Paper
17 May 2019 Minor area motion imagery sensor data fusion of electro-optical/infrared airborne imagery for basic research
Author Affiliations +
Abstract
Sensor level data fusion allows us to produce more consistent and accurate tracking information from available imagery and cyber data. This paper discusses the approaches we have taken to implement sensor fusion of Electro-Optical and Infrared airborne imagery. Before any sensor fusion is done, the data is processed to generate object detections and a tracking algorithm is utilized to track objects of interest. Possible detections includes vehicles, dismounts, noise, clutter, and unidentified objects. One of the main reasons for sensor fusion of EO and IR imagery is the opportunity to use complimentary information from different sensors especially when detections are incorrect or missed by the tracking algorithm. EO/IR imagery sensor fusion will allow us generate new detection locations for skipped targets and “align” detections in instances where registration fails. In this paper real data analyzed and sensor fusion is performed for two scenarios; when both the EO and IR detections are present or if one of the two is missed by the tracking algorithm.
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Bala Konate, James Graham, and Igor Ternovskiy "Minor area motion imagery sensor data fusion of electro-optical/infrared airborne imagery for basic research", Proc. SPIE 11011, Cyber Sensing 2019, 110110J (17 May 2019); https://doi.org/10.1117/12.2521166
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KEYWORDS
Sensors

Image fusion

Infrared sensors

Infrared imaging

Detection and tracking algorithms

Sensor fusion

Data fusion

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