jia, L. Gao, and M. Peng, "Hyperspectral imagery clustering with neighborhood constraints, " IEEE Geosci. Remote Sens. Lett., vol. 10, no. 3, pp. 588-592, Mar. 2013.
26. X. Sun, Q. Qu, N. M. Nasrabadi, and T. D. Tran, "Structured priors for sparse-representation-based hyperspectral image classification, " IEEE Geosci. Remote Sens. Lett., vol. 11, no. 7, pp. 1235-1239, Jul. 2014.
27. L. Zhang et al., "Kernel sparse representation based classifier, " IEEE Trans. Signal Process., vol. 60, no. 4, pp. 1684-1695, Apr. 2012.
28. J. Li, J. M. Bioucas-Dias, and A. Plaza, "Spectral-spatial hyperspectral image segmentation using subspace multinomial logistic regression and Markov random fields, " IEEE Trans. Geosci. Remote Sens., vol. 50, no. 3, pp. 809-823, Mar. 2012.
29. Y. Tarabalka, M. Fauvel, J. Chanussot, and J. A. Benediktsson, "SVM-And MRF-based method for accurate classification of hyperspectral images, " IEEE Geosci. Remote Sens. Lett., vol. 7, no. 4, pp. 736-740, Apr. 2010.
30. B. Zhang, S. Li, X. Jia, L. Gao, and M. Peng, "Adaptive Markov random field approach for classification of hyperspectral imagery, " IEEE Geosci. Remote Sens. Lett., vol. 8, no. 5, pp. 973-977, May 2011.
31. G. Moser and S. B. Serpico, "Combining support vector machines and Markov random fields in an integrated framework for contextual image classification, " IEEE Trans.Geosci. Remote Sens., vol. 51, no. 5, pp. 2734-2752, May 2013.
32. L. Sun, Z. Wu, J. Liu, L. Xiao, and Z. Wei, "Supervised spectral-spatial hyperspectral image classification with weighted Markov random fields (MRFs), " IEEE Trans. Geosci. Remote Sens., vol. 53, no. 5, pp. 1490-1503, Mar. 2015.
33. J. Li, J.M. Bioucas-Dias, and A. Plaza, "Semisupervised hyperspectral image segmentation using multinomial logistic regression with active learning, " IEEE Trans. Geosci. Remote Sens., vol. 48, no. 11, pp. 4085-4098, Nov. 2010.
34. 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.
35. J. Li, J. M. Bioucas-Dias, and A. Plaza, "Hyperspectral image segmentation using a new Bayesian approach with active learning, " IEEE Trans. Geosci. Remote Sens., vol. 49, no. 10, pp. 3947-3960, Oct. 2011.
36. J. Li, J. M. Bioucas-Dias, and A. Plaza, "Spectral-spatial hyperspectral image segmentation using subspace multinomial logistic regression and Markov random fields, " IEEE Trans. Geosci. Remote Sens., vol. 50, no. 3, pp. 809-823, Mar. 2012.
37. M. D. Iordache, J. M. Bioucas-Dias, and A. Plaza, "Total variation spatial regularization for sparse hyperspectral unmixing, " IEEE Trans. Geosci. Remote Sens., vol. 50, no. 11, pp. 4484-4502, Nov. 2012.
38. J. M. Bioucas-Dias and M. A. T. Figueiredo, "Alternating direction algorithms for constrained sparse regression: Application to hyperspectral unmixing, " in Proc. 2nd Workshop Hyperspectral Image Signal Process. Evol. Remote Sens., 2010. pp. 1-4.
39. W. Deng, W. Yin, and Y. Zhang, "Group sparse optimization by alternating direction method, " Dept. Comput. Appl. Math., Rice Univ., Houston, TX, USA, 2011.
40. J. M. Bioucas-Dias and M. Figueiredo, "Logistic regression via variable splitting and augmented Lagrangian tools, " Instituto Superior Tecnico, Tech. Univ. Lisbon, Lisbon, Portugal, Tech. Rep., 2009.
41. NVIDIA Developer Zone, "Cufft library users guide, " Mar. 2015. [Online]. Available: http://docs.nvidia.com/cuda/pdf/CUFFT-Library.pdf
42. NVIDIA CUDA Zone, "CUDA toolkit, " Mar. 2015. [Online]. Available: https://developer.nvidia.com/cuda-Toolkit
43. S. Bernabe, S. Sanchez, A. Plaza, S. Lopez, J. A. Benediktsson, and R. Sarmiento, "Hyperspectral unmixing on GPUs and multi-core processors: A comparison, " IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 6, no. 3, pp. 1386-1398, Mar. 2013.
44. Intel Developer Zone, "Reference manual for intel R math kernel library 11.2, " Nov. 2014. [Online]. Available: https://software.intel.com/enus/mkl-11.2-ref
45. G. M. Foody, "Classification accuracy comparison: hypothesis tests and the use of confidence intervals in evaluations of difference, equivalence and non-inferiority, " Remote Sens. Environ., vol. 113, no. 8, pp. 1658-1663, Aug. 2009.