Superpixel-based classification of hyperspectral data using sparse representation and conditional random fields

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn , Issue , 2014, Pages 3674-3677

  Roscher, Ribana ^a   Waske, Björn ^a  

^a FREIE UNIVERSITÄT BERLIN   (Germany)

Author keywords

hyperspectral; random field; Sparse coding; sparse representation; superpixel

Indexed keywords

IMAGE SEGMENTATION; PIXELS; RANDOM PROCESSES; REMOTE SENSING; SPECTROSCOPY; SUPERPIXELS;

CONDITIONAL RANDOM FIELD; HIERARCHICAL STRUCTURES; HYPERSPECTRAL; HYPERSPECTRAL IMAGE DATAS; RANDOM FIELDS; SPARSE CODING; SPARSE REPRESENTATION; WEIGHTED LINEAR COMBINATIONS;

CLASSIFICATION (OF INFORMATION);

EID: 84911382221     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2014.6947280     Document Type: Conference Paper

References (18)

1. Gustavo Camps-Valls, Devis Tuia, Lorenzo Bruzzone, and J Benediktsson, "Advances in hyperspectral image classification: Earth monitoring with statistical learning methods," IEEE Signal Processing Magazine, Vol. 31, no. 1, pp. 45-54, 2014.
2. J. Bioucas-Dias, A. Plaza, G. Camps-Valls, P. Scheunders, N. Nasrabadi, and J. Chanussot, "Hyperspectral remote sensing data analysis and future challenges," IEEE Geosci. Remote Sens. Mag., Vol. 1, no. 2, pp. 6-36, 2013.
3. Benqin Song, Jun Li, M. Dalla Mura, Peijun Li, A. Plaza, J.M. Bioucas-Dias, J. Atli Benediktsson, and J. Chanussot, "Remotely sensed image classification using sparse representations of morphological attribute profiles," IEEE Trans. Geosci. Remote Sens., Vol. 52, no. 8, pp. 5122-5136, 2014.
4. Ali-Asghar Soltani-Farani, Hamid R. Rabiee, and Seyyed Abbas Hosseini, "Spatial-aware dictionary learning for hyperspectral image classification," Proc. Conference on Computer Vision and Pattern Recognition, 2013.
5. Y. Chen, Nasser M. Nasrabadi, and Trac D. Tran, "Hyperspectral image classification via kernel sparse representation," IEEE Trans. Geosci. Remote Sens., Vol. 51, no. 1, pp. 217-231, 2013.
6. Y. Chen, Nasser M. Nasrabadi, and Trac D. Tran, "Hyperspectral image classification using dictionary-based sparse representation," IEEE Trans. Geosci. Remote Sens., Vol. 49, no. 10, pp. 3973-3985, 2011.
7. Shuyuan Yang, Honghong Jin, Min Wang, Yu Ren, and Licheng Jiao, "Data-driven compressive sampling and learning sparse coding for hyperspectral image classification," IEEE Geosci. Remote Sens. Lett., Vol. 11, no. 2, pp. 479-483, 2014.
8. Adam S Charles, Bruno A Olshausen, and Christopher J Rozell, "Learning sparse codes for hyperspectral imagery," IEEE J. Sel. Topics Signal Process., Vol. 5, no. 5, pp. 963-978, 2011.
9. Haoliang Yuan, Yang Lu, Lina Yang, Huiwu Luo, and Yuan Yan Tang, "Sparse representation using contextual information for hyperspectral image classification," in IEEE International Conference on Cybernetics, 2013, pp. 138-143.
10. U. Srinivas, Yi Chen, V. Monga, N.M. Nasrabadi, and T.D. Tran, "Exploiting sparsity in hyperspectral image classification via graphical models," IEEE Geosci. Remote Sens. Lett., Vol. 10, no. 3, pp. 505-509, 2013.
11. Jingting Liu, Weidong Yang, Shulun Tan, and Zijian Wang, "Remote sensing image classification based on random projection super-pixel segmentation," in Proc. Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 2013, vol. 8921.
12. J. Stefanski, B. Mack, and B. Waske, "Optimization of object-based image analysis with random forests for land cover mapping," IEEE J. Sel. Topics Appl. Earth Observ., Vol. 6, no. 6, pp. 2492-2504, 2013.
13. S. Kumar and M. Hebert, "Discriminative random fields," International Journal of Computer Vision, Vol. 68, no. 2, pp. 179-201, 2006.
14. John D. Lafferty, Andrew McCallum, and Fernando C. N. Pereira, "Conditional random fields: Probabilistic models for segmenting and labeling sequence data," in Proc. International Conference on Machine Learning, 2001, pp. 282-289.
15. R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Süsstrunk, "Slic superpixels compared to state-of-the-art superpixel methods," IEEE Trans. Pattern Anal. Mach. Intell., Vol. 34, no. 11, pp. 2274-2282, 2012.
16. Joel A Tropp, Anna C Gilbert, and Martin J Strauss, "Algorithms for simultaneous sparse approximation. part i: Greedy pursuit," Signal Processing, Vol. 86, no. 3, pp. 572-588, 2006.
17. Yuri Boykov, Olga Veksler, and Ramin Zabih, "Fast approximate energy minimization via graph cuts," IEEE Trans. Pattern Anal. Mach. Intell., Vol. 23, no. 11, pp. 1222-1239, 2001.
18. Gustavo Camps-Valls, Luis Gomez-Chova, Jordi Muñoz-Marí, Joan Vila-Francés, and Javier Calpe-Maravilla, "Composite kernels for hyperspectral image classification," IEEE Geosci. Remote Sens. Lett., Vol. 3, no. 1, pp. 93-97, 2006.