Hyperspectral Imaging for Real-Time Unmanned Aerial Vehicle Maritime Target Detection

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Abstract

This work address hyperspectral imaging systems use for maritime target detection using unmanned aerial vehicles. Specifically, by working in the creation of a hyperspectral real-time data processing system pipeline. We develop a boresight calibration method that allows to calibrate the position of the navigation sensor related to the camera imaging sensor, and improve substantially the accuracy of the target geo-reference. We also develop an unsupervised method for segmenting targets (boats) from their dominant background in real-time. We evaluated the performance of our proposed system for target detection in real-time with UAV flight data and present detection results comparing favorably our approach against other state-of- the-art method.

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Freitas, S., Silva, H., Almeida, J., & Silva, E. (2018). Hyperspectral Imaging for Real-Time Unmanned Aerial Vehicle Maritime Target Detection. Journal of Intelligent and Robotic Systems: Theory and Applications, 90(3–4), 551–570. https://doi.org/10.1007/s10846-017-0689-0

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