A spatio-frequency trade-off scale for scale-space filtering

Author

Florack, Luc

Author_Institution

Dept. of Math., Utrecht Univ., Netherlands

Volume

22

Issue

9

fYear

2000

fDate

9/1/2000 12:00:00 AM

Firstpage

1050

Lastpage

1055

Abstract

We study implementation issues for spatial convolution filters and their Fourier alternative, with the aim to optimize the accuracy of filter output. We focus on Gaussian scale-space filters and show that there exists a trade-off scale that subdivides the available scale range into two subintervals of equal length. Below this trade-off scale Fourier filtering yields more accurate results than spatial filtering; above it is the other way around. This should be contrasted with demands of computational speed, which show the opposite tenet

Keywords

computational complexity; convolution; filtering theory; image processing; optimisation; spatial filters; Fourier alternative; Fourier filtering; Gaussian scale-space filters; computational speed; filter output accuracy optimization; image processing; scale-space filtering; spatial convolution filters; spatio-frequency trade-off scale; subintervals; trade-off scale; Biomedical imaging; Convolution; Discrete Fourier transforms; Equations; Filtering; Filters; Fourier transforms; Frequency; Image analysis; Image processing;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.877526

Filename

877526