On the ROF Model in Rectilinear Anisotropy: Piecewise Constant Approximation and Universal Minimality

Fuente: arXiv
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Main Authors: Kirisits, Clemens, Setterqvist, Eric
Format: Preprint
Published: 2019
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author Kirisits, Clemens
Setterqvist, Eric
author_facet Kirisits, Clemens
Setterqvist, Eric
contents We prove that the $L^2$ distance between the minimizer of the $\ell^1$-anisotropic Rudin-Osher-Fatemi (ROF) functional and its minimizer over the space of piecewise constant functions on a rectilinear grid is $\mathcal{O}(h^{\frac12 - \frac{q'}{2q}})$, where $h$ is the grid's mesh size and the datum belongs to $L^q$, $q \ge 2$. These convergence rates are valid in any dimension $d\ge 1$. However, in dimension $d = 1$ they can be further improved to $\mathcal{O}(h^{\frac12 - \frac{1}{2q}})$. To establish the error bounds, $L^q$ estimates of the ROF minimizer in terms of the datum are critical. Such estimates are particular cases of a universal minimality property of the ROF minimizer derived in the second part of the paper. There it is shown, in both the finite-dimensional and infinite-dimensional settings, that the minimizer simultaneously minimizes a broad class of convex functionals over a neighbourhood of the datum arising in the convex dual of the ROF problem. This extends previous results of similar type about taut strings and the ROF problem.
format Preprint
id arxiv_https___arxiv_org_abs_1910_05186
institution arXiv
publishDate 2019
record_format arxiv
spellingShingle On the ROF Model in Rectilinear Anisotropy: Piecewise Constant Approximation and Universal Minimality
Kirisits, Clemens
Setterqvist, Eric
Optimization and Control
46N10, 65D18, 65K99, 65N15, 68U10, 92C55
We prove that the $L^2$ distance between the minimizer of the $\ell^1$-anisotropic Rudin-Osher-Fatemi (ROF) functional and its minimizer over the space of piecewise constant functions on a rectilinear grid is $\mathcal{O}(h^{\frac12 - \frac{q'}{2q}})$, where $h$ is the grid's mesh size and the datum belongs to $L^q$, $q \ge 2$. These convergence rates are valid in any dimension $d\ge 1$. However, in dimension $d = 1$ they can be further improved to $\mathcal{O}(h^{\frac12 - \frac{1}{2q}})$. To establish the error bounds, $L^q$ estimates of the ROF minimizer in terms of the datum are critical. Such estimates are particular cases of a universal minimality property of the ROF minimizer derived in the second part of the paper. There it is shown, in both the finite-dimensional and infinite-dimensional settings, that the minimizer simultaneously minimizes a broad class of convex functionals over a neighbourhood of the datum arising in the convex dual of the ROF problem. This extends previous results of similar type about taut strings and the ROF problem.
title On the ROF Model in Rectilinear Anisotropy: Piecewise Constant Approximation and Universal Minimality
topic Optimization and Control
46N10, 65D18, 65K99, 65N15, 68U10, 92C55
url https://arxiv.org/abs/1910.05186