Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. Bridging Compression to Wavelet Thresholding as a Denoising Method
 
conference paper

Bridging Compression to Wavelet Thresholding as a Denoising Method

Chang, S. Grace
•
Yu, Bin
•
Vetterli, Martin  
1997
Proceedings Conference on Information Sciences and Systems
Conference on Information Sciences and Systems

Some past work has suggested that lossy compression can be a good denoising tool. Building on this theme, we make the connection that quantization of transform coefficients approximates the operation of Donoho-Johnstone's wavelet thresholding, to conclude that compression (via coefficient quantization) is appropriate for filtering noise from signal. The method of quantization is scale adaptive and is facilitated by a criterion similar to Rissanen's minimum description length principle. Results show that a small number of quantization levels achieves almost the same performance of full precision thresholding, suggesting that denoising is mainly due to the zero-zone and that the full precision of the thresheld coefficients is of secondary importance.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

cbv icss.pdf

Access type

openaccess

Size

348.7 KB

Format

Adobe PDF

Checksum (MD5)

8b6a67c50db93314184fb5580f30df65

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés