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Proceedings Paper

Optical Gabor and wavelet transforms for scene analysis
Author(s): David P. Casasent; John Scott Smokelin; Anqi Ye
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Paper Abstract

Recent development in vision and image understanding related study reveals that a signal decomposition before processing may provide enormous useful information about the signal. Various signal decomposition models, such as the Gabor and wavelet transforms have been proposed. While the Gabor signal expansion creates a fixed resolution space-frequency signal representation, the wavelet transform provides a multi-resolution signal space-scale decomposition. Digital implementation of these transforms are computationally intensive both because of the nature of the coordinate-doubling of the transforms and due to the large quantity of convolution/correlation operations to be performed. Optics with its inherent parallel processing capability has been applied to many useful linear signal and image transformations for feature analysis and extraction. This paper is intended to study the suitability of using optical processing techniques for the signal Gabor and wavelet analysis. Gabor and wavelet transforms of both one- and two-dimensional signals and images are discussed. System parameters and limitation are analyzed. Preliminary experimental results are presented.

Paper Details

Date Published: 1 July 1992
PDF: 9 pages
Proc. SPIE 1702, Hybrid Image and Signal Processing III, (1 July 1992); doi: 10.1117/12.60542
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)
John Scott Smokelin, Carnegie Mellon Univ. (United States)
Anqi Ye, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 1702:
Hybrid Image and Signal Processing III
David P. Casasent; Andrew G. Tescher, Editor(s)

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