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Frontiers of Computer Science

, Volume 9, Issue 5, pp 713–719 | Cite as

A statistical learning based image denoising approach

  • Ke Tu
  • Hongbo LiEmail author
  • Fuchun Sun
Research Article
  • 118 Downloads

Abstract

The image denoising is a very basic but important issue in the field of image procession. Most of the existing methods addressing this issue only show desirable performance when the image complies with their underlying assumptions. Especially, when there is more than one kind of noises, most of the existing methods may fail to dispose the corresponding image. To address this problem, we propose a two-step image denoising method motivated by the statistical learning theory. Under the proposed framework, the type and variance of noise are estimated with support vector machine (SVM) first, and then this information is employed in the proposed denoising algorithm to further improve its denoising performance. Finally, comparative study is constructed to demonstrate the advantages and effectiveness of the proposed method.

Keywords

SVM image denosing multiple noises 

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Copyright information

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Department of Computer Science and Technology, State Key Laboratory of Intelligent Technology and SystemsTsinghua UniversityBeijingChina

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