p-Laplace diffusion for distance function estimation, optimal transport approximation, and image enhancement

Pierre-Alain Fayolle; Alexander G. Belyaev

doi:10.1016/j.cagd.2018.09.003

p-Laplace diffusion for distance function estimation, optimal transport approximation, and image enhancement

Pierre-Alain Fayolle, Alexander G. Belyaev

School of Engineering & Physical Sciences

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

172 Downloads (Pure)

Abstract

In this paper, we propose ADMM-based numerical schemes for power-law diffusion equations involving the p-Laplacian div(|∇u|^p−2∇u) with constant (p=const) and variable (p=p(x)) exponents. Applications to distance function and optimal transport approximations (p is large and constant) and image enhancement (p is small and variable) are considered.

Original language	English
Pages (from-to)	1-20
Number of pages	20
Journal	Computer Aided Geometric Design
Volume	67
Early online date	19 Sept 2018
DOIs	https://doi.org/10.1016/j.cagd.2018.09.003
Publication status	Published - Dec 2018

Keywords

Distance function estimation
Image enhancement
Optimal transport approximation
p-Laplacian
Power-law diffusion

ASJC Scopus subject areas

Modelling and Simulation
Automotive Engineering
Aerospace Engineering
Computer Graphics and Computer-Aided Design

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10.1016/j.cagd.2018.09.003

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Cite this

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title = "p-Laplace diffusion for distance function estimation, optimal transport approximation, and image enhancement",

abstract = "In this paper, we propose ADMM-based numerical schemes for power-law diffusion equations involving the p-Laplacian div(|∇u|p−2∇u) with constant (p=const) and variable (p=p(x)) exponents. Applications to distance function and optimal transport approximations (p is large and constant) and image enhancement (p is small and variable) are considered.",

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AU - Fayolle, Pierre-Alain

AU - Belyaev, Alexander G.

PY - 2018/12

Y1 - 2018/12

N2 - In this paper, we propose ADMM-based numerical schemes for power-law diffusion equations involving the p-Laplacian div(|∇u|p−2∇u) with constant (p=const) and variable (p=p(x)) exponents. Applications to distance function and optimal transport approximations (p is large and constant) and image enhancement (p is small and variable) are considered.

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KW - Distance function estimation

KW - Image enhancement

KW - Optimal transport approximation

KW - p-Laplacian

KW - Power-law diffusion

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ER -

p-Laplace diffusion for distance function estimation, optimal transport approximation, and image enhancement

Abstract

Keywords

ASJC Scopus subject areas

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Alexander Belyaev

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p-Laplace diffusion for distance function estimation, optimal transport approximation, and image enhancement

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

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Alexander Belyaev

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