Abstract
AbstractA bilevel training scheme is used to introduce a novel class of regularizers, providing a unified approach to standard regularizers$$TGV^2$$TGV2and$$NsTGV^2$$NsTGV2. Optimal parameters and regularizers are identified, and the existence of a solution for any given set of training imaging data is proved by$$\Gamma $$Γ-convergence under a conditional uniform bound on the trace constant of the operators and a finite-null-space condition. Some first examples and numerical results are given.
Funder
Austrian Science Fund
BMBWF
National Science Foundation
Engineering and Physical Sciences Research Council
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,General Engineering,Modeling and Simulation
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