Improved target detector for FLIR imagery

Algorithms are considered for searching wide area forward-looking infrared imagery for military vehicles. Wide area search has typically been handled by using a simple detection algorithm with low computational cost to search the entire image or set of images, followed by a clutter rejection algorit...

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Bibliographic Details
Published in2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03) Vol. 2; pp. II - 401
Main Authors Chan, L.A., Der, S.Z., Nasrabadi, N.M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Algorithm design and analysis
Computational efficiency
Computer architecture
Computer vision
Detection algorithms
Detectors
Image analysis
Infrared imaging
Military computing
Vehicles
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Summary:Algorithms are considered for searching wide area forward-looking infrared imagery for military vehicles. Wide area search has typically been handled by using a simple detection algorithm with low computational cost to search the entire image or set of images, followed by a clutter rejection algorithm that analyzes only those portions of the image that are marked by the detection algorithm. We start with a feature based detector and a eigen-neural based clutter rejecter, and examine a number of architectures for combining these modules to maximize joint performance. The architectures considered include a clutter rejection threshold method and a nonlinear learning-based combination. The performance of the architectures are compared using a set of several thousand real images.
ISBN:9780780376632
0780376633
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2003.1202383