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

Selim Hemissi, Imed Riadh Farah

2013

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.

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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