Title
A new variational approach for restoring images with multiplicative noise.
Abstract
This paper proposes a novel variational model for restoration of images corrupted with multiplicative noise. It combines a fractional-order total variational filter with a high-order PDE (Laplacian) norm. The combined approach is able to preserve edges while avoiding the blocky-effect in smooth regions. This strategy minimizes a certain energy subject to a fitting term derived from a maximum a posteriori (MAP). Semi-implicit gradient descent scheme is applied to efficiently finding the minimizer of the proposed functional. To improve the numerical results, we opt for an adaptive regularization parameter selection procedure for the proposed model by using the trial-and-error method. The existence and uniqueness of a solution to the proposed variational model is established. In this study parameter dependence is also discussed. Experimental results demonstrate the effectiveness of the proposed model in visual improvement as well as an increase in the peak signal-to-noise ratio comparing to corresponding PDE methods.
Year
DOI
Venue
2016
10.1016/j.camwa.2016.03.024
Computers & Mathematics with Applications
Keywords
Field
DocType
Fractional-order total variation,High-order PDE norm,Synthetic aperture radar,Maximum a posteriori (MAP),Multiplicative noise
Uniqueness,Gradient descent,Mathematical optimization,Synthetic aperture radar,Variational model,Maximum a posteriori estimation,Adaptive regularization,Multiplicative noise,Mathematics,Laplace operator
Journal
Volume
Issue
ISSN
71
10
0898-1221
Citations 
PageRank 
References 
4
0.43
26
Authors
3
Name
Order
Citations
PageRank
Asmat Ullah151.45
W. Chen231049.17
Mushtaq Ahmad Khan351.79