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A Variational Approach to Multi-Modal Image Matching

Abstract : We address the problem of non-parametric multi-modal image matching. We propose a generic framework which relies on a global variational formulation and show its versatility through three different multi-modal registration methods : supervised registration by joint intensity learning, maximization of the mutual information and maximization of the correlation ratio. Regulariz- ation is performed by using a functional borrowed from linear elasticity theory. We also consider a geometry-driven regularization method. Experiments on synthetic images and preliminary results on the realignment of MRI datasets are presented.
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https://hal.inria.fr/inria-00072513
Contributor : Rapport de Recherche Inria <>
Submitted on : Wednesday, May 24, 2006 - 10:09:29 AM
Last modification on : Thursday, February 7, 2019 - 3:50:21 PM
Long-term archiving on: : Sunday, April 4, 2010 - 11:11:15 PM

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  • HAL Id : inria-00072513, version 1

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Gerardo Hermosillo, Christophe Chefd'Hotel, Olivier Faugeras. A Variational Approach to Multi-Modal Image Matching. RR-4117, INRIA. 2001. ⟨inria-00072513⟩

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