Publication Details
Minimum Memory Vectorisation of Wavelet Lifting
BAŘINA, D.; ZEMČÍK, P. Minimum Memory Vectorisation of Wavelet Lifting. In Advanced Concepts for Intelligent Vision Systems (ACIVS). Lecture Notes in Computer Science (LNCS) 8192. Poznan: Springer London, 2013. p. 91-101. ISBN: 978-3-319-02894-1.
Czech title
Vektorizace vlnkové transformace
Type
conference paper
Language
English
Authors
Keywords
discrete wavelet transform, lifting scheme, parallelization, vectorisation, SIMD
Abstract
The subject of this paper is to introduce novel vectorisation of discrete wavelet transform implementation using lifting scheme.
Annotation
With the start of the widespread use of discrete wavelet transform the need for its effective implementation is becoming increasingly more important. This work presents a novel approach to discrete wavelet transform through a new computational scheme of wavelet lifting. The presented approach is compared with two other. The results are obtained on a general purpose processor with 4-fold SIMD instruction set (such as Intel x86-64 processors). Using the frequently exploited CDF 9/7 wavelet, the achieved speedup is about 3× compared to naive implementation.
Published
2013
Pages
91–101
Proceedings
Advanced Concepts for Intelligent Vision Systems (ACIVS)
Series
Lecture Notes in Computer Science (LNCS) 8192
Volume
8192
ISBN
978-3-319-02894-1
Publisher
Springer London
Place
Poznan
DOI
UT WoS
000332973500009
EID Scopus
BibTeX
@inproceedings{BUT103548,
author="David {Bařina} and Pavel {Zemčík}",
title="Minimum Memory Vectorisation of Wavelet Lifting",
booktitle="Advanced Concepts for Intelligent Vision Systems (ACIVS)",
year="2013",
series="Lecture Notes in Computer Science (LNCS) 8192",
volume="8192",
pages="91--101",
publisher="Springer London",
address="Poznan",
doi="10.1007/978-3-319-02895-8\{_}9",
isbn="978-3-319-02894-1",
url="https://www.fit.vut.cz/research/publication/10420/"
}