自适应图像处理：一阶偏微分方程约束正则化器与双层训练方案
Adaptive Image Processing: First Order PDE Constraint Regularizers and a Bilevel Training Scheme.
作者信息
Davoli Elisa, Fonseca Irene, Liu Pan
机构信息
Institute of Analysis and Scientific Computing, TU Wien, Wiedner Hauptstrasse 8-10, 1040 Vienna, Austria.
Department of Mathematics, Center of Nonlinear Analysis, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 USA.
出版信息
J Nonlinear Sci. 2023;33(3):41. doi: 10.1007/s00332-023-09902-4. Epub 2023 Mar 3.
A bilevel training scheme is used to introduce a novel class of regularizers, providing a unified approach to standard regularizers and . Optimal parameters and regularizers are identified, and the existence of a solution for any given set of training imaging data is proved by -convergence under a conditional uniform bound on the trace constant of the operators and a finite-null-space condition. Some first examples and numerical results are given.
采用一种双层训练方案来引入一类新型正则化器，为标准正则化器提供了一种统一的方法。确定了最优参数和正则化器，并在算子迹常数的条件一致有界和有限零空间条件下，通过Γ收敛证明了对于任何给定的一组训练成像数据都存在解。给出了一些初步示例和数值结果。
Zotero 插件