Analytical Approximations for Nonlinear Diffusion Time in Multiscale Edge Enhancement

Platero Dueñas, Carlos ORCID: https://orcid.org/0000-0003-3712-8297, Sanguino Botella, Fco. Javier ORCID: https://orcid.org/0000-0002-9203-101X, Tobar Puente, M. del Carmen ORCID: https://orcid.org/0000-0002-7370-6835, Poncela Pardo, José Manuel and Asensio Madrid, Gabriel ORCID: https://orcid.org/0000-0001-9108-0840 (2009). Analytical Approximations for Nonlinear Diffusion Time in Multiscale Edge Enhancement. En: "4th International Conference on Computer Vision Theory and Applications", 5-8 febrero, 2009, Lisboa, Portugal. pp. 78-81. https://doi.org/https://www.scitepress.org/Papers/2009/17892/17892.pdf.

Descripción

Título: Analytical Approximations for Nonlinear Diffusion Time in Multiscale Edge Enhancement
Autor/es:
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 4th International Conference on Computer Vision Theory and Applications
Fechas del Evento: 5-8 febrero, 2009
Lugar del Evento: Lisboa, Portugal
Título del Libro: Proceedings of the Fourth International Conference on Computer Vision Theory and Applications
Fecha: 12 Octubre 2009
Volumen: 1
Materias:
ODS:
Palabras Clave Informales: Anisotropic Diffusion; Multiscale edge enhancement; nonlinear diffusion filter; Regularization; Schemes; Segmentation; WAVELET SHRINKAGE
Escuela: E.T.S.I. Diseño Industrial (UPM)
Departamento: Ingeniería Eléctrica, Electrónica Automática y Física Aplicada
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The image simplification, noise elimination and edge enhancement steps are all fundamental to segmentation tasks. These processing techniques usually require the tuning of their control parameters; a procedure known to be incompatible with automatic segmentation. The aim of this paper is to adopt a procedure, based on nonlinear diffusion, that is capable of auto tuning by means of analytical expressions that relate diffusion times to the gradient module. The numerical method and experimental results are shown in 1D, 2D and 3D.

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ID de Registro: 94618
Identificador DC: https://oa.upm.es/94618/
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URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/5510505
Identificador DOI: https://www.scitepress.org/Papers/2009/17892/17892.pdf
URL Oficial: https://api.elsevier.com/content/abstract/scopus_i...
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