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A Spatio-Frequency Trade-Off Scale for Scale-Space Filtering
September 2000 (vol. 22 no. 9)
pp. 1050-1055

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.

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Index Terms:
Scale-space filtering, temporal versus frequency aliasing, time-frequency trade-off scale.
Citation:
Luc Florack, "A Spatio-Frequency Trade-Off Scale for Scale-Space Filtering," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 9, pp. 1050-1055, Sept. 2000, doi:10.1109/34.877526
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