Special class of orthonormal wavelets: Theory, implementations, and applications

Lixin Shen, Jo Yew Tham, Seng Luan Lee, Hwee Huat Tan

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper introduces a novel class of length-4N orthonormal scalar wavelets, and presents the theory, implementational issues, and their applications to image compression. We first give the necessary and sufficient conditions for the existence of this class. The parameterized representation of filters with different lengths are then given. Next, we derive new and efficient decomposition and reconstruction algorithms specifically tailored to this class of wavelets. We will show that the proposed discrete wavelet transformations are orthogonal and have lower computational complexity than conventional octave-bandwidth transforms using Daubechies' orthogonal filters of equal length. In addition, we also verify that symmetric boundary extensions can be applied. Finally, our image compression results further confirm that improved performance can be achieved with lower computational cost.

Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PublisherIEEE Computer Society
Pages1225-1228
Number of pages4
Volume3
StatePublished - 1999
Externally publishedYes
EventProceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-99) - Phoenix, AZ, USA
Duration: Mar 15 1999Mar 19 1999

Other

OtherProceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-99)
CityPhoenix, AZ, USA
Period3/15/993/19/99

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ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Acoustics and Ultrasonics

Cite this

Shen, L., Tham, J. Y., Lee, S. L., & Tan, H. H. (1999). Special class of orthonormal wavelets: Theory, implementations, and applications. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (Vol. 3, pp. 1225-1228). IEEE Computer Society.