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.
Highlights
Hyperspectral imaging technology has gained momentum over the last years because of its capability for providing abundant spectral information that allows discover subtle differences of the scene that cannot be uncovered with other optical devices
The virtual environment developed in this work offers the possibility of simulating and stimulating the sensor, virtually creating hyperspectral images as they are captured by the targeted hyperspectral sensor and applying the processing algorithms to them in order to obtain the results straight away
In order to minimize the risk of fatal accidents due to agricultural mowing operations and/or collisions with big obstacles, the scheme shown in Figure 2 has been considered, in which the drone flies at a certain height above ground, and some meters ahead of the harvester scanning the field for the possible appearance of static or dynamic objects
Summary
Hyperspectral imaging technology has gained momentum over the last years because of its capability for providing abundant spectral information that allows discover subtle differences of the scene that cannot be uncovered with other optical devices. The algorithm development process starts with a design phase consisting of analysing the target application needs and defining a few possible solutions, followed by the implementation phase where the solution is coded into a high level language to rapidly have results available and start looking for the most suitable solution This latter phase is carried out offline, with synthetic or real hyperspectral images downloaded from public repositories. The work uncovered in this paper is based on using a pushbroom hyperspectral camera, that presently constitutes one of the most widely chosen sensors to be mounted on a UAV [8,9] due to its trade off between spatial and spectral resolution The integration of this type of camera into a UAV is a rather complex task since the captured frames are individual lines that share no overlapping, and much more effort has to be put into the acquisition and processing stages, in order to generate a 2D image
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