Exploiting Raster Maps for Imagery Analysis

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9550-06-C-0075
Agency Tracking Number: F064-004-0143
Amount: $99,944.00
Phase: Phase I
Program: STTR
Awards Year: 2006
Solicitation Year: 2006
Solicitation Topic Code: AF06-T004
Solicitation Number: N/A
Small Business Information
INTERNATIONAL ASSOCIATION OF VIRTUAL ORG
DBA, IAVO Research and Scientific, 1010 Gloria Ave, Durham, NC, 27701
DUNS: 059333349
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Eric Lester
 VP
 (919) 433-2412
 elester@iavo-rs.com
Business Contact
 Matthew Heric
Title: CEO
Phone: (919) 433-2402
Email: mheric@iavo-rs.com
Research Institution
 U. OF UTAH, SCHOOL OF COMPUTING
 Tom Henderson
 50 S. Central Campus Dr.
Salt Lake City, UT, 84112
 (801) 581-3601
 Nonprofit college or university
Abstract
The US Air Force seeks innovative technologies to exploit available map data to provide a contextual backdrop for imagery. This contextual backdrop will allow the imagery analyst to more rapidly and accurately exploit the data for further processing. Maps provide a wealth of information, such as road delineations, road names, buildings, and other cultural features which comprise the contextual backdrop for an image. In short, the desired capability should allow the analyst to rapidly “know where they are” in an image and increase their daily throughput of images without sacrificing accuracy. Accordingly, we propose to develop ContextMAX which adheres closely to the stated requirements and leverages our 20+ years of successful imagery processing development and operational transitioning. ContextMAX will incorporate novel robot-mapping techniques for performing automated map analysis, advanced tie-point extraction from imagery, and multi-source registration to create a correlated scene providing the necessary contextual backdrop to imagery analyst for a given image. By this, ContextMAX represents an innovative, low-risk solution for improved contextual awareness to the imagery analyst as well as producing modular geospatial data management and extraction techniques useful to a number of remote sensing and GIS applications.

* information listed above is at the time of submission.

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