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Publicaciones

Bilevel Optimization Methods in Imaging

Authors

Carlos De los Reyes, Juan , VILLACIS PROAÑO, DAVID ALEJANDRO, Chen, K , Schonlieb, CB , Tai, XC , Younes, L

External publication

No

Means

Handbook Of Mathematical Models And Algorithms In Computer Vision And Imaging: Mathematical Imaging And Vision

Scope

Capítulo de un Libro

Nature

Científica

JCR Quartile

0

SJR Quartile

0

Publication date

01/01/2022

ISI

001071202000025

Abstract

Optimization techniques have been widely used for image restoration tasks, as many imaging problems may be formulated as minimization ones with the recovered image as the target minimizer. Recently, novel optimization ideas also entered the scene in combination with machine learning approaches, to improve the reconstruction of images by optimally choosing different parameters/functions of interest in the models. This chapter provides a review of the latest developments concerning the latter, with special emphasis on bilevel optimization techniques and their use for learning local and nonlocal image restoration models in a supervised manner. Moreover, the use of related optimization ideas within the development of neural networks in imaging will be briefly discussed.

Keywords

Bilevel optimization; Machine learning; Variational models

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