Please use this identifier to cite or link to this item: https://doi.org/10.1109/34.790434
Title: Fast implementation of scale-space by interpolatory subdivision scheme
Authors: Wang, Y.-P. 
Qu, R. 
Issue Date: Sep-1999
Citation: Wang, Y.-P., Qu, R. (1999-09). Fast implementation of scale-space by interpolatory subdivision scheme. IEEE Transactions on Pattern Analysis and Machine Intelligence 21 (9) : 933-939. ScholarBank@NUS Repository. https://doi.org/10.1109/34.790434
Abstract: While the scale-space approach has been widely used in computer vision, there has been a great interest in fast implementation of scale-space filtering. In this paper, we introduce an interpolatory subdivision scheme (ISS) for this purpose. In order to extract the geometric features in a scale-space representation, discrete derivative approximations are usually needed. Hence, a general procedure is also introduced to derive exact formulae for numerical differentiation with respect to this ISS. Then, from ISS, an algorithm is derived for fast approximation of scale-space filtering. Moreover, the relationship between the ISS and the Whittaker-Shannon sampling theorem and the commonly used spline technique is discussed. As an example of the application of ISS technique, we present some examples on fast implementation of λτ-spaces as introduced by Gokmen and Jain, which encompasses various famous edge detection filters. It is shown that the ISS technique demonstrates high performance in fast implementation of the scale-space filtering and feature extraction.
Source Title: IEEE Transactions on Pattern Analysis and Machine Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/103266
ISSN: 01628828
DOI: 10.1109/34.790434
Appears in Collections:Staff Publications

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

SCOPUSTM   
Citations

4
checked on Oct 15, 2018

WEB OF SCIENCETM
Citations

3
checked on Oct 15, 2018

Page view(s)

34
checked on Sep 28, 2018

Google ScholarTM

Check

Altmetric


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