# Sylvester Tikhonov-regularization methods in image restoration

@inproceedings{Bouhamidi2007SylvesterTM, title={Sylvester Tikhonov-regularization methods in image restoration}, author={Abderrahman Bouhamidi and Khalide Jbilou}, year={2007} }

- Published 2007

In this paper, we consider large-scale linear discrete ill-posed problems where the right-hand side contains noise. Regularization techniques such as Tikhonov regularization are needed to control the effect of the noise on the solution. In many applications such as in image restoration the coefficient matrix is given as a Kronecker product of two matrices and then Tikhonov regularization problem leads to the generalized Sylvester matrix equation. For large-scale problems, we use the global… CONTINUE READING

#### From This Paper

##### Figures, tables, and topics from this paper.

#### Citations

##### Publications citing this paper.

Showing 1-10 of 27 extracted citations

## Preconditioning Toeplitz-plus-diagonal linear systems using the Sherman-Morrison-Woodbury formula

View 5 Excerpts

Highly Influenced

## Fully fuzzy Sylvester matrix equation

View 1 Excerpt

#### References

##### Publications referenced by this paper.

Showing 1-10 of 33 references

## Regularization of incorrectly posed problems

View 11 Excerpts

Highly Influenced

## Matrix computations (3. ed.)

View 3 Excerpts

Highly Influenced

## Algebraic Riccati equations

View 1 Excerpt

## Gmres , L-curves , and Discrete Ill-posed Problems ∗

View 1 Excerpt

## Tikhonov regularization and the L-curve for large discrete ill-posed problems

View 1 Excerpt

## Estimation of the L-curve via Lanczos bidiagonalization

View 1 Excerpt

## Generalized cross - validation as a method for choosing a good ridge parameter

## Global FOM and GMRES algorithms for matrix equations, Appl

View 2 Excerpts