Authors:
Haijuan Hu
1
;
Bing Li
2
and
Quansheng Liu
1
Affiliations:
1
Université de Bretagne-Sud, France
;
2
Zhongshan Polytechnic, China
Keyword(s):
Gaussian Noise, Impulse Noise, Mixed Noise, Image Restoration, Denoising, Trilateral Filter, Non-local Means Filter, Law of Large Numbers, Central Limit Theorem.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
Abstract:
In this paper we first present two convergence theorems which give a theoretical justification of the Non-Local Means Filter. Based on these theorems, we propose a new filter, called Non-Local Mixed Filter, to remove a mixture of Gaussian and random impulse noises. This filter combines the essential ideas of the Trilateral Filter and the Non-Local Means Filter. It improves the Trilateral Filter and extends the Non-Local Means Filter. Our experiments show that the new filter generally outperforms two other recent proposed methods. A careful discussion and simple formulas are given for the choice of parameters for the proposed filter.