Defining Belief Functions using Mathematical Morphology -- Application to Image Fusion under Imprecision

Abstract :

We address in this paper the problem of defining belief functions, typically for multi-source classification applications in image processing. We propose to use mathematical morphology for introducing imprecision in the mass and belief functions while estimating disjunctions of hypotheses. The basic idea relies on the similarity between some properties of morphological operators and properties of belief functions. The framework of mathematical morphology guarantees that the derived functions have all required properties. We illustrate the proposed approach on synthetic and real images.

Document type :
Journal articles
International Journal of Approximate Reasoning, Elsevier, 2008, 48, pp.437-465


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Submitted on : Monday, December 7, 2009 - 10:46:24 AM
Last modification on : Monday, December 7, 2009 - 11:09:49 AM

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  • HAL Id : hal-00437063, version 1

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I. Bloch. Defining Belief Functions using Mathematical Morphology -- Application to Image Fusion under Imprecision. International Journal of Approximate Reasoning, Elsevier, 2008, 48, pp.437-465. <hal-00437063>

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