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Proceedings Paper

Target recognition in infrared image using a new neural network model
Author(s): Yun Hu; Guan Hua; Zhenkang Shen; Zhongkang Sun
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Paper Abstract

This paper is concerned with algorithms for target detection and recognition in infrared (IR) images. The second order differential method is developed to remove the correlation of noise and clutter, and multiframe cumulation is exploited for enhancing the target and suppressing background noise relatively. Backpropagation neural network is developed for target identifying. The proposed ANN is trained by unsupervised learning and supervised learning.

Paper Details

Date Published: 28 March 1995
PDF: 12 pages
Proc. SPIE 2424, Nonlinear Image Processing VI, (28 March 1995); doi: 10.1117/12.205264
Show Author Affiliations
Yun Hu, National Univ. of Defense Technology (China)
Guan Hua, National Univ. of Defense Technology (China)
Zhenkang Shen, National Univ. of Defense Technology (China)
Zhongkang Sun, National Univ. of Defense Technology (China)

Published in SPIE Proceedings Vol. 2424:
Nonlinear Image Processing VI
Edward R. Dougherty; Jaakko T. Astola; Harold G. Longbotham; Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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