
Proceedings Paper
Distance classifier correlation filtersFormat | Member Price | Non-Member Price |
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Paper Abstract
The performance of shift-invariant distance classifiers based on correlation filters is evaluated. First, the effect of noise on a classifier designed to recognize synthetic aperture radar (SAR) is observed. Then, a 2-class ATR designed to recognize infrared images of actual targets is evaluated. The results attest to the ability of the distance classifier to tolerate distortions, and recognize targets in the presence of noise and clutter.
Paper Details
Date Published: 1 June 1994
PDF: 12 pages
Proc. SPIE 2238, Hybrid Image and Signal Processing IV, (1 June 1994); doi: 10.1117/12.177703
Published in SPIE Proceedings Vol. 2238:
Hybrid Image and Signal Processing IV
David P. Casasent; Andrew G. Tescher, Editor(s)
PDF: 12 pages
Proc. SPIE 2238, Hybrid Image and Signal Processing IV, (1 June 1994); doi: 10.1117/12.177703
Show Author Affiliations
Abhijit Mahalanobis, Hughes Missile Systems Co. (United States)
Daniel W. Carlson, Carnegie Mellon Univ. (United States)
Daniel W. Carlson, Carnegie Mellon Univ. (United States)
Bhagavatula Vijaya Kumar, Carnegie Mellon Univ. (United States)
S. Richard F. Sims, U.S. Army Aviation and Missile Command (United States)
S. Richard F. Sims, U.S. Army Aviation and Missile Command (United States)
Published in SPIE Proceedings Vol. 2238:
Hybrid Image and Signal Processing IV
David P. Casasent; Andrew G. Tescher, Editor(s)
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