Low complexity multidimensional CDF 5/3 DWT architecture

This paper introduces an efficient low complexity multidimensional DWT architecture. The proposed architecture is based on a lifting-scheme for the Cohen-Daubechies-Feauveau (CDF) 5/3 DWT filter. It consists of low complexity identical computation and control units which can be used easily to implem...

Full description

Saved in:
Bibliographic Details
Main Authors: Al-Azawi S., Abbas Y.A., Jidin R.
Other Authors: 36614945900
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uniten.dspace-21845
record_format dspace
spelling my.uniten.dspace-218452023-05-16T10:45:41Z Low complexity multidimensional CDF 5/3 DWT architecture Al-Azawi S. Abbas Y.A. Jidin R. 36614945900 56417806700 6508169028 This paper introduces an efficient low complexity multidimensional DWT architecture. The proposed architecture is based on a lifting-scheme for the Cohen-Daubechies-Feauveau (CDF) 5/3 DWT filter. It consists of low complexity identical computation and control units which can be used easily to implement 2-D and 3-D DWT architectures. The synthesis results show that the output latency is 2N+2 clock cycles, with N2+2N+2 clock cycles required for the first level 2-D CDF 5/3 DWT computation. The architecture is parameterized to tackle various images and wordlength sizes. Furthermore, the proposed architecture is implemented using a Virtex 6 Xilinx FPGA platform. The implementation results reveal that the proposed architecture can operate at up to 198 MHz operating frequency. This reduces the time for first level DWT decomposition of a 512×512-pixel image to less than 1.3 m sec. © 2014 IEEE. Final 2023-05-16T02:45:41Z 2023-05-16T02:45:41Z 2014 Conference Paper 10.1109/CSNDSP.2014.6923937 2-s2.0-84910614426 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84910614426&doi=10.1109%2fCSNDSP.2014.6923937&partnerID=40&md5=79cbb587d4b79241fe2951b9064d836e https://irepository.uniten.edu.my/handle/123456789/21845 6923937 804 808 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description This paper introduces an efficient low complexity multidimensional DWT architecture. The proposed architecture is based on a lifting-scheme for the Cohen-Daubechies-Feauveau (CDF) 5/3 DWT filter. It consists of low complexity identical computation and control units which can be used easily to implement 2-D and 3-D DWT architectures. The synthesis results show that the output latency is 2N+2 clock cycles, with N2+2N+2 clock cycles required for the first level 2-D CDF 5/3 DWT computation. The architecture is parameterized to tackle various images and wordlength sizes. Furthermore, the proposed architecture is implemented using a Virtex 6 Xilinx FPGA platform. The implementation results reveal that the proposed architecture can operate at up to 198 MHz operating frequency. This reduces the time for first level DWT decomposition of a 512×512-pixel image to less than 1.3 m sec. © 2014 IEEE.
author2 36614945900
author_facet 36614945900
Al-Azawi S.
Abbas Y.A.
Jidin R.
format Conference Paper
author Al-Azawi S.
Abbas Y.A.
Jidin R.
spellingShingle Al-Azawi S.
Abbas Y.A.
Jidin R.
Low complexity multidimensional CDF 5/3 DWT architecture
author_sort Al-Azawi S.
title Low complexity multidimensional CDF 5/3 DWT architecture
title_short Low complexity multidimensional CDF 5/3 DWT architecture
title_full Low complexity multidimensional CDF 5/3 DWT architecture
title_fullStr Low complexity multidimensional CDF 5/3 DWT architecture
title_full_unstemmed Low complexity multidimensional CDF 5/3 DWT architecture
title_sort low complexity multidimensional cdf 5/3 dwt architecture
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806427833089654784
score 13.18916