Median filter method for mean curvature flow using a random Jacobi algorithm

Fuente: arXiv
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Auteurs principaux: Ullrich, Anton, Laux, Tim
Format: Preprint
Publié: 2024
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author Ullrich, Anton
Laux, Tim
author_facet Ullrich, Anton
Laux, Tim
contents We present an efficient scheme for level set mean curvature flow using a domain discretization and median filters. For this scheme, we show convergence in $L^\infty$-norm under mild assumptions on the number of points in the discretization. In addition, we strengthen the weak convergence result for the MBO thresholding scheme applied to data clustering of Lelmi and one of the authors. This is done through a strong convergence of the discretized heat flow in the optimal regime. Different boundary conditions are also discussed.
format Preprint
id arxiv_https___arxiv_org_abs_2410_07776
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Median filter method for mean curvature flow using a random Jacobi algorithm
Ullrich, Anton
Laux, Tim
Analysis of PDEs
Numerical Analysis
53E10 (Primary), 35D40, 60D05 (Secondary)
We present an efficient scheme for level set mean curvature flow using a domain discretization and median filters. For this scheme, we show convergence in $L^\infty$-norm under mild assumptions on the number of points in the discretization. In addition, we strengthen the weak convergence result for the MBO thresholding scheme applied to data clustering of Lelmi and one of the authors. This is done through a strong convergence of the discretized heat flow in the optimal regime. Different boundary conditions are also discussed.
title Median filter method for mean curvature flow using a random Jacobi algorithm
topic Analysis of PDEs
Numerical Analysis
53E10 (Primary), 35D40, 60D05 (Secondary)
url https://arxiv.org/abs/2410.07776