A Spatio-Frequency Trade-Off Scale for Scale-Space Filtering

ÐWe 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. Index TermsÐScale-space filtering, temporal versus frequency aliasing, timefrequency trade-off scale.