An optimal fluid optical flow registration for super-resolution with Lamé parameters learning
From MaRDI portal
Publication:6161545
DOI10.1007/s10957-023-02186-4OpenAlexW4365999509MaRDI QIDQ6161545
Aissam Hadri, Lekbir Afraites, A. El Hakoume, Amine Laghrib
Publication date: 27 June 2023
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10957-023-02186-4
Convex programming (90C25) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
Cites Work
- Unnamed Item
- A first-order primal-dual algorithm for convex problems with applications to imaging
- A multi-frame super-resolution using diffusion registration and a nonlocal variational image restoration
- Template-based image reconstruction from sparse tomographic data
- A new multiframe super-resolution based on nonlinear registration and a spatially weighted regularization
- A combined first and second order variational approach for image reconstruction
- Non-local regularization of inverse problems
- A nonlinear fourth-order PDE for multi-frame image super-resolution enhancement
- Solving inverse optimal control problems via value functions to global optimality
- An edge preserving high-order PDE for multiframe image super-resolution
- The Split Bregman Method for L1-Regularized Problems
- Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
- Analysis of Discrete Ill-Posed Problems by Means of the L-Curve
- The Use of the L-Curve in the Regularization of Discrete Ill-Posed Problems
- Image Super-Resolution Based on Structure-Modulated Sparse Representation
- A bilevel approach for parameter learning in inverse problems
- Optimal Control Formulation for Determining Optical Flow
- A bilevel learning approach for optimal observation placement in variational data assimilation
- Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution
- Primal-Dual Extragradient Methods for Nonlinear Nonsmooth PDE-Constrained Optimization
- Joint Learning for Single-Image Super-Resolution via a Coupled Constraint
- Single Image Super-Resolution With Non-Local Means and Steering Kernel Regression
This page was built for publication: An optimal fluid optical flow registration for super-resolution with Lamé parameters learning
