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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 5245948, 13 pages
http://dx.doi.org/10.1155/2016/5245948
Research Article

A Residual-Based Kernel Regression Method for Image Denoising

1College of Mathematics and Statistics, Shenzhen University, Shenzhen 518060, China
2Department of Mathematics, Syracuse University, Syracuse, NY 13244, USA

Received 7 October 2015; Revised 4 January 2016; Accepted 18 January 2016

Academic Editor: Kacem Chehdi

Copyright © 2016 Jiefei Wang 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.

Abstract

We propose a residual-based method for denoising images corrupted by Gaussian noise. In the method, by combining bilateral filter and structure adaptive kernel filter together with the use of the image residuals, the noise is suppressed efficiently while the fine features, such as edges, of the images are well preserved. Our experimental results show that, in comparison with several traditional filters and state-of-the-art denoising methods, the proposed method can improve the quality of the restored images significantly.