Stefan Kindermann, Lawrence Mutimbu, Elena Resmerita,
"A numerical study of heuristic parameter choice rules for total variation regularization"
, in Journal of Inverse and ill-posed Problems, 2013, ISSN: 1569-3945
Original Titel:
A numerical study of heuristic parameter choice rules for total variation regularization
Sprache des Titels:
Englisch
Original Kurzfassung:
We present a numerical study of heuristic (noiselevel-free) regularization parameter
choice rules for linear inverse problems with total variation regularization. Such
type of regularization is frequently employed in image and signal processing tasks, such as
denoising or deblurring. We review convergence results for total variation regularization
and propose some generalizations of two well-known heuristic parameter choice rules,
the quasi-optimality principle and the Hanke?Raus rules. We investigate the feasibility of
these rules using different concepts of convergence such as convergence in the Bregman
Forschungs-