SBIR/STTR Research Award

Infrared Background Clutter Metrics

Award identifier 3dff721023e24d34dc7dd6cc2197979e0db8e11fdccb97eb7f25c4d4fb120579Awarding agency Department of Defense · Army

Award amount

$98,939

Program and phase

SBIR · Phase I

Award year

1997

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Army
Recipient company
OPTIMETRICS, INC.
Proposal award date
Not reported
Contract end date
Not reported
UEI
XFY4P5U7THQ1
Solicitation number
Not reported
Topic code
Not reported

Research abstract

The ability of either a human observer or an automated sensor to recognize a target in an infrared scene depends both on the target and clutter content of the infrared scene. Metrics have been developed to quantify the difference between the target and its background, to be used as independent variables in the modeling of both observer performance and of automated seeker performance. We believe that a metric designed particularly to measure the information content added by the presence of a target will be monotonically related with the ability of any observer to detect that target, and hence should form a robust and useful measure of target detectability. We propose to build a correlation-free description of the background portion of the image under investigation, measure the information content of the background region, in bits/pixel, and then code the target region in a coding scheme based on the entropy of the background region. The result will be an absolute measure of the number of bits (information) added to the target/background image by the presence of the target. This quantity will serve as a very appropriate independent variable against which observer and seeker performance can be modeled. We will have developed a technique whereby the information content introduced by the presence of a target can be computed. The ease with which a target can be detected in its background should be monotonically related to the information content added by the presence of the target. Thus, we will have developed a powerful technique for modeling detection performance of a variety of sensors.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

28 SBIR/STTR records share this UEI (1984–2010). Reported award amounts total $6,890,662. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.