Variational regularisation for inverse problems with imperfect forward operators and general noise models

Bungert L, Burger M, Korolev Y, Schönlieb CB (2020)


Publication Status: Submitted

Publication Type: Journal article

Future Publication Type: Journal article

Publication year: 2020

Journal

Book Volume: 36

Journal Issue: 12

URI: https://iopscience.iop.org/article/10.1088/1361-6420/abc531

DOI: 10.1088/1361-6420/abc531

Abstract

We study variational regularisation methods for inverse problems with imperfect forward operators whose errors can be modelled by order intervals in a partial order of a Banach lattice. We carry out analysis with respect to existence and convex duality for general data fidelity terms and regularisation functionals. Both for a priori and a posteriori parameter choice rules, we obtain convergence rates of the regularised solutions in terms of Bregman distances. Our results apply to fidelity terms such as Wasserstein distances, phiv-divergences, norms, as well as sums and infimal convolutions of those.

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APA:

Bungert, L., Burger, M., Korolev, Y., & Schönlieb, C.B. (2020). Variational regularisation for inverse problems with imperfect forward operators and general noise models. Inverse Problems, 36(12). https://doi.org/10.1088/1361-6420/abc531

MLA:

Bungert, Leon, et al. "Variational regularisation for inverse problems with imperfect forward operators and general noise models." Inverse Problems 36.12 (2020).

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