Minimizing variational models by means of (un)constrained optimization algorithms is a well-known approach for dealing with the image denoising problem. In this paper, we propose a modification of the widely explored TV-ROF model named H-TV-ROF, in which a penalty term based on higher order derivatives is added. A Split Bregman iterative scheme is used to solve the proposed model and its convergence is proved. The performance of the new algorithm is analized and compared with TV-ROF on a set of numerical experiments.
|Titolo:||Modification of TV-ROF denoising model based on Split Bregman iterations|
|Autori interni:||MARCELLINO, Livia|
|Data di pubblicazione:||2017|
|Rivista:||APPLIED MATHEMATICS AND COMPUTATION|
|Appare nelle tipologie:||1.1 Articolo in rivista|