SBIR/STTR Research Award
Fast Image Enhancement via Real-time Capable Encoding (FIERCE)
Award amount
$99,958Program and phase
SBIR · Phase IAward year
2017Award details
- Awarding agency
- Department of Defense
- Branch
- Army
- Recipient company
- CHARLES RIVER ANALYTICS, INC.
- Proposal award date
- 2017-09-01
- Contract end date
- 2018-03-01
- UEI
- DD1BYN8SN355
- Solicitation number
- 2017.1
- Topic code
- A17-046
Research abstract
When a Warfighter navigating a vehicle is immersed in a highly degraded visual environment (HDVE), they lose the critical ability to visually observe their environment. Warfighters that encounter a HDVE typically must halt, exposing themselves to attack, risking a potentially catastrophic delay in delivery of critical supplies, or allowing adversaries to gain intelligence on the operation. To address these challenges, we propose to design and evaluate Fast Image Enhancement via Real-time Encoding (FIERCE), an image enhancement methodology that leverages robust image processing techniques and convex optimization to produce augmented imagery designed specifically so that Warfighters can safely navigate at a minimum speed of 10 m.p.h. through HDVEs.
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.
- Neural Network Enhancements for Customized Reduced Order Models to Accelerate Nuanced COA Evaluation and Reasoning (NECROMANCER)
- Foreign malign influence (FMI) AI-driven Challenge Environment eXperiential Simulation (FACE-X)
- Forecasting Outcomes with Root Cause Evaluation for Fielded Systems (FORCEFIELDS)
- Anthropometry and Pose Observation using Low-dimensional Latent Optimization (APOLLO)
- Robotic Interconnecting Vessels Enabling River-crossing using Sensor Processing and Autonomous Navigation (RIVERSPAN)
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- High-Speed Image Processing in Heavily Degraded Environments Using a Machine Learning Classifier
- High-Speed Image Processing in Heavily Degraded Environments Using a Machine Learning Classifier
Research funding history
961 SBIR/STTR records share this UEI (1984–2026). Reported award amounts total $386,500,110. Reported amounts are not federal obligations.
Phases: Phase I, Phase II, Phase II – Direct to Phase II
Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Health and Human Services, Department of Homeland Security, Department of Transportation, Department of Energy