13 May 2010 Using compressive imaging as a fast class formation method in automatic target acquisition
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Abstract
Subspace projection is an effective and established way to form classes in the Automatic Target Acquisition (ATA) problem. Class subspace formation is viewed in this paper as an over specified F h = u problem. Recent advances in compressive imaging show that this problem can be solved for sparse matrices via iterative techniques. Convergence of these techniques is aided by a metric induced by an appropriately selected norm. In this paper we will use infrared data to show this rapid class formation and to compare convergence for two norms. Based on this class formulation a new method for ATA solution will also be demonstrated.
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Charles F. Hester, Kelly K. Dobson, "Using compressive imaging as a fast class formation method in automatic target acquisition", Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 76960P (13 May 2010); doi: 10.1117/12.849717; https://doi.org/10.1117/12.849717
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KEYWORDS
Optical spheres

Compressive imaging

Target acquisition

Image segmentation

Condition numbers

Visualization

Image compression

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