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Proceedings Paper

Restoration of randomly sampled blurred images
Author(s): Arthur Forman; Abhijit Mahalanobis
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Paper Abstract

The problem this paper addresses is to create an approximation for a source image given only a randomly selected subset of pixel samples extracted from a blurred version of the source image. This problem is different from the conventional image restoration problem, which attempts to create an approximation for the source image given all of the pixel samples available in the blurred image. Our approach finds a minimum weighted L2 norm solution for the ideal image that satisfies linear constraints given by the observed samples of the blurred image.

Paper Details

Date Published: 12 May 2016
PDF: 6 pages
Proc. SPIE 9844, Automatic Target Recognition XXVI, 984402 (12 May 2016); doi: 10.1117/12.2220828
Show Author Affiliations
Arthur Forman, Lockheed Martin Missiles and Fire Control (United States)
Abhijit Mahalanobis, Lockheed Martin Missiles and Fire Control (United States)


Published in SPIE Proceedings Vol. 9844:
Automatic Target Recognition XXVI
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)

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