Wavelet singularity detection for image processing

Pak Kong Lun, Tai Chiu Hsung, Yuk Fan Ho

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)


The idea of wavelet singularity detection (WSD) can be traced back to the work of Jaffard. He showed that the local regularity of an n-dimensional signal (which is measured through its Lipschitz exponent) can be estimated by analyzing its n+1-dimensional scale-space. Mallat further showed that the Lipschitz exponent of a singularity can be estimated by tracing its wavelet transform modulus maxima (WTMM). Nevertheless, the tracing of WTMM is not just a tedious procedure computationally; ambiguity is often resulted in determining the correspondence of a modulus maximum to a singularity. In that light, the wavelet transform modulus sum (WTMS) approach was proposed. In this paper, the applications of WTMS in image denoising, compressed image deblocking, and scalable image coding are described. They show that WSD is a valuable tool for image processing and has widespread applications.
Original languageEnglish
Title of host publicationMidwest Symposium on Circuits and Systems
Publication statusPublished - 1 Dec 2002
Event2002 45th Midwest Symposium on Circuits and Systems - Tulsa, OK, United States
Duration: 4 Aug 20027 Aug 2002


Conference2002 45th Midwest Symposium on Circuits and Systems
Country/TerritoryUnited States
CityTulsa, OK

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials


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