A multigrid method for total variation-based image denoising. (English) Zbl 0831.93062
Bowers, K. L. (ed.) et al., Computation and control IV. Proceedings of the fourth Bozeman conference, Bozeman, Montana, MT, USA, August 3-9, 1994. Boston, MA: Birkhäuser. Prog. Syst. Control Theory. 20, 323-331 (1995).
Image reconstruction with noise removal, or denoising, is considered. In order to overcome the problems for non-smooth solutions, a least squares- constrained total variation minimization method is applied. Then a penalty method is used for the minimization. In order to overcome the difficulties associated with poorly behaved diffusion coefficients, the author applied a cell-centered finite difference discretization.
Then a variant of the multigrid algorithm introduced by Ewing and Shen is used to solve the resulting discrete linear system. A unique feature of this multigrid algorithm is the use of nonstandard transfer operators.
For the entire collection see [Zbl 0819.00052].
Then a variant of the multigrid algorithm introduced by Ewing and Shen is used to solve the resulting discrete linear system. A unique feature of this multigrid algorithm is the use of nonstandard transfer operators.
For the entire collection see [Zbl 0819.00052].
Reviewer: W.Heinrichs (Düsseldorf)
MSC:
| 93E11 | Filtering in stochastic control theory |
| 93E14 | Data smoothing in stochastic control theory |
| 65M55 | Multigrid methods; domain decomposition for initial value and initial-boundary value problems involving PDEs |
