DocumentCode
1509544
Title
Interpolating multiwavelet bases and the sampling theorem
Author
Selesnick, Ivan W.
Author_Institution
Dept. of Electr. Eng., Polytech.. Univ., Brooklyn, NY, USA
Volume
47
Issue
6
fYear
1999
fDate
6/1/1999 12:00:00 AM
Firstpage
1615
Lastpage
1621
Abstract
This paper considers the classical sampling theorem in multiresolution spaces with scaling functions as interpolants. As discussed by Xia and Zhang (1993), for an orthogonal scaling function to support such a sampling theorem, the scaling function must be cardinal (interpolating). They also showed that the only orthogonal scaling function that is both cardinal and of compact support is the Haar function, which is not continuous. This paper addresses the same question, but in the multiwavelet context, where the situation is different. This paper presents the construction of compactly supported orthogonal multiscaling functions that are continuously differentiable and cardinal. The scaling functions thereby support a Shannon-like sampling theorem. Such wavelet bases are appealing because the initialization of the discrete wavelet transform (prefiltering) is the identity operator
Keywords
discrete wavelet transforms; filtering theory; interpolation; signal resolution; signal sampling; Haar function; Shannon-like sampling theorem; cardinal scaling functions; compactly supported orthogonal multiscaling functions; continuously differentiable function; discrete wavelet transform; identity operator; multiresolution spaces; multiwavelet bases interpolation; prefiltering; Continuous wavelet transforms; Discrete wavelet transforms; Filter bank; History; Interpolation; Multiresolution analysis; Sampling methods; Signal processing; Signal resolution; Signal sampling;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.765131
Filename
765131
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