An adaptive threshold method based on the local energy of NSCT coefficients for image denoising

Xiyu Liu*, Xiaolan Yao, Xin Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this paper, we propose a new adaptive denoising method based on nonsubsampled Contourlet transform(NSCT). Traditional Wavelet provides only three directional components so that its geometrical property is not well, and Contourlet transform lacks translation invariance, therefore NSCT is developed. The proposed algorithm can adapt different thresholds on different scales and different directions. Further more, we use different thresholds in a directional subband according to local energy of NSCT coefficients to overcome the disadvantages of the unified threshold de-noising method and other fixed thresholds, which cause the image fuzzy distortion because of "over-killed". The experimental results prove that the algorithm outperforms existing schemes in both peak-signal-to-noise-ratio (PSNR) and visual quality.

Original languageEnglish
Title of host publicationProceedings of the 2012 International Conference on Communication, Electronics and Automation Engineering
PublisherSpringer Verlag
Pages279-285
Number of pages7
ISBN (Print)9783642316975
DOIs
Publication statusPublished - 2013

Publication series

NameAdvances in Intelligent Systems and Computing
Volume181 AISC
ISSN (Print)2194-5357

Keywords

  • Adaptive threshold
  • Image de-noising
  • Local energy
  • Nonsubsampled Contourlet transform
  • Translation invariance

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