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dc.contributor.authorGonzález-Gutiérrez, Paulo
dc.contributor.authorGarcía, Thierry
dc.contributor.authorSpiterif, P
dc.contributor.authorTauber, Clovis
dc.date.accessioned2020-04-01T12:17:11Z
dc.date.available2020-04-01T12:17:11Z
dc.date.issued2019
dc.identifier.urihttp://repositorio.ucm.cl/handle/ucm/2680
dc.description.abstractThe present work deals with the development of a novel approach to increase the quality of 3D vector-valued (4D) images. We model the problem as a coupled anisotropic convection diffusion filtering scheme based upon local structure analysis. The orientation of the denoising and shock filtering are based upon an analysis of the local structure of the vector-valued image through a tensor that accounts for the distribution of the noise between the channels. With this approach, the noise is reduced in homogeneous regions while the vector edges are sharpened orthogonally to the flow of diffusion. We present the continuous problem and a corresponding discretization in space and time by a numerical way. Results on realistic dynamic PET image simulations illustrate the potential of the proposed method, which led to distinct improvements of figures of merit over several other approaches from the literature.es_CL
dc.language.isoenes_CL
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
dc.sourceIET Conference Publications. 10th International Conference on Pattern Recognition Systems (ICPRS-2019), 2019(CP761), 58-63es_CL
dc.subjectImage denoisinges_CL
dc.subjectMedical image processinges_CL
dc.subjectVectorses_CL
dc.subjectConvectiones_CL
dc.subjectImage filteringes_CL
dc.subjectPositron emission tomographyes_CL
dc.subjectBiodiffusiones_CL
dc.titleSimultaneous filtering and sharpening of vector-valued images with numerical schemeses_CL
dc.typeArticlees_CL
dc.ucm.indexacionScopuses_CL
dc.ucm.uridigital-library.theiet.org/content/conferences/10.1049/cp.2019.0249es_CL
dc.ucm.doidx.doi.org/10.1049/cp.2019.0249es_CL


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