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We demonstrate a supercontinuum-based hyperspectral laser scanning technique that provides high-precision distance measurements of natural surfaces along with their reflectance signature over the broad spectral range of the supercontinuum (SC) output. The SC used in our experiments is spectrally broadened to 570-970 nm from a 780 nm mode-locked femtosecond laser. Distance measurements are carried out by monitoring the differential phase delay of the intermode beat notes obtained from direct photodetection of the SC, while the backscattered reflection spectrum is acquired using a commercial spectrometer. We achieve a single-point range precision below 10 μm on natural targets (gypsum board and leaves of a plant used herein) placed at a stand-off distance of 5 m. Our results demonstrate the acquisition of hyperspectral point clouds together with sub-mm range noise on the scanned surface. This range performance is comparable to commercial state-of-the-art terrestrial laser scanners which traditionally employ a monochromatic laser source.We show the benefit of enhanced range precision toward correctly estimating the surface orientation and for radiometric calibration of the acquired intensities. Initial results illustrate the direct 3D mapping of spectral data of plant leaves with a reduced angle of incidence-related bias, highlighting new opportunities for future research into remote sensing of vegetation.
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(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Pabitro Ray,David Salido-Monzú,Andreas Wieser, andTomislav Medić
"Supercontinuum-based hyperspectral laser scanning: towards enhanced 3D surface reconstruction and its benefits for remote sensing", Proc. SPIE 12621, Multimodal Sensing and Artificial Intelligence: Technologies and Applications III, 126210M (9 August 2023); https://doi.org/10.1117/12.2673800
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Pabitro Ray, David Salido-Monzú, Andreas Wieser, Tomislav Medić, "Supercontinuum-based hyperspectral laser scanning: towards enhanced 3D surface reconstruction and its benefits for remote sensing," Proc. SPIE 12621, Multimodal Sensing and Artificial Intelligence: Technologies and Applications III, 126210M (9 August 2023); https://doi.org/10.1117/12.2673800