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hal.structure.identifierMathématiques Appliquées Paris 5 [MAP5 - UMR 8145]
dc.contributor.authorGALERNE, B.
hal.structure.identifierCentre de Mathématiques et de Leurs Applications [CMLA]
dc.contributor.authorLECLAIRE, Arthur
hal.structure.identifierMathématiques Appliquées Paris 5 [MAP5 - UMR 8145]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorMOISAN, L.
dc.date.accessioned2024-04-04T03:10:51Z
dc.date.available2024-04-04T03:10:51Z
dc.date.created2016-03-16
dc.date.issued2017-01-19
dc.identifier.issn0167-7055
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193721
dc.description.abstractEnDesigning realistic noise patterns from scratch is hard. To solve this problem, recent contributions have proposed involved spectral analysis algorithms that enable procedural noise models to faithfully reproduce some class of textures. The aim of this paper is to propose the simplest and most efficient noise model that allows for the reproduction of any Gaussian texture. Texton noise is a simple sparse convolution noise that sums randomly scattered copies of a small bilinear texture called texton. We introduce an automatic algorithm to compute the texton associated with an input texture image that concentrates the input frequency content into the desired texton support. One of the main features of texton noise is that its evaluation only consists to sum thirty texture fetches on average. Consequently texton noise generates Gaussian textures with an unprecedented evaluation speed for noise by example. A second main feature of texton noise is that it allows for high quality on-the-fly anisotropic filtering by simply invoking existing GPU hardware solutions for texture fetches. In addition, we demonstrate that texton noise can be applied on any surface using parameterization-free surface noise and that it allows for noise mixing.
dc.language.isoen
dc.publisherWiley
dc.subject.enprocedural noise
dc.subject.ennoise by example
dc.subject.entexton
dc.subject.enGaussian texture
dc.subject.enantialiasing
dc.subject.ennoise mixing
dc.title.enTexton Noise
dc.typeArticle de revue
dc.identifier.doi10.1111/cgf.13073
dc.subject.halInformatique [cs]/Synthèse d'image et réalité virtuelle [cs.GR]
bordeaux.journalComputer Graphics Forum
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01299336
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01299336v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Computer%20Graphics%20Forum&rft.date=2017-01-19&rft.eissn=0167-7055&rft.issn=0167-7055&rft.au=GALERNE,%20B.&LECLAIRE,%20Arthur&MOISAN,%20L.&rft.genre=article


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