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hal.structure.identifierUniversity of Cambridge [UK] [CAM]
dc.contributor.authorPARISOTTO, Simone
hal.structure.identifierMorphologie et Images [MORPHEME]
dc.contributor.authorCALATRONI, Luca
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorBUGEAU, Aurélie
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorPAPADAKIS, Nicolas
hal.structure.identifierUniversity of Cambridge [UK] [CAM]
dc.contributor.authorSCHÖNLIEB, Carola-Bibiane
dc.date.accessioned2024-04-04T02:59:31Z
dc.date.available2024-04-04T02:59:31Z
dc.date.issued2020
dc.identifier.issn1057-7149
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/192747
dc.description.abstractEnWe propose a new variational model for nonlinear image fusion. Our approach incorporates the osmosis model proposed in Vogel et al. (2013) and Weickert et al. (2013) as an energy term in a variational model. The osmosis energy is known to realize visually plausible image data fusion. As a consequence, our method is invariant to multiplicative brightness changes. On the practical side, it requires minimal supervision and parameter tuning and can encode prior information on the structure of the images to be fused. We develop a primal-dual algorithm for solving this new image fusion model and we apply the resulting minimisation scheme to multi-modal image fusion for face fusion, colour transfer and some cultural heritage conservation challenges. Visual comparison to state-of-the-art proves the quality and flexibility of our method.
dc.description.sponsorshipGeneralized Optimal Transport Models for Image processing - ANR-16-CE33-0010
dc.description.sponsorshipRepenser la post-production d'archives avec des méthodes à patch, variationnelles et par apprentissage - ANR-19-CE23-0027
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.subject.enImage fusion
dc.subject.enOsmosis filtering
dc.subject.enCultural heritage imaging
dc.subject.enPrimal-dual algorithm
dc.subject.enNon-convex optimisation
dc.title.enVariational Osmosis for Non-linear Image Fusion
dc.typeArticle de revue
dc.subject.halInformatique [cs]/Traitement du signal et de l'image
dc.identifier.arxiv1910.02012
dc.description.sponsorshipEuropeNonlocal Methods for Arbitrary Data Sources
bordeaux.journalIEEE Transactions on Image Processing
bordeaux.page5507-5516
bordeaux.volume29
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-02314972
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02314972v1
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