Kronecker product approximation for the total variation regularization in image restoration

Abdeslem Hafid Bentbib, Abderrahman Bouhamidi, Karim Kreit

Abstract


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.


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References


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DOI: https://doi.org/10.52846/ami.v49i1.1511