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Sylvester Tikhonov-regularization methods in image restoration
- Source :
-
Journal of Computational & Applied Mathematics . Sep2007, Vol. 206 Issue 1, p86-98. 13p. - Publication Year :
- 2007
-
Abstract
- Abstract: 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-GMRES method which is an orthogonal projection method onto a matrix Krylov subspace. We present some theoretical results and give numerical tests in image restoration. [Copyright &y& Elsevier]
- Subjects :
- *IMAGE reconstruction
*MATRICES (Mathematics)
*TENSOR products
*UNIVERSAL algebra
Subjects
Details
- Language :
- English
- ISSN :
- 03770427
- Volume :
- 206
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Journal of Computational & Applied Mathematics
- Publication Type :
- Academic Journal
- Accession number :
- 25359083
- Full Text :
- https://doi.org/10.1016/j.cam.2006.05.028