Optimization filters design for GFT by genetic algorithm

Hanjun Peng; H. John Caulfield; Jason M. Kinser; James M. Hereford

doi:10.1117/12.217644

28 August 1995 Optimization filters design for GFT by genetic algorithm

Hanjun Peng, H. John Caulfield, Jason M. Kinser, James M. Hereford

Proceedings Volume 2565, Optical Implementation of Information Processing; (1995) https://doi.org/10.1117/12.217644
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

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.

Citation Download Citation

Hanjun Peng, H. John Caulfield, Jason M. Kinser, and James M. Hereford "Optimization filters design for GFT by genetic algorithm", Proc. SPIE 2565, Optical Implementation of Information Processing, (28 August 1995); https://doi.org/10.1117/12.217644

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