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Article Dans Une Revue Journal of Mathematical Modeling Année : 2022

Discrete cosine transform LSQR methods for multidimensional ill-posed problems

Mohamed El Guide
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Alaa El Ichi
  • Fonction : Auteur

Résumé

We propose new tensor Krylov subspace methods for ill-posed linear tensor problems such as color or video image restoration. Those methods are based on the tensor-tensor discrete cosine transform that gives fast tensor-tensor product computations. In particular, we will focus on the tensor discrete cosine versions of GMRES, Golub-Kahan bidiagonalisation and LSQR methods. The presented numer- ical tests show that the methods are very fast and give good accuracies when solving some linear tensor ill-posed problems.
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Dates et versions

hal-04413522 , version 1 (23-01-2024)

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  • HAL Id : hal-04413522 , version 1

Citer

Mohamed El Guide, Alaa El Ichi, Khalide Jbilou. Discrete cosine transform LSQR methods for multidimensional ill-posed problems. Journal of Mathematical Modeling, 2022, 10 (1), pp.21-37. ⟨hal-04413522⟩
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