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Communication Dans Un Congrès Année : 2023

Learned Discretization Schemes for the Second-Order Total Generalized Variation

Résumé

The total generalized variation extends the total variation by incorporating higher-order smoothness. Thus, it can also suffer from similar discretization issues related to isotropy. Inspired by the success of novel discretization schemes of the total variation, there has been recent work to improve the second-order total generalized variation discretization, based on the same design idea. In this work, we propose to extend this to a general discretization scheme based on interpolation filters, for which we prove variational consistency. We then describe how to learn these interpolation filters to optimize the discretization for various imaging applications. We illustrate the performance of the method on a synthetic data set as well as for natural image denoising.

Dates et versions

hal-04239970 , version 1 (12-10-2023)

Identifiants

Citer

Lea Bogensperger, Antonin Chambolle, Alexander Effland, Thomas Pock. Learned Discretization Schemes for the Second-Order Total Generalized Variation. 9th International Conference on Scale Space and Variational Methods in Computer Vision. SSVM 2023, Università di Bologna, Italie, May 2023, Santa Margherita di Pula (Cagliari), Italy. pp.484-497, ⟨10.1007/978-3-031-31975-4_37⟩. ⟨hal-04239970⟩
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