Please use this identifier to cite or link to this item: https://doi.org/10.1109/78.823972
DC FieldValue
dc.titleA general approach for analysis and application of discrete multiwavelet transforms
dc.contributor.authorTham, J.Y.
dc.contributor.authorShen, L.
dc.contributor.authorLee, S.L.
dc.contributor.authorTan, H.H.
dc.date.accessioned2014-10-28T02:28:09Z
dc.date.available2014-10-28T02:28:09Z
dc.date.issued2000
dc.identifier.citationTham, J.Y.,Shen, L.,Lee, S.L.,Tan, H.H. (2000). A general approach for analysis and application of discrete multiwavelet transforms. IEEE Transactions on Signal Processing 48 (2) : 457-464. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/78.823972" target="_blank">https://doi.org/10.1109/78.823972</a>
dc.identifier.issn1053587X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/102650
dc.description.abstractThis paper proposes a general paradigm for the analysis and application of discrete multiwavelet transforms, particularly to image compression. First, we establish the concept of an equivalent scalar (wavelet) filter bank system in which we present an equivalent and sufficient representation of a multiwavelet system of multiplicity r in terms of a set of r equivalent scalar filter banks. This relationship motivates a new measure called the good multifilter properties (GMP's), which define the desirable filter characteristics of the equivalent scalar filters. We then relate the notion of GMP's directly to the matrix filters as necessary eigenvector properties for the refinement masks of a given multiwavelet system. Second, we propose a generalized, efficient, and nonredundant framework for multiwavelet initialization by designing appropriate preanalysis and post-synthesis multirate filtering techniques. Finally, our simulations verified that both orthogonal and biorthogonal multiwavelets that possess GMP's and employ the proposed initialization technique can perform better than the popular scalar wavelets such as Daubechies'DS wavelet and the D(9/7) wavelet, and some of these multiwavelets achieved this with lower computational complexity. © 2000 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/78.823972
dc.sourceScopus
dc.subjectGood multifilter properties
dc.subjectImage compression
dc.subjectMultiwavelets
dc.subjectPreanalysis and post-synthesis filtering
dc.subjectWavelets
dc.typeArticle
dc.contributor.departmentMATHEMATICS
dc.description.doi10.1109/78.823972
dc.description.sourcetitleIEEE Transactions on Signal Processing
dc.description.volume48
dc.description.issue2
dc.description.page457-464
dc.description.codenITPRE
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

125
checked on Dec 6, 2022

Page view(s)

152
checked on Dec 8, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.