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Proceedings Paper

Acceleration of tomographic hyperspectral restoration algorithms
Author(s): Harvey C. Schau
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Paper Abstract

Hyperspectral imaging spectrometers have proven to be both versatile and powerful instruments with applications in diverse areas such as medical diagnosis, land usage, military target detection, and art forgery. In many applications scanning systems cannot be effectively employed and true "flash" operation is necessary. Multiplex systems have been developed which can gather information in multispectral bands simultaneously, and then produce a datacube after mathematical restoration. Such system enjoy compact size, robust construction, inexpensive costs and zero moving parts at the cost of highly complex mathematical restoration operations. Currently the limiting feature of such tomographic hyperspectral imagers such as the FMDIS [1,2] is the speed of restoration. Due to the large sizes of the restoration kernel, restorations are typically recursive and require many iterations to achieve satisfactory results. Little can be done to make the systems smaller since the size is determined by the number of colors and pixel size of the focal plane arrays (FPA) employed. Thus, techniques must be investigated to speed up the restoration either by reducing the number of iterations or reducing the number of operations within an iteration. It is assumed that little can be done to reduce the number of operations in an iteration since the operations are done in sparse format, we therefore investigate reducing the number of iterations through mathematical accelerations. We assume this acceleration will work to advantage regardless of the mechanism (PC-based or dedicated processor such as a gate array) by which the restoration is implemented.

Paper Details

Date Published: 8 May 2006
PDF: 11 pages
Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 623308 (8 May 2006);
Show Author Affiliations
Harvey C. Schau, Raytheon Missile Systems (United States)

Published in SPIE Proceedings Vol. 6233:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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