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Proceedings Paper

Transform domain adaptive compressive sensing of specific objects
Author(s): Abhijit Mahalanobis
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Paper Abstract

We have previously shown in reference [3] that images of particular objects of interest can be recovered from compressive measurements by minimizing a L2-norm criterion that incorporates prior knowledge of the signal such as its expected spectra. The basis in which the signal is reconstructed was also noted to be an important consideration in the formulation of the solution. In this paper, we further improve this technique by representing the image in a multi-scale domain so that select bands of the transform can be adapted to reference signals from other sources, while improving the overall quality of reconstruction of the full image. It is shown by means of an example that the adaptation not only reduces the overall mean square error of the reconstruction, but also helps to correctly resolve features in the high-resolution image that are not accurately reconstructed by the open-loop algorithm.

Paper Details

Date Published: 3 June 2011
PDF: 9 pages
Proc. SPIE 8056, Visual Information Processing XX, 80560Q (3 June 2011); doi: 10.1117/12.884486
Show Author Affiliations
Abhijit Mahalanobis, Lockheed Martin Missiles and Fire Control (United States)

Published in SPIE Proceedings Vol. 8056:
Visual Information Processing XX
Zia-ur Rahman; Stephen E. Reichenbach; Mark Allen Neifeld, Editor(s)

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