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Proceedings Paper

Time series modeling for automatic target recognition
Author(s): Andre Sokolnikov
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Paper Abstract

Time series modeling is proposed for identification of targets whose images are not clearly seen. The model building takes into account air turbulence, precipitation, fog, smoke and other factors obscuring and distorting the image. The complex of library data (of images, etc.) serving as a basis for identification provides the deterministic part of the identification process, while the partial image features, distorted parts, irrelevant pieces and absence of particular features comprise the stochastic part of the target identification. The missing data approach is elaborated that helps the prediction process for the image creation or reconstruction. The results are provided.

Paper Details

Date Published: 3 May 2012
PDF: 10 pages
Proc. SPIE 8391, Automatic Target Recognition XXII, 839104 (3 May 2012); doi: 10.1117/12.919723
Show Author Affiliations
Andre Sokolnikov, Visual Solutions and Applications (United States)


Published in SPIE Proceedings Vol. 8391:
Automatic Target Recognition XXII
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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