Kronecker product approximation for the total variation regularization in image restoration - Archive ouverte HAL
Article Dans Une Revue Annals of the University of Craiova. Mathematics and Computer Science series Année : 2022

Kronecker product approximation for the total variation regularization in image restoration

Abdeslem Hafid Bentbib
Karim Kreit

Résumé

In this paper, we propose a new algorithm to restore blurred and noisy images based on the total variation regularization, where the discrete associated Euler-Lagrange problem is solved by exploiting the structure of the matrices and transforming the initial problem to a generalized Sylvester linear matrix equation by using a special Kronecker product approximation. Afterwards, global Krylov subspace methods are used to solve the linear matrix equation. Numerical experiments are given to illustrate the effectiveness of the proposed method.

Dates et versions

hal-04359121 , version 1 (21-12-2023)

Identifiants

Citer

Abdeslem Hafid Bentbib, Abderrahman Bouhamidi, Karim Kreit. Kronecker product approximation for the total variation regularization in image restoration. Annals of the University of Craiova. Mathematics and Computer Science series, 2022, 49 (1), pp.84-98. ⟨10.52846/ami.v49i1.1511⟩. ⟨hal-04359121⟩
12 Consultations
0 Téléchargements

Altmetric

Partager

More