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Aggregation and Fusion of Imperfect Information pp 189–213Cite as

Fusion of Image Information under Imprecision

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Part of the book series: Studies in Fuzziness and Soft Computing ((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.

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  1. Ecole Nationale Supérieure des Télécommunications, département Images, CNRS URA 820, 46 rue Barrault, 75013, Paris, France

    Isabelle Bloch & Henri Maître

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  1. Isabelle Bloch
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  1. Centre National de la Recherche Scientifique, LIP6 — Laboratoire d’Informatique de Paris 6, Université Pierre et Marie Curie, 4, Place Jussieu, Case 169, F-75252, Paris Cedex 05, France

    Bernadette Bouchon-Meunier

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Bloch, I., Maître, H. (1998). Fusion of Image Information under Imprecision. In: Bouchon-Meunier, B. (eds) Aggregation and Fusion of Imperfect Information. Studies in Fuzziness and Soft Computing, vol 12. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1889-5_11

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  • DOI: https://doi.org/10.1007/978-3-7908-1889-5_11

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