Table of Contents
Advances in Optical Technologies
Volume 2013, Article ID 794728, 6 pages
Research Article

Nonlocal Mean Image Denoising Using Anisotropic Structure Tensor

1Department of Electronic Engineering, Chengdu University of Information Technology, 24 Xuefu Road, Chengdu, Sichuan 610225, China
2College of Computer Science, Sichuan University, 12 Yihuan Road, Chengdu, Sichuan 610065, China

Received 24 September 2012; Accepted 3 January 2013

Academic Editor: Augusto Belendez

Copyright © 2013 Xi Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We present a novel nonlocal mean (NLM) algorithm using an anisotropic structure tensor to achieve higher accuracy of imaging denoising and better preservation of fine image details. Instead of using the intensity to identify the pixel, the proposed algorithm uses the structure tensor to characterize the boundary information around the pixel more comprehensively. Meanwhile, similarity of the structure tensor is computed in a Riemannian space for more rigorous comparison, and the similarity weight of the pixel (or patch) is determined by the intensity and structure tensor simultaneously. The proposed algorithm is compared with the original NLM algorithm and a modified NLM algorithm that is based on the principle component analysis. Quantitative and qualitative comparisons of the three NLM algorithms are presented as well.