Morphological wavelets and the complexity of dyadic trees

Zhen James Xiang, Peter Jeffrey Ramadge

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper we reveal a connection between the coefficients of the morphological wavelet transform and complexity measures of dyadic tree representations of level sets. This leads to better understanding of the edge preserving property that has been discovered in both areas. As an immediate application, we examine a depth-adaptive soft thresholding scheme on morphological wavelet coefficients in which the threshold decays geometrically as the resolution increases. A greater decay rate gives greater preference towards unbalanced trees and this can control edge enhancement in denoised signals.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
Pages4030-4033
Number of pages4
DOIs
StatePublished - Nov 8 2010
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: Mar 14 2010Mar 19 2010

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
CountryUnited States
CityDallas, TX
Period3/14/103/19/10

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Image edge analysis
  • Image enhancement
  • Morphological operations
  • Wavelet transforms

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  • Cite this

    Xiang, Z. J., & Ramadge, P. J. (2010). Morphological wavelets and the complexity of dyadic trees. In 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings (pp. 4030-4033). [5495757] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2010.5495757