17 March 2008 Computational sensing algorithms for image reconstruction and the detection of moving objects in multiplexed imaging systems
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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.
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Robert Muise, Robert Muise, Abhijit Mahalanobis, Abhijit Mahalanobis, } "Computational sensing algorithms for image reconstruction and the detection of moving objects in multiplexed imaging systems", Proc. SPIE 6977, Optical Pattern Recognition XIX, 69770M (17 March 2008); doi: 10.1117/12.785131; https://doi.org/10.1117/12.785131
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