Abstract
Spectral imaging has a wide range of applications, like remote sensing or biomedical imaging. In recent years, with the increasing use of unmanned aerial vehicles (UAVs), it is common to attach a spectral camera to an UAV to acquire information. Unfortunately, the spectral cameras used with UAV are expensive. Therefore this work proposes a low-cost optical architecture to acquire spectral images. The proposed architecture takes advantage of the UAV movement to spectral imaging. The proposed optical architecture is composed of two arms, one has an RGB camera, and the other a single-pixel spectrometer. The results show that depending on the sensing conditions selected, it is possible to retrieve high-quality spectral images. Simulation results show that the proposed architecture improves image quality in terms of PSNR compared with an RGB camera and the single-pixel camera (SPC), up to 1.31 dB and 20.44 dB respectively, also obtained a performance similar to an architecture that combine the SPC and RGB, and even besting it improving the quality of the image in terms of PSNR up to 0.49 dB. Moreover, the optical architecture proposed has the advantage of reducing the amount of sensed information in comparison to SPC and SPC + RGB; also, the implementation costs are reduced drastically because the proposed architecture does not use a digital micromirror device (DMD) to codify the incoming scene, which is the case of the SPC and SPC + RGB architectures.
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Acknowledgment
This work was supported by the investigation center Centro TIC with financial support of the vicerrectoria de investigación y extención of the Universidad Industrial de Santander through the project “Plataforma IoT para el Desarrollo de Servicios Inteligentes de Apoyo al Monitoreo Ambiental”.
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Guarin, A., Ortega, H., Garcia, H. (2019). Acquisition System Based in a Low-Cost Optical Architecture with Single Pixel Measurements and RGB Side Information for UAV Imagery. In: Orjuela-Cañón, A., Figueroa-García, J., Arias-Londoño, J. (eds) Applications of Computational Intelligence. ColCACI 2019. Communications in Computer and Information Science, vol 1096. Springer, Cham. https://doi.org/10.1007/978-3-030-36211-9_13
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DOI: https://doi.org/10.1007/978-3-030-36211-9_13
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