Edge detection methods based on RBF interpolation
type: Item
instance of: scholarly article
title: Edge detection methods based on RBF interpolation
zbMATH Open document ID: 1440.65026
author: Lucia Romani
author: Milvia Rossini
author: Daniela Schenone
published in: Journal of Computational and Applied Mathematics
publication date: 2019-01-24T00:00:00Z
review text: Radial basis function (in short: RBF) interpolation is a useful and popular tool for (multivariable or multivariate) function approximation. Other algorithms than interpolation are available, such as least-squares methods or quasi-interpolation, but for most applications, interpolation is the scheme of choice. In this article, edge detection methods are developed from the radial basis function spaces that are spanned by translates of a single rotationally invariant function, such as the famous multiquadric function \(\phi(r)=\sqrt{r^2+c^2}\). This multiquadric (but also other RBFs) offers an approach to the edge detection in more than one variable by the variable scale methods, where parameters such as the \(c\) in the multiquadric are adjusted in a recursive methds. Many numerical examples are given to show the usefulness of the new algorithms.
reviewed by: Martin D. Buhmann
Mathematics Subject Classification ID: 65D12
Mathematics Subject Classification ID: 65D15
Mathematics Subject Classification ID: 65D18
zbMATH DE Number: 7006449
zbMATH Keywords: signal/image analysis
zbMATH Keywords: edge detection
zbMATH Keywords: RBF interpolation
zbMATH Keywords: variably scaled kernels
zbMATH Keywords: Gibbs phenomenon
describes a project that uses: Matlab
MaRDI profile type: Publication
full work available at URL: j.cam.2018.08.006
OpenAlex ID: W2887573124
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Wikidata QID: Q129393145
DOI: 10.1016/J.CAM.2018.08.006
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description: scientific article; zbMATH DE number 7006449