Hypergraph-Based image representation

Authors:
Alain Bretto;Luc Gillibert
Affiliations:
GREYC CNRS UMR-6072, Université de Caen, Caen cedex, France;GREYC CNRS UMR-6072, Université de Caen, Caen cedex, France
Venue:
GbRPR'05 Proceedings of the 5th IAPR international conference on Graph-Based Representations in Pattern Recognition
Year:
2005

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Abstract

An appropriate image representation induces some good image treatment algorithms. Hypergraph theory is a theory of finite combinatorial sets, modeling a lot of problems of operational research and combinatorial optimization. Hypergraphs are now used in many domains such as chemistry, engineering and image processing. We present an overview of a hypergraph-based picture representation giving much application in picture manipulation, analysis and restoration: the Image Adaptive Neighborhood Hypergraph (IANH). With the IANH it is possible to build powerful noise detection an elimination algorithm, but also to make some edges detection or some image segmentation. IANH has various applications and this paper presents a survey of them.