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Fast Convolution with Laplacian-of-Gaussian Masks

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3 Author(s)
J. S. Chen ; Departments of Electrical Engineering and Computer Science, University of Southern California, Los Angeles, CA 90089. ; A. Huertas ; G. Medioni

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 ¿1 < ¿. 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 ¿ increases. We illustrate the method on two images.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:PAMI-9 ,  Issue: 4 )