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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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Submitted on : Wednesday, May 24, 2006 - 10:09:29 AM
Last modification on : Friday, February 4, 2022 - 3:16:18 AM
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  • HAL Id : inria-00072513, version 1



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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