Learning optimal spatially-dependent regularization parameters in total variation image denoising

From MaRDI portal
Publication:5348007

DOI10.1088/1361-6420/33/7/074005zbMath1371.49018arXiv1603.09155OpenAlexW2963683570MaRDI QIDQ5348007

Carola-Bibiane Schönlieb, Juan Carlos De Los Reyes, Cao Van Chung

Publication date: 11 August 2017

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1603.09155




Related Items

Locally adaptive total variation for removing mixed Gaussian–impulse noiseA high order PDE-constrained optimization for the image denoising problemOptimality Conditions for Bilevel Imaging Learning Problems with Total Variation RegularizationBilevel Training Schemes in Imaging for Total Variation--Type Functionals with Convex IntegrandsSpatially adapted first and second order regularization for image reconstruction: from an image surface perspectiveAn improved bilevel optimization approach for image super-resolution based on a fractional diffusion tensorDualization and Automatic Distributed Parameter Selection of Total Generalized Variation via Bilevel OptimizationPreface for Inverse Problems special issue on learning and inverse problemsBilevel Imaging Learning Problems as Mathematical Programs with Complementarity Constraints: Reformulation and TheoryLearning Regularization Parameter-Maps for Variational Image Reconstruction Using Deep Neural Networks and Algorithm UnrollingOn and Beyond Total Variation Regularization in Imaging: The Role of Space VarianceParameter space study of optimal scale-dependent weights in TV image denoisingAn adaptive finite element method for distributed elliptic optimal control problems with variable energy regularizationStructural changes in nonlocal denoising models arising through bi-level parameter learningDeep Learning for Trivial Inverse ProblemsMaximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach Part I: Methodology and ExperimentsAutomated parameter selection for total variation minimization in image restorationGradient-Based Solution Algorithms for a Class of Bilevel Optimization and Optimal Control Problems with a Nonsmooth Lower LevelModern regularization methods for inverse problemsSolving inverse problems using data-driven modelsAn optimal bilevel optimization model for the generalized total variation and anisotropic tensor parameters selection



Cites Work