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Bilevel Parameter Learning for Higher-Order Total Variation Regularisation Models
ArticleAbstract: We consider a bilevel optimisation approach for parameter learning in higher-order total variation iPalabras claves:Bilevel optimisation, Image quality measures, Total variation regularisersAutores:Juan Carlos De Los Reyes, Schönlieb C.B., Valkonen T.Fuentes:googlescopusBilevel approaches for learning of variational imaging models
Book PartAbstract: We review some recent learning approaches in variational imaging based on bilevel optimization and ePalabras claves:Bilevel optimization, image denoising, Supervised learning, Variational methodsAutores:Calatroni L., Chung Cao, Juan Carlos De Los Reyes, Schönlieb C.B., Valkonen T.Fuentes:scopusImage denoising: Learning the noise model via nonsmooth PDE-constrained optimization
ArticleAbstract: We propose a nonsmooth PDE-constrained optimization approach for the determination of the correct noPalabras claves:Huber regularization, image denoising, Noise distribution, PDE-constrained optimizationAutores:Juan Carlos De Los Reyes, Schönlieb C.B.Fuentes:googlescopusInfimal convolution of data discrepancies for mixed noise removal
ArticleAbstract: We consider the problem of image denoising in the presence of noise whose statistical properties arePalabras claves:Huber regularization, image denoising, Mixed noise distribution, Semismooth newton optimization, Total variation regularizationAutores:Calatroni L., Juan Carlos De Los Reyes, Schönlieb C.B.Fuentes:googlescopusLearning optimal spatially-dependent regularization parameters in total variation image denoising
ArticleAbstract: We consider a bilevel optimization approach in function space for the choice of spatially dependentPalabras claves:Bilevel optimization, optimization-based learning in imaging, PDE-constrained optimization, Schwarz domain decomposition method, Semismooth Newton methodAutores:Cao van Chung, Juan Carlos De Los Reyes, Schönlieb C.B.Fuentes:scopusLearning the Sampling Pattern for MRI
ArticleAbstract: The discovery of the theory of compressed sensing brought the realisation that many inverse problemsPalabras claves:bilevel learning, Compressed Sensing, k-space optimisation, MRI, regularisationAutores:Benning M., Ehrhardt M.J., Graves M.J., Juan Carlos De Los Reyes, Maierhofer G., Schönlieb C.B., Sherry F., Williams G.B.Fuentes:googlescopus