A Multi-features Fusion of Multi-temporal Hyperspectral Images using a Cooperative GDD/SVM Method

Selim Hemissi, Imed Riadh Farah

Abstract

Considering the emergence of hyperspectral sensors, feature fusion has been more and more important for images classification, indexing and retrieval. In this paper, a cooperative fusion method GDD/SVM (Generalized Dirichlet Distribution/Support Vector Machines), which involves heterogeneous features, is proposed for multi-temporal hyperspectral images classification. It differentiates, from most of the previous approaches, by incorporating the potentials of generative models into a discriminative classifier. Therefore, the multi-features, including the 3D spectral features and textural features, can be integrated with an efficient way into a unified robust framework. The experimental results on a series of Hyperion images confirm the improved performance and show that this cooperative fusion approach has consistence over different testing datasets.

References

  1. Bishop, C. M. (2006). Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag New York, Inc., Secaucus, NJ, USA.
  2. Bouguila, N. and Ziou, D. (2010). A dirichlet process mixture of generalized dirichlet distributions for proportional data modeling. IEEE Transactions on Neural Networks, 21(1):107-122.
  3. Burges, C. J. C. (1998). A tutorial on support vector machines for pattern recognition. Data Min. Knowl. Discov., 2(2):121-167.
  4. Clark, R., Swayze, G., Wise, R., Livo, E., Hoefen, T., Kokaly, R., and Sutley, S. (2007). Usgs digital spectral library splib06a: U.s. geological survey. In Digital Data Series 2312007. NASA, USGS.
  5. Cristianini, N. and Shawe-Taylor, J. (2000). An Introduction to Support Vector Machines. Cambridge University Press, Cambridge, UK.
  6. Farah, I. R., Hemissi, S., Ettabaa, K. S., and Souleiman, B. (2010). Multi-temporal Hyperspectral Images Unmixing and Classification Based on 3D Signature Model and Matching. Piers Online, 6:480-484.
  7. Heinz, D., Davidson, C., and Ben-David, A. (2010). Temporal-spectral detection in long-wave ir hyperspectral imagery. IEEE Sensors Journal, 10(3):509 -517.
  8. LeBlanc, K. and Saffiotti, A. (2007). Cooperative information fusion in a network robot system. In Proceedings of the 1st international conference on Robot communication and coordination, RoboComm 7807, pages 42:1-42:4, Piscataway, NJ, USA. IEEE Press.
  9. Nakariyakul, S. and Casasent, D. (2004). Hyperspectral feature selection and fusion for detection of chicken skin tumors. In Proc. SPIE, pages 128-139.
  10. Sun, J., Ovsjanikov, M., and Guibas, L. (2009). A concise and provably informative multi-scale signature based on heat diffusion. In Proceedings of the Symposium on Geometry Processing, SGP 7809, pages 1383-1392. Eurographics Association.
  11. Ulusoy, I. and Bishop, C. M. (2006). Comparison of generative and discriminative techniques for object detection and classification. Toward CategoryLevel Object Recognition, pages 173-195.
  12. Wang, Y. and Chua, C. (2005). Face recognition from 2d and 3d images using 3d gabor filters. Image and Vision Computing, 23(11):1018-1028.
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Paper Citation


in Harvard Style

Hemissi S. and Riadh Farah I. (2013). A Multi-features Fusion of Multi-temporal Hyperspectral Images using a Cooperative GDD/SVM Method . In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: PRG, (ICPRAM 2013) ISBN 978-989-8565-41-9, pages 681-685. DOI: 10.5220/0004377406810685


in Bibtex Style

@conference{prg13,
author={Selim Hemissi and Imed Riadh Farah},
title={A Multi-features Fusion of Multi-temporal Hyperspectral Images using a Cooperative GDD/SVM Method},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: PRG, (ICPRAM 2013)},
year={2013},
pages={681-685},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004377406810685},
isbn={978-989-8565-41-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: PRG, (ICPRAM 2013)
TI - A Multi-features Fusion of Multi-temporal Hyperspectral Images using a Cooperative GDD/SVM Method
SN - 978-989-8565-41-9
AU - Hemissi S.
AU - Riadh Farah I.
PY - 2013
SP - 681
EP - 685
DO - 10.5220/0004377406810685