This paper surveys an important class of methods that combine iterative projection methods
and variational regularization methods for large-scale inverse problems. Iterative methods …

In the framework of large-scale linear discrete ill-posed problems, Krylov projection methods
represent an essential tool since their development, which dates back to the early 1950's. In …

Large‐scale linear systems coming from suitable discretizations of linear inverse problems
are challenging to solve. Indeed, since they are inherently ill‐posed, appropriate …

This paper proposes a new approach to image and video restoration. This approach
constructs a degradation model based on a tensor representation, where a color image is …

GMRES is one of the most popular iterative methods for the solution of large linear systems
of equations that arise from the discretization of linear well-posed problems, such as …

Iterative hybrid projection methods have proven to be very effective for solving large linear
inverse problems due to their inherent regularizing properties as well as the added flexibility …

The symmetric Lanczos method is commonly applied to reduce large‐scale symmetric linear
discrete ill‐posed problems to small ones with a symmetric tridiagonal matrix. We investigate …

This paper proposes a new approach for choosing the regularization parameters in multi-
parameter regularization methods when applied to approximate the solution of linear …

When projection methods are employed to regularize linear discrete ill-posed problems, one
implicitly assumes that the discrete Picard condition (DPC) is somehow inherited by the …

In this paper we study some properties of the classical Arnoldi-based methods for solving
infinite dimensional linear equations involving compact operators. These problems are …