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

  • Sara Freitas
  • Hugo Silva
  • José Almeida
  • Eduardo Silva
Open Access


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.


Unmanned aerial vehicles Hyperspectral imaging Surveillance Target detection Computer vision 



The authors would like to thank the Portuguese Air Force and the Portuguese Navy for providing the UAV and the boats for the data collection. The authors would also like to thank SPECIM and XENICS for providing the Hyperspectral camera and the IR camera for the payload used in this dataset campaign. This work is financed by the ERDF - European Regional Development Fund through the Operational Program for Competitiveness and Internationalization - COMPETE 2020 Program within project POCI-01-0145-FEDER-006961, by the SUNNY Project funded by the European Commission under the FP7 program Grant Agreement number: 313243, and by National Funds through the FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013.


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© The Author(s) 2017

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Sara Freitas
    • 1
  • Hugo Silva
    • 1
  • José Almeida
    • 2
  • Eduardo Silva
    • 2
  1. 1.INESC TECPortoPortugal
  2. 2.INESC TEC, Instituto Superior de Engenharia do PortoPortoPortugal

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