<div class="csl-bib-body">
<div class="csl-entry">Davoli, E., Fonseca, I., & Liu, P. (2023). Adaptive Image Processing: First Order PDE Constraint Regularizers and a Bilevel Training Scheme. <i>Journal of Nonlinear Science</i>, <i>33</i>(3), Article 41. https://doi.org/10.1007/s00332-023-09902-4</div>
</div>
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dc.identifier.issn
0938-8974
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/191003
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dc.description.abstract
A bilevel training scheme is used to introduce a novel class of regularizers, providing a unified approach to standard regularizers TGV² and NsTGV². Optimal parameters and regularizers are identified, and the existence of a solution for any given set of training imaging data is proved by 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.
en
dc.description.sponsorship
FWF - Österr. Wissenschaftsfonds
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dc.description.sponsorship
FWF - Österr. Wissenschaftsfonds
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dc.description.sponsorship
FWF - Österr. Wissenschaftsfonds
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dc.language.iso
en
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dc.publisher
SPRINGER
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dc.relation.ispartof
Journal of Nonlinear Science
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Γ-convergence
en
dc.subject
First order differential operators
en
dc.subject
Image processing
en
dc.subject
Optimal training scheme
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dc.title
Adaptive Image Processing: First Order PDE Constraint Regularizers and a Bilevel Training Scheme
