Novel Representations of Elevation Data

Award Information
Agency:
Department of Defense
Branch:
Army
Amount:
$119,972.00
Award Year:
2007
Program:
SBIR
Phase:
Phase I
Contract:
W9132V-08-C-0013
Agency Tracking Number:
A072-123-0960
Solicitation Year:
2007
Solicitation Topic Code:
A07-123
Solicitation Number:
2007.2
Small Business Information
NUMERICA CORP.
4850 Hahns Peak Drive, Suite 200, Loveland, CO, 80538
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
956324362
Principal Investigator
 Randy Paffenroth
 Program Director
 (970) 461-2000
 rpaffenroth@numerica.us
Business Contact
 Stephanie Mueller
Title: Contract Manger
Phone: (970) 461-2000
Email: smueller@numerica.us
Research Institution
N/A
Abstract
With ever-increasing detail in terrain elevation data available to the Warfighter, new challenges are faced in the Battlespace for storage, transmission, and rapid display of these data. The key benefit of these more detailed data is better representation of terrain: thus, traditional approaches to compress or stream the information are generally not acceptable as these techniques typically reduce data fidelity. Accurate representations of elevation data are required for Mission Planning, Intelligence Preparation of the Battlefield, and Dismount Maneuvers. All of these applications are facilitated by highly compressed, high fidelity Digital Elevation Models (DEM). Accordingly, advanced algorithms are required to compress Geographic Information System (GIS) data allowing DEM data to be transmitted, stored, manipulated, and displayed by the Warfighter to facilitate real-time Battlespace assessment. Currently available compression technologies can be quite effective at reducing image data files sizes. Such methods often do not correctly represent outliers in the data, but outliers are perhaps the most important part of a DEM data set. The precise location and elevation of local maxima are critical information for pilots and artillery units. The proposed work centers on compression schemes that accurately encode outlier information while maintaining small file sizes and efficient decompression.

* information listed above is at the time of submission.

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