Authors:
Marcella Matrecano
;
Giovanni Poggi
and
Luisa Verdoliva
Affiliation:
University of Naples Federico II, Italy
Keyword(s):
Denoising, Correlated Noise, Nonlocal Filtering, BM3D.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
Abstract:
Most of the literature on denoising focuses on the additive-white-gaussian-noise (AWGN) model. However, in many important applicative fields, images are typically affected by non-Gaussian and/or colored noise, in which cases AWGN-based techniques fall much short of their promises. In this paper, we propose a new denoising technique for correlated noise based on the non-local approach. We start from the well-known BM3D algorithm, which can be considered to be the state of the art in AWGN denoising, and modify it in various critical steps in order to take into account the non-whiteness of noise. Experimental results on several test images corrupted by correlated noise confirm the potential of the proposed technique.