Correspondence Between Multiscale Frame Shrinkage and High-Order Nonlinear Diffusion

  • Haihui Wang*
  • , Qi Huang
  • , Bo Meng
  • *Corresponding author for this work

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

Abstract

Wavelet frame and nonlinear diffusion filters are two popular tools for signal denoising. The correspondence between Ron-Shen’s framelet and high-order nonlinear diffusion has been proved at multilevel setting. However, for the general framelet, the correspondence is established only at one level. In this paper we extend the relationship between framelet shrinkage and high-order nonlinear diffusion in Jiang (Appl Numerical Math 51–66, 2012 [19]) from one level framelet shrinkage to the multilevel framelet shrinkage setting. Subsequently, we complete the correspondence between framelet shrinkage and high-order nonlinear diffusion. Furthermore, we propose a framelet-diffused denoising method for processing the dynamic pressure signals which are generated by a transonic axial compressor. Numerical results show that our algorithm has superior noise removal ability than traditional algorithms and presents the ability in analyzing the pressure signals from an axial transonic compressor.

Original languageEnglish
Title of host publicationAnalysis and Partial Differential Equations
Subtitle of host publicationPerspectives from Developing Countries, 2016
EditorsMichael Ruzhansky, Julio Delgado, Michael Ruzhansky
PublisherSpringer New York LLC
Pages159-171
Number of pages13
ISBN (Print)9783030056568
DOIs
StatePublished - 2019
EventConference on Noncommutative Analysis and Partial Differential Equations, 2016 - London, United Kingdom
Duration: 11 Apr 201615 Apr 2016

Publication series

NameSpringer Proceedings in Mathematics and Statistics
Volume275
ISSN (Print)2194-1009
ISSN (Electronic)2194-1017

Conference

ConferenceConference on Noncommutative Analysis and Partial Differential Equations, 2016
Country/TerritoryUnited Kingdom
CityLondon
Period11/04/1615/04/16

Keywords

  • Nonlinear diffusion
  • Signal analysis
  • Wavelets

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