title: Fast Convolution with Laplacian-of-Gaussian Masks.
abstract: We present a technique for computing the convolution of an image with LoG (Laplacian-of-Gaussian) masks. It is well known that a LoG of variance a can be decomposed as a Gaussian mask and a LoG of variance a1 < a. We take advantage of the specific spectral characteristics of these filters in our computation: the LoG is a bandpass filter; we can therefore fold the spectrum of the image (after low pass filtering) without loss of information, which is equivalent to reducing the resolution. We present a complete evaluation of the parameters involved, together with a complexity analysis that leads to the paradoxical result that the computation time decreases when a increases. We illustrate the method on two images.
authors.affiliation: Departments of Electrical Engineering and Computer Science, University of Southern California, Los Angeles, CA 90089.
authors.forename: J S
authors.initials: JS
authors.lastname: Chen
authors.forename: A
authors.initials: A
authors.lastname: Huertas
authors.forename: G
authors.initials: G
authors.lastname: Medioni