Calculus of Variations and Geometric Measure Theory

J. A. Iglesias - G. Mercier

Convergence of level sets in fractional Laplacian regularization

created by iglesias on 10 Apr 2024

[BibTeX]

Published Paper

Inserted: 10 apr 2024
Last Updated: 10 apr 2024

Journal: Inverse Problems
Year: 2022
Doi: 10.1088/1361-6420/ac9805

ArXiv: 2201.13281 PDF

Abstract:

The use of the fractional Laplacian in image denoising and regularization of inverse problems has enjoyed a recent surge in popularity, since for discontinuous functions it can behave less aggressively than methods based on $H^1$ norms, while being linear and computable with fast spectral numerical methods. In this work, we examine denoising and linear inverse problems regularized with fractional Laplacian in the vanishing noise and regularization parameter regime. The clean data is assumed piecewise constant in the first case, and continuous and satisfying a source condition in the second. In these settings, we prove results of convergence of level set boundaries with respect to Hausdorff distance, and additionally convergence rates in the case of denoising and indicatrix clean data. The main technical tool for this purpose is a family of barriers constructed by Savin and Valdinoci for studying the fractional Allen-Cahn equation. To help put these fractional methods in context, comparisons with the total variation and classical Laplacian are provided throughout.