Bilevel Optimization Methods in Imaging


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.

Año de publicación:

2023

Keywords:

  • Bilevel optimization
  • Machine Learning
  • Variational models

Fuente:

scopusscopus

Tipo de documento:

Other

Estado:

Acceso restringido

Áreas de conocimiento:

  • Optimización matemática
  • Optimización matemática
  • Optimización matemática

Áreas temáticas de Dewey:

  • Probabilidades y matemática aplicada
  • Métodos informáticos especiales
  • Física aplicada
Procesado con IAProcesado con IA

Objetivos de Desarrollo Sostenible:

  • ODS 11: Ciudades y comunidades sostenibles
  • ODS 15: Vida de ecosistemas terrestres
  • ODS 9: Industria, innovación e infraestructura
Procesado con IAProcesado con IA