A Residual-Based Kernel Regression Method for Image Denoising

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

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


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.

Original languageEnglish (US)
Article number5245948
JournalMathematical Problems in Engineering
StatePublished - 2016

ASJC Scopus subject areas

  • General Mathematics
  • General Engineering


Dive into the research topics of 'A Residual-Based Kernel Regression Method for Image Denoising'. Together they form a unique fingerprint.

Cite this