A Novel Approach to EO, IR, SAR, and Hyperspectral Sensor Fusion

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$100,000.00
Award Year:
2005
Program:
SBIR
Phase:
Phase I
Contract:
FA8718-05-C-0057
Award Id:
73138
Agency Tracking Number:
F051-207-1169
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
15400 Calhoun Drive, Suite 400, Rockville, MD, 20855
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
161911532
Principal Investigator:
ChimanKwan
Director of Research and Design
(301) 294-5238
ckwan@i-a-i.com
Business Contact:
MarkJames
Contracts and Proposals Manager
(301) 294-5221
mjames@i-a-i.com
Research Institute:
n/a
Abstract
Target detection and classification is challenging because target detection and classification cannot be effectively carried out by pure visual inspection and must rely on some automatic algorithms. Intelligent Automation, Inc. (IAI) and its subcontractor, Prof. C. Chang of the University of Maryland at Baltimore County (UMBC), propose a new hybrid framework for target detection and classification using airborne images from two perspectives: spatial and spectral. The spatial approach focuses on texture analysis. The idea is motivated by the fact that the image texture will be disturbed if targets are present. This approach is applicable to EO, IR, hyperspectral, and SAR images. The spectral approach and has two steps. First, a new automatic target generation process (ATGP) is used to generate a set of potential targets from the image data in an unsupervised fashion without using any prior knowledge. Second, an Automatic Target Detection and Classification Algorithm (ATDCA) is used to identify the potential targets. The algorithm can be used to detect anomalies (new and unknown targets) in blind environments. The algorithm is suitable for surveillance operations where the objective is to detect the presence of any potential targets.

* information listed above is at the time of submission.

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