The Community for Technology Leaders
Green Image
Issue No. 02 - February (1986 vol. 8)
ISSN: 0162-8828
pp: 234-239
William M. Wells , SRI International, Menlo Park, CA 94025.
Gaussian filtering is an important tool in image processing and computer vision. In this paper we discuss the background of Gaussian filtering and look at some methods for implementing it. Consideration of the central limit theorem suggests using a cascade of ``simple'' filters as a means of computing Gaussian filters. Among ``simple'' filters, uniform-coefficient finite-impulse-response digital filters are especially economical to implement. The idea of cascaded uniform filters has been around for a while [13], [16]. We show that this method is economical to implement, has good filtering characteristics, and is appropriate for hardware implementation. We point out an equivalence to one of Burt's methods [1], [3] under certain circumstances. As an extension, we describe an approach to implementing a Gaussian Pyramid which requires approximately two addition operations per pixel, per level, per dimension. We examine tradeoffs in choosing an algorithm for Gaussian filtering, and finally discuss an implementation.

W. M. Wells, "Efficient Synthesis of Gaussian Filters by Cascaded Uniform Filters," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 8, no. , pp. 234-239, 1986.
90 ms
(Ver 3.3 (11022016))