4 papers
Iterated graph Laplacian for image restoration problems
Stefano Aleotti, Davide Bianchi, Florian Bossmann +2
We study the graph Laplacian operator as a regularizer in a generalized Tikhonov framework for linear ill-posed problems. The Laplacian is updated iteratively from the current reco…
Multilevel Preconditioning Strategies for Convex Optimization Methods in Image Deblurring
Stefano Aleotti, Claudia Binda, Marco Donatelli +1
Proximal gradient methods are widely used in imaging, and their speed of convergence can be accelerated by incorporating variable metrics and/or extrapolation steps. Recent works h…
Trust-Region Methods with Low-Fidelity Objective Models
Andrea Angino, Matteo Aurina, Alena Kopaničáková +3
We introduce two multifidelity trust-region methods based on the Magical Trust Region (MTR) framework. MTR augments the classical trust-region step with a secondary, informative di…
A Preconditioned Version of a Nested Primal-Dual Algorithm for Image Deblurring
Stefano Aleotti, Marco Donatelli, Rolf Krause +1
Variational models for image deblurring problems typically consist of a smooth term and a potentially non-smooth convex term. A common approach to solving these problems is using p…