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Proceedings Paper

Application of wavelet and neural processing to automatic target recognition
Author(s): Gene A. Tagliarini; Edward W. Page; Gregory M. Kesden; David J. Chiang; Philip J. McPartland
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Paper Abstract

The general area of signal and image processing that focuses upon the detection and identification of military targets is known as automatic target recognition. This paper compares the impact of alternative wavelet processing techniques upon the performance of neural networks being used for target detection. In particular, the use of a filter whose coefficients are a linear combination of wavelet coefficients gave rise to an energy distribution in which targets were more detectable with fewer false alarms than when the same targets were sought in images whose data dimensionality was reduced using a conventional wavelet.

Paper Details

Date Published: 23 June 1997
PDF: 7 pages
Proc. SPIE 3069, Automatic Target Recognition VII, (23 June 1997); doi: 10.1117/12.277100
Show Author Affiliations
Gene A. Tagliarini, Neural Technology, Inc. (United States)
Edward W. Page, Neural Technology, Inc. (United States)
Gregory M. Kesden, Neural Technology, Inc. (United States)
David J. Chiang, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Philip J. McPartland, Naval Air Warfare Ctr. (United States)


Published in SPIE Proceedings Vol. 3069:
Automatic Target Recognition VII
Firooz A. Sadjadi, Editor(s)

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