Fast Implementation of the Continuous Wavelet Transform with Integer Scales

Michael Unser, Akram Aldroubi, Steven Schiff

Research output: Contribution to journalArticle

62 Citations (Scopus)

Abstract

We describe a fast noniterative algorithm for the evaluation of continuous spline wavelet transforms at any integer scale m. In this approach, the input signal and the analyzing wavelet are both represented by polynomial splines. The algorithm uses a combination of moving sum and zero-padded filters, and its complexity per scale is O(N), where N is the signal length. The computation is exact, and the implementation is noniterative across scales. We also present examples of spline wavelets exhibiting properties that are desirable for either singularity detection (first and second derivative operators) or Gabor-like time-frequency signal analysis.

Original languageEnglish (US)
Pages (from-to)3519-3523
Number of pages5
JournalIEEE Transactions on Signal Processing
Volume42
Issue number12
DOIs
StatePublished - Jan 1 1994

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Splines
Wavelet transforms
Signal analysis
Polynomials
Derivatives

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

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Fast Implementation of the Continuous Wavelet Transform with Integer Scales. / Unser, Michael; Aldroubi, Akram; Schiff, Steven.

In: IEEE Transactions on Signal Processing, Vol. 42, No. 12, 01.01.1994, p. 3519-3523.

Research output: Contribution to journalArticle

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