Unsupervised Spectral-Spatial Feature Learning With Stacked Sparse Autoencoder for Hyperspectral Imagery Classification

IEEE Geoscience and Remote Sensing Letters

Volumn 12, Issue 12, 2015, Pages 2438-2442

  Tao, Chao ^a   Pan, Hongbo ^a   Li, Yansheng ^b   Zou, Zhengrou ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b WUHAN UNIVERSITY   (China)

Author keywords

Feature extraction; Hyperspectral imaging; Standards; Training; Training data

Indexed keywords

LEARNING SYSTEMS; REMOTE SENSING; SPECTROSCOPY;

FEATURE LEARNING; FEATURE REPRESENTATION; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL IMAGERY; HYPERSPECTRAL IMAGERY CLASSIFICATIONS; LINEAR SUPPORT VECTOR MACHINES; SPATIAL FEATURES; SPECTRAL FEATURE;

CLASSIFICATION (OF INFORMATION);

EID: 84947865496     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2015.2482520     Document Type: Article

References (17)

1. C.-I. Chang, Hyperspectral Data Exploitation: Theory and Applications. New York, NY, USA: Wiley-Interscience, 2007.
2. D. Tuia, R. Flamary, and N. Courty, "Multiclass feature learning for hyperspectral image classification: Sparse and hierarchical solutions," ISPRS J. Photogramm. Remote Sens., vol. 105, pp. 272-285, 2015.
3. A. Plaza, P. Martinez, J. Plaza, and R. Perez, "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.
4. C.-I. Chang and H. Ren, "An experiment-based quantitative and comparative analysis of target detection and image classification algorithms for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 38, no. 2, pp. 1044-1063, Mar. 2000.
5. M. Fauvel, Y. Tarabalka, J. A. Benediktsson, J. Chanussot, and J. C. Tilton, "Advances in spectral-spatial classification of hyperspectral images," in Proc. IEEE, vol. 101, no. 3, pp. 652-675, Mar. 2013.
6. 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.
7. M. Dalla Mura, A. Villa, J. A. Benediktsson, J. Chanussot, and L. Bruzzone, "Extended profiles with morphological attribute filters for the analysis of hyperspectral data," Int. J. Remote Sens., vol. 32, no. 22, pp. 5975-5991, 2010.
8. C. Tao, Y. Q. Tang, C. Fan, and Z. R. Zou, "Hyperspectral imagery classification based on rotation invariant spectral-spatial feature," IEEE Geosci. Remote Sens. Lett., vol. 11, no. 5, pp. 980-984, May 2014.
9. G. Camps-Valls, L. Gomez-Chova, J. Munoz-Mari, J. Vila-Francés, and J. Calpe-Maravilla, "Composite kernels for hyperspectral image classification," IEEE Geosci. Remote Sens. Lett., vol. 3, no. 1, pp. 93-97, Jan. 2006.
10. J. Li, P. R. Marpu, A. Plazam, J. M. Bioucas-Dias, and J. A. Benediktsson, "Generalized composite kernel framework for hyperspectral image classification," IEEE Trans. Geosci. Remote Sens., vol. 51, no. 9, pp. 4816-4829, Sep. 2013.
11. J. Li et al., "Multiple feature learning for hyperspectral image classification," IEEE Trans. Geosci. Remote Sens., vol. 53, no. 3, pp. 1592-1606, Mar. 2015.
12. S. Hoo-Chang, M. R. Orton, D. J. Collins, S. J. Doran, and M. O. Leach, "Stacked autoencoders for unsupervised feature learning and multiple organ detection in a pilot study using 4D patient data," IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 8, pp. 1930-1943, Aug. 2013.
13. Y. C. Tang and C. Eliasmith, "Deep networks for robust visual recognition," in Proc. ICML, 2010, pp. 1055-1062.
14. C. Farabet, C. Couprie, L. Najman, and Y. LeCun, "Learning hierarchical features for scene labeling," IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 8, pp. 1915-1929, Aug. 2013.
15. Y. S. Chen, Z. H. Lin, X. Zhao, G. Wang, and Y. F. Gu, "Deep learning-based classification of hyperspectral data," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 7, no. 6, pp. 2094-2107, Jun. 2014.
16. J. Wright et al., "Sparse representation for computer vision and pattern recognition," Proc. IEEE, vol. 98, no. 6, pp. 1031-1044, Jun. 2010.
17. G. Hinton and R. Salakhutdinov, "Reducing the dimensionality of data with neural networks," Science, vol. 313, no. 5786, pp. 504-507, Jul. 2006.