OSA's Digital Library

Chinese Optics Letters

Chinese Optics Letters

| PUBLISHED MONTHLY BY CHINESE LASER PRESS AND DISTRIBUTED BY OSA

  • Vol. 9, Iss. 1 — Jan. 10, 2011
  • pp: 011002–

Combining clustering and classification for remote-sensing images using unlabeled data

Xiaoyong Bian, Tianxu Zhang, and Xiaolong Zhang  »View Author Affiliations


Chinese Optics Letters, Vol. 9, Issue 1, pp. 011002- (2011)


View Full Text Article

Acrobat PDF (216 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations
  • Export Citation/Save Click for help

Abstract

A joint clustering and classification approach is proposed. This approach exploits unlabeled data for efficient clustering, which is applied in the classification with support vector machine (SVM) in the case of small-size training samples. The proposed method requires no prior information on data labels, and yields better cluster structures. Through cluster assumption and the notions of support vectors, the most confident k cluster centers and data points near the cluster boundaries are labeled and used to train a reliable SVM classifier. Our method gains better estimation of data distributions and mitigates the unrepresentative problem of small-size training samples. The data set collected from Landsat Thematic Mapper (Landsat TM-5) validates the effectiveness of the proposed approach.

© 2011 Chinese Optics Letters

OCIS Codes
(100.5010) Image processing : Pattern recognition
(100.3008) Image processing : Image recognition, algorithms and filters

Citation
Xiaoyong Bian, Tianxu Zhang, and Xiaolong Zhang, "Combining clustering and classification for remote-sensing images using unlabeled data," Chin. Opt. Lett. 9, 011002- (2011)
http://www.opticsinfobase.org/col/abstract.cfm?URI=col-9-1-011002


Sort:  Author  |  Year  |  Journal  |  Reset

References

  1. H. Deng, J. Liu, and Z. Chen, Chin. Opt. Lett. 8, 24 (2010).
  2. H. Su and Y. Sheng, Chin. Opt. Lett. 8, 811 (2010).
  3. G. Hu, S. Zhou, J. Guan, and X. Hu, Information Processing and Management 44, 1397 (2008).
  4. W. Tang, H. Xiong, S. Zhong, and J. Wu, in Proceedings of Knowledge Discovery and Data Mining (KDD'07) 707 (2007).
  5. M. Chi, R. Feng, and L. Bruzzone, Advances in Space Research 41, 1793 (2008).
  6. L. Bruzzone, M. Chi, and M. Marconcini, IEEE Trans. Geosci. Remote Sens. 44, 3363 (2006).
  7. M. Chi, Q. Qian, and J. A. Benediktsson, in Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS'08) I-209 (2008).
  8. H.-J. Zeng, X.-H. Wang, Z. Chen, H. Lu, and W.-Y. Ma, in Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM'03) (2003).
  9. Z. Liu, J. Liu, C. Pan, and G. Wang, IEEE Trans. Neural Networks 20, 1215 (2009).
  10. O. Chapelle and A. Zien, in Proceedings of the International Workshop on Artificial Intelligence and Statistics (AISTATS'05) (2005).

Cited By

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited