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Fusion of Image Information under Imprecision

  • Isabelle Bloch
  • Henri Maître
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 12)

Abstract

We present in this paper a review of image fusion techniques paying a special attention to the management of uncertainty and imprecision. We investigate the three main numerical methods based on probabilistic reasoning, fuzzy set theory and Dempster-Shafer evidence theory. We show how it is possible to introduce imprecision at the three basic levels of modelling, combining and deciding. We underline the main advantages of each method at these three levels. We also explore some promising fields where innovative works will most certainly take place in the coming years. They concern the management of spatial information within the framework of fusion and require the development of new tools or the extension of yet established ones.

Keywords

Spatial Information Image Fusion Data Fusion Markov Random Field Image Information 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Isabelle Bloch
    • 1
  • Henri Maître
    • 1
  1. 1.Ecole Nationale Supérieure des Télécommunications, département ImagesCNRS URA 820ParisFrance

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