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International Workshop on Fuzzy Logic in Artificial Intelligence

FLAI 1997: Fuzzy Logic in Artificial Intelligence pp 166–179Cite as

An application of possibility theory information fusion to satellite image classification

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1566))

Abstract

This paper presents the application of an adaptive information fusion operator developed in the framework of possibility theory for the supervised classification of multisource remote sensing images. This operator is low CPU time consuming and carries out classification rates comparable to maximum likelihood.

The adaptive operator has been designed to merge several agreeing information sources which might be in conflict from time to time. It has been used for the classification of two data sets: a Landsat MSS image and GIS data on the one hand, and multitemporal SPOT XS visible images on the other hand. Satellite images of the same scene are redundant and complementary, and this operator is efficient at handling this kind of data.

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Author information

Authors and Affiliations

  1. Nasda-Eorc, 1-9-9 Roppongi, Minato-ku, 106-0032, Tokyo, Japan

    Ludovic Roux

Authors
  1. Ludovic Roux
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Editor information

Anca L. Ralescu James G. Shanahan

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© 1999 Springer-Verlag Berlin Heidelberg

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Roux, L. (1999). An application of possibility theory information fusion to satellite image classification. In: Ralescu, A.L., Shanahan, J.G. (eds) Fuzzy Logic in Artificial Intelligence. FLAI 1997. Lecture Notes in Computer Science, vol 1566. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095077

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  • DOI: https://doi.org/10.1007/BFb0095077

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66374-4

  • Online ISBN: 978-3-540-48358-8

  • eBook Packages: Springer Book Archive

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