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Proceedings Paper

Optimization filters design for GFT by genetic algorithm
Author(s): Hanjun Peng; H. John Caulfield; Jason M. Kinser; James M. Hereford
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Paper Abstract

In all current Fourier transform processing systems, which we call conventional Fourier transform (CFT) processors, no matter what kind of filter is used, its filter function can be expressed as a diagonal matrix, if in the view of digital image processing. We have presented a generalized Fourier transform (GFT) processor by extending the diagonal filter matrix into a nondiagonal matrix. It includes CFT as a special case, and still retains the space/time- invariance property. In this paper, we present a method based on genetic algorithms for finding an optimal filter of GFT processor. The behavior of the optimal filter in GFT processor and its advantages over that in the CFT processor are illustrated by the satisfied test results. An optimal generalized Teoplitz matrix for the GFT processor filter based on the figure of merit--the Manhatten error norm is also proposed.

Paper Details

Date Published: 28 August 1995
PDF: 11 pages
Proc. SPIE 2565, Optical Implementation of Information Processing, (28 August 1995); doi: 10.1117/12.217644
Show Author Affiliations
Hanjun Peng, Alabama A&M Univ. (United States)
H. John Caulfield, Alabama A&M Univ. (United States)
Jason M. Kinser, Alabama A&M Univ. (United States)
James M. Hereford, Camber Corp. (United States)

Published in SPIE Proceedings Vol. 2565:
Optical Implementation of Information Processing
Bahram Javidi; Joseph L. Horner, Editor(s)

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