Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/60199
Title: A Simulation Environment for Validation and Verification of Real Time Hyperspectral Processing Algorithms on-Board a UAV
Authors: Horstrand, Pablo
López Feliciano, José Francisco 
López Suárez, Sebastián 
Leppalampi, Tapio
Pusenius, Markku
Rooker, Martijn
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: simulation environment
hyperspectral imagery
UAV
anomaly detection
Issue Date: 2019
Journal: Remote Sensing 
Abstract: The utilization of hyperspectral imaging sensors has gained a significant relevance among many different applications due to their capability for collecting a huge amount of information across the electromagnetic spectrum. These sensors have been traditionally mounted on-board satellites and airplanes in order to extract information from the Earth's surface. Fortunately, the progressive miniaturization of these sensors during the last lustrum has enabled their use in other remote sensing platforms, such as drones equipped with hyperspectral cameras which bring advantages in terms of higher spatial resolution of the acquired images, more flexible revisit times and lower cost of the flight campaigns. However, when these drones are autonomously flying and taking real-time critical decisions from the information contained in the captured images, it is crucial that the whole process takes place in a safe and predictable manner. In order to deal with this problem, a simulation environment is presented in this work to analyze the virtual behavior of a drone equipped with a pushbroom hyperspectral camera used for assisting harvesting applications, which enables an exhaustive and realistic validation and verification of the drone real-time hyperspectral imaging system prior to its launch. To the best of the authors' knowledge, the proposed environment represents the only solution in the state-of-the-art that allows the virtual verification of real-time hyperspectral image processing algorithms under realistic conditions.
URI: http://hdl.handle.net/10553/60199
ISSN: 2072-4292
DOI: 10.3390/rs11161852
Source: Remote Sensing,v. 11 (16)
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