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Fuzzy Methods in Image Mining

  • Chapter
Book cover Methods for Handling Imperfect Spatial Information

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 256))

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Abstract

This paper presents the use of soft methods in image mining. Image mining considers the chain from object identification on natural or man-made processes from remote sensing images through modelling, tracking on a series of images and prediction, towards communication to stakeholders. Attention is given to image mining for vague and uncertain objects. Aspects of up- and downscaling are addressed. We further consider in this paper both spatial interpolation and decision making. The paper is illustrated with several case studies.

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Author information

Authors and Affiliations

  1. ITC, PO Box 6, 7500 AA, Enschede, The Netherlands

    Alfred Stein

Authors
  1. Alfred Stein
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Editor information

Editors and Affiliations

  1. IGM Université Paris Est, Champs-sur-Marne, France

    Robert Jeansoulin

  2. LSIS UMR CNRS, Marseille, France

    Odile Papini

  3. Université Paul Sabatier, Toulouse, France

    Henri Prade

  4. Ghent University, Ghent, Belgium

    Steven Schockaert

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Stein, A. (2010). Fuzzy Methods in Image Mining. In: Jeansoulin, R., Papini, O., Prade, H., Schockaert, S. (eds) Methods for Handling Imperfect Spatial Information. Studies in Fuzziness and Soft Computing, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14755-5_10

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  • DOI: https://doi.org/10.1007/978-3-642-14755-5_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14754-8

  • Online ISBN: 978-3-642-14755-5

  • eBook Packages: EngineeringEngineering (R0)

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