A novel hierarchical semisupervised SVM for classification of hyperspectral images

IEEE Geoscience and Remote Sensing Letters

Volumn 11, Issue 9, 2014, Pages 1609-1613

  Shao, Zhenfeng ^a   Zhang, Lei ^a   Zhou, Xiran ^a   Ding, Lin ^a  

^a Mapping and Remote Sensing   (China)

Author keywords

Hyperspectral image classification; semisupervised learning; support vector machine (SVM)

Indexed keywords

CLASSIFICATION (OF INFORMATION); IMAGE CLASSIFICATION; INDEPENDENT COMPONENT ANALYSIS; SPECTROSCOPY;

CLASSIFICATION INFORMATIONS; CLASSIFICATION METHODS; CLUSTER FEATURE; HIERARCHICAL STRUCTURES; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL IMAGE CLASSIFICATION; SEMI- SUPERVISED LEARNING; UNLABELED SAMPLES;

SUPPORT VECTOR MACHINES;

EID: 84899919914     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2014.2302034     Document Type: Article

References (19)

1. S. Serranti, D. Cesare, F. Marini, and G. Bonifazi, "Classification of oat and groat kernels using NIR hyperspectral imaging," Talanta, vol. 103, pp. 276-284, Jan. 2013.
2. A. Villa, J. Chanussot, and J. A. Benediktsson, "Spectral unmixing for the classification of hyperspectral images at a finer spatial resolution," IEEE J. Sel. Topics Signal Process., vol. 5, no. 3, pp. 521-533, Jun. 2011.
3. L. Shijin, W. Hao, and W. Dingsheng, "An effective feature selection method for hyperspectral image classification based on genetic algorithm and support vector machine," Knowl.-Based Syst, vol. 24, no. 1, pp. 40-48, Feb. 2011.
4. P. H. Hsu, "Feature extraction of hyperspectral images using wavelet and matching pursuit," ISPRS J. Photogramm. Remote Sens., vol. 62, no. 2, pp. 78-92, Jun. 2007.
5. W. Kim and M. Crawford, "Adaptive classification for hyperspectral image data using manifold regularization kernel machines," IEEE Trans. Geosci. Remote Sens., vol. 48, no. 11, pp. 4110-4121, Nov. 2010.
6. G. F. Hughes, "On the mean accuracy of statistical pattern recognizers," IEEE Trans. Inf. Theory, vol. IT-14, no. 1, pp. 55-63, Jan. 1968.
7. M. Chi and L. Bruzzone, "Semisupervised classification of hyperspectral images by SVMs optimized in the primal," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 6, pp. 1870-1880, Jun. 2007. (Pubitemid 46853295)
8. L. Bruzzone and M. M. Chi, "A novel transductive SVM for the semisupervised classification of remote-sensing images," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 11, pp. 3363-3373, Nov. 2006.
9. V. G. Camps, T. V. Bandos, and D. Y. Zhou, "Semisupervised graph-based hyperspectral image classification," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 10, pp. 3044-3054, Oct. 2007.
10. F. Ratle, G. Camps-Valls, and J. Weston, "Semisupervised neural networks for efficient hyperspectral image classification," IEEE Trans. Geosci. Remote Sens., vol. 48, no. 5, pp. 2271-2282, May 2010.
11. M. Marconcini, G. Camps-Valls, and L. Bruzzone, "A composite semisupervised SVM for classification of hyperspectral images," IEEE Geosci. Remote Sens. Lett., vol. 6, no. 2, pp. 234-238, Apr. 2009.
12. H. Su, H. Yang, and Q. Du, "Semisupervised band clustering for dimensionality reduction of hyperspectral imagery," IEEE Geosci. Remote Sens. Lett., vol. 8, no. 6, pp. 1135-1139, Nov. 2011.
13. L. Gómez-Chova, G. Camps-Valls, and J. Munoz-Mari, "Semisupervised image classification with Laplacian support vector machines," IEEE Geosci. Remote Sens. Lett., vol. 5, no. 3, pp. 336-340, Jul. 2008.
14. Y. Tarabalka, J. A. Benediktsson, and J. Chanussot, "Spectral- spatial classification of hyperspectral imagery based on partitional clustering techniques," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 8, pp. 2973-2987, Aug. 2009.
15. C. L. Stork and M. R. Keenan, "Advantages of clustering in the phase classification of hyperspectral materials images," Microsc. Microanal., vol. 16, no. 6, pp. 810-820, Dec. 2010.
16. D. Q. Zhang and S. C. Chen, "Kernel-based fuzzy and possibilistic c-means clustering," in Proc. Int. Conf. Artif. Neural Netw., 2003, pp. 122-125.
17. L. Wang, K. Inoue, and K. Urahama, "Robust kernel fuzzy clustering," in Proc. Fuzzy Syst. Knowl. Discov., 2005, pp. 454-461. (Pubitemid 41480286)
18. S. Zhenfeng, Z. Xiran, and L. Jun, "QaR tree method for optimal image particle decomposing," Geomatics Inf. Sci. Wuhan Univ., vol. 38, no. 2, pp. 204-207, 2013.
19. J. A. Gualtieri and S. Chettri, "Support vector machines for classification of hyperspectral data," in Proc. IEEE IGARSS, 2000, vol. 2, pp. 813-815. (Pubitemid 32019653)