Title
On a nonlinear multigrid algorithm with primal relaxation for the image total variation minimisation
Abstract
Digital image restoration has drawn much attention in the recent years and a lot of research has been done on effective variational partial differential equation models and their theoretical studies. However there remains an urgent need to develop fast and robust iterative solvers, as the underlying problem sizes are large. This paper proposes a fast multigrid method using primal relaxations. The basic primal relaxation is known to get stuck at a ‘local’ non-stationary minimum of the solution, which is usually believed to be ‘non-smooth’. Our idea is to utilize coarse level corrections, overcoming the deadlock of a basic primal relaxation scheme. A further refinement is to allow non-regular coarse levels to correct the solution, which helps to improve the multilevel method. Numerical experiments on both 1D and 2D images are presented.
Year
DOI
Venue
2006
10.1007/s11075-006-9020-z
Numerical Algorithms
Keywords
Field
DocType
image restoration,nonlinear solvers,primal relaxation,regularisation,total variation,68U10,65F10,65K10
Mathematical optimization,Nonlinear multigrid,Mathematical analysis,Deadlock,Relaxation (iterative method),Algorithm,Digital image,Minimisation (psychology),Image restoration,Partial differential equation,Mathematics,Multigrid method
Journal
Volume
Issue
ISSN
41
4
1017-1398
Citations 
PageRank 
References 
12
0.70
15
Authors
2
Name
Order
Citations
PageRank
Tony F. Chan18733659.77
Ke Chen226827.05