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

Luc Florack

doi:10.1109/34.877526

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

Luc Florack

Mathematical Image Analysis

Research output: Contribution to journal › Article › Academic › peer-review

10 Citations (Scopus)

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

Original language	English
Pages (from-to)	1050-1055
Number of pages	6
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	22
Issue number	9
DOIs	https://doi.org/10.1109/34.877526
Publication status	Published - 2000

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

Abstract

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