Fast Iterative Algorithms for Total Variation Based Multiplicative Noise Removal Model
Noor Badshah · IOSR Journal of Mathematics · 2012
This paper presents fast iterative algorithms for solution of PDEs arisen from minimization of multiplicative noise removal model [14].This model may be regarded as an improved version of the Total Variation (TV) de-noising models.For the TV and the multiplicative noise removal models, their associated Euler-Lagrange equations are highly nonlinear Partial Differential Equations (PDEs).For this model a very slow explicit time marching method has been reported.The main contribution we present in this paper is the implementation of the fixed point, semi-implicit and additive operator splitting schemes which do not yield good results.Consequently a fast and efficient multi-grid method with AOS as smoother is developed.Numerical experiments are presented to show the good performance of the fast multi-grid algorithm.