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Proceedings Paper

Multispectral image feature extraction by the joint wavelet-transform correlator
Author(s): Samuel Peter Kozaitis; Mark A. Getbehead; Wesley E. Foor
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Paper Abstract

A multispectral version of an image consisting of multiple wavelet components allows for more flexible feature extraction when compared to the use of one wavelet component. We showed how a multiple-input joint wavelet- transform correlator could be used for multispectral analysis of an input image. For m wavelet scales, m versions of the wavelet and m copies of the input image were generated using conventional optics that are used as inputs to a joint wavelet-transform correlator. The output consisted of 4m-1 correlation results, one of which is the desired output. The space-bandwidth product of the system is the same as for a conventional tow-input joint-transform correlator.

Paper Details

Date Published: 27 March 1997
PDF: 10 pages
Proc. SPIE 3073, Optical Pattern Recognition VIII, (27 March 1997); doi: 10.1117/12.270379
Show Author Affiliations
Samuel Peter Kozaitis, Florida Institute of Technology (United States)
Mark A. Getbehead, Rome Lab. (United States)
Wesley E. Foor, Rome Lab. (United States)

Published in SPIE Proceedings Vol. 3073:
Optical Pattern Recognition VIII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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