In the framework of the numerical solution of linear systems arising from image restoration, in this paper we present an adaptive approach based on the reordering of the image approximations obtained with the Arnoldi-Tikhonov method. The reordering results in a modified regularization operator, so that the corresponding regularization can be interpreted as problem dependent. Numerical experiments are presented
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...
In the framework of the numerical solution of linear systems arising from image restoration, in this...
Image reconstruction from projections gives rise to large ill-conditioned linear systems of equation...
Image reconstruction from projections gives rise to large ill-conditioned linear systems of equation...
This paper introduces a new strategy for setting the regularization parameter when solving large-sca...
This paper introduces a new strategy for setting the regularization parameter when solving large-sca...
none3This paper introduces a new approach to computing an approximate solution of Tikhonov-regulariz...
In the framework of iterative regularization techniques for large-scale linear ill-posed problems, t...
For the solution of linear discrete ill-posed problems, in this paper we consider the Arnoldi-Tikhon...
In this paper image restoration applications where multiple distorted versions of the same original ...
For the solution of linear discrete ill-posed problems, in this paper we consider the Arnoldi-Tikhon...
In the framework of iterative regularization techniques for large-scale linear ill-posed problems, t...
In image formation, the observed images are usually blurred by optical instruments and/or transfer ...
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...
In the framework of the numerical solution of linear systems arising from image restoration, in this...
Image reconstruction from projections gives rise to large ill-conditioned linear systems of equation...
Image reconstruction from projections gives rise to large ill-conditioned linear systems of equation...
This paper introduces a new strategy for setting the regularization parameter when solving large-sca...
This paper introduces a new strategy for setting the regularization parameter when solving large-sca...
none3This paper introduces a new approach to computing an approximate solution of Tikhonov-regulariz...
In the framework of iterative regularization techniques for large-scale linear ill-posed problems, t...
For the solution of linear discrete ill-posed problems, in this paper we consider the Arnoldi-Tikhon...
In this paper image restoration applications where multiple distorted versions of the same original ...
For the solution of linear discrete ill-posed problems, in this paper we consider the Arnoldi-Tikhon...
In the framework of iterative regularization techniques for large-scale linear ill-posed problems, t...
In image formation, the observed images are usually blurred by optical instruments and/or transfer ...
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...