Fast Computation by Subdivision of Multidimensional Splines and Their Applications
Abstract
We present theory and algorithms for fast explicit computations of
uni- and multi-dimensional periodic splines of arbitrary order at triadic rational
points and of splines of even order at diadic rational points. The algorithms
use the forward and the inverse Fast Fourier transform (FFT). The implementation
is as fast as FFT computation. The algorithms are based on binary and
ternary subdivision of splines. Interpolating and smoothing splines are used for a
sample rate convertor such as resolution upsampling of discrete-time signals and
digital images and restoration of decimated images that were contaminated by
noise. The performance of the rate conversion based spline is compared with the
performance of the rate conversion by prolate spheroidal wave functions.
Main Authors
Format
Articles
Research article
Published
2016
Series
Subjects
Publication in research information system
Publisher
Yokohama Publishers
Original source
http://www.ybook.co.jp/online2/oppafa/vol1/p309.html
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201609063992Use this for linking
Review status
Peer reviewed
ISSN
2189-3756
Language
English
Published in
Pure and Applied Functional Analysis
Citation
- Averbuch, A., Neittaanmäki, P., Shabat, G., & Zheludev, V. (2016). Fast Computation by Subdivision of Multidimensional Splines and Their Applications. Pure and Applied Functional Analysis, 1(3), 309-341. http://www.ybook.co.jp/online2/oppafa/vol1/p309.html
Copyright© 2016 Yokohama Publishers. This is a final draft version of an article whose final and definitive form has been published by Yokohama Publishers. Published in this repository with the kind permission of the publisher.