A residual-based kernel regression method for image denoising

Jiefei Wang, Yupeng Chen, Tao Li, Jian Lu, Lixin Shen

Abstract: In this paper, 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.

Journal: Mathematical Problems in Engineering, 2016

URL: http://www.hindawi.com/journals/mpe/aip/245639/