A local wavelet transform implementation versus an optimal row-column algorithm for the 2D multilevel decomposition

Y. Andreopoulos, N. D. Zervas, G. Lafruit, P. Schelkens, T. Stouraitis, C. E. Goutis, J. Cornelis

Research output: Contribution to conferencePaperpeer-review

14 Scopus citations

Abstract

A new method for the implementation of the binary-tree decomposition of the convolution-based wavelet transform, called the Local Wavelet Transform (LWT) has been recently proposed in the literature. While it produces exactly the same results as the classical row-column implementation of the transform, it has many implementation benefits. In this paper, this fact is shown experimentally for the first time for a general-purpose processor-based architecture, by comparing our C implementation of the LWT with an optimal C implementation of the lifting-scheme row-column algorithm. The comparisons are made for the forward multilevel binary-tree decomposition using the 9/7 filter pair, in the typical Intel Pentium processor family.

Original languageBritish English
Pages330-333
Number of pages4
StatePublished - 2001
EventIEEE International Conference on Image Processing (ICIP) - Thessaloniki, Greece
Duration: 7 Oct 200110 Oct 2001

Conference

ConferenceIEEE International Conference on Image Processing (ICIP)
Country/TerritoryGreece
CityThessaloniki
Period7/10/0110/10/01

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