Using Randomized Nystrom Preconditioners to Accelerate Variational Image Reconstruction.

ABSTRACT: Model-based iterative reconstruction plays a key role in solving inverse problems. However, the associated minimization problems are generally large-scale, nonsmooth, and sometimes even nonconvex, which present challenges in designing efficient iterative solvers. Preconditioning methods can significantly accelerate the convergence of iterative methods. In some applications, computing preconditioners on-the-fly is beneficial. Moreover, forward models in image reconstruction are typically represented as operators, and the corresponding explicit matrices are often unavailable, which brings additional challenges in designing preconditioners. Therefore, for practical use, computing and applying preconditioners should be computationally inexpensive. This paper adapts the randomized Nyström appro

SUBMITTER: Hong T 

PROVIDER: S-EPMC12685022 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature