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Comparison of Unsupervised Band Selection Methods for Hyperspectral Imaging

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4477))

Abstract

Different methods have been proposed in order to deal with the huge amount of information that hyperspectral applications involve. This paper presents a comparison of some of the methods proposed for band selection. A relevant and recent set of methods have been selected that cover the main tendencies in this field. Moreover, a variant of an existing method is also introduced in this work. The comparison criterion used is based on pixel classification tasks.

This work has been partly supported by projects ESP2005-07724-C05-05 from Spanish CICYT.

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Joan Martí José Miguel Benedí Ana Maria Mendonça Joan Serrat

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© 2007 Springer Berlin Heidelberg

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Martínez-Usó, A., Pla, F., Sotoca, J.M., García-Sevilla, P. (2007). Comparison of Unsupervised Band Selection Methods for Hyperspectral Imaging. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72847-4_6

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  • DOI: https://doi.org/10.1007/978-3-540-72847-4_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72846-7

  • Online ISBN: 978-3-540-72847-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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