Searching for the optimal curvelet tiling

Hasan Al-Marzouqi, Ghassan Alregib

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

7 Scopus citations

Abstract

Curvelets were recently introduced as a popular extension of wavelets. In the curvelet domain the input image is represented by sets of coefficients representing signal energy in different scales and angular directions. In this paper an algorithm that searches for optimal tilings for use with the curvelet transform is introduced. We consider two adaptations: scale locations, and the number of angular divisions per scale. A search algorithm that searches for the optimal tiling with respect to denoising performance is introduced. Results show significant improvement over original curvelet tilings. Tiling results were also tested with a seismic compressed sensing recovery problem. A similar performance advantage is reported.

Original languageBritish English
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages1626-1630
Number of pages5
DOIs
StatePublished - 18 Oct 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 26 May 201331 May 2013

Publication series

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

Conference

Conference2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Country/TerritoryCanada
CityVancouver, BC
Period26/05/1331/05/13

Keywords

  • curvelet transform
  • denoising
  • image processing
  • seismic recovery
  • wavelet extension

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