Approximation-theoretical analysis of translation invariant wavelet expansions

J. Liu, P. Moulin

Research output: Contribution to conferencePaperpeer-review


It has been observed from image denoising experiments that translation invariant (TI) wavelet transforms often outperform orthogonal wavelet transforms. This paper compares the two transforms from the viewpoint of approximation theory, extending previous results based on Haar wavelets. The advantages of the TI expansion over orthogonal expansion are twofold: the TI expansion produces smaller approximation error when approximating a smooth function, and it mitigates Gibbs artifacts when approximating a discontinuous function.

Original languageEnglish (US)
Number of pages4
StatePublished - 2001
EventIEEE International Conference on Image Processing (ICIP) 2001 - Thessaloniki, Greece
Duration: Oct 7 2001Oct 10 2001


OtherIEEE International Conference on Image Processing (ICIP) 2001

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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