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Proceedings Paper

Computational sensing algorithms for image reconstruction and the detection of moving objects in multiplexed imaging systems
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Paper Abstract

The problem of wide area persistent surveillance presents imaging problems which cannot be addressed by traditional sensing. We consider a coded aperture approach to imaging a wide area with high resolution for an object tracking application. Coded aperture imaging systems are generally designed for obtaining images of static scenes. For exploitation of dynamic scenes, the coding approach must be modified to not only reconstruct the image, but also to facilitate the detection of moving objects over this large area. We present a multi-scale framework that describes a multiplexed sensing and image reconstruction process. A novel method is introduced for learning a "motion model" for a given scene, and using it to handle the ambiguity induced by object motion. The results of initial simulations are presented.

Paper Details

Date Published: 17 March 2008
PDF: 10 pages
Proc. SPIE 6977, Optical Pattern Recognition XIX, 69770M (17 March 2008); doi: 10.1117/12.785131
Show Author Affiliations
Robert Muise, Lockheed Martin Missiles and Fire Control (United States)
Abhijit Mahalanobis, Lockheed Martin Missiles and Fire Control (United States)

Published in SPIE Proceedings Vol. 6977:
Optical Pattern Recognition XIX
David P. Casasent; Tien-Hsin Chao, Editor(s)

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