Content
Abstract:
An approach to the construction of a hyperspectral system is proposed and justified, providing control of spectral, spatial, and radiometric (brightness) resolution, which opens up the possibility of hyperspectral monitoring of objects with limited computing resources and bandwidth of the video data transmission channel. Spectral resolution control is supposed to be carried out on the basis of tuneable, software-controlled acousto-optic filters, spatial resolution control – based on modern CMOS matrix technologies with the “active pixel” function, digitalization control of the images obtained – based on the developed analogy-to-digital converter with tuneable quantization level. Modelling using experimental data has shown the possibility of implementing a sufficiently reproducible classification of hyperspectral images with a decrease in their spectral, spatial, and radiometric resolutions.
References:
1. Vinogradov, A.N., Egorov, V.V., Kalinin, A.P., Rodionov, A.I., Rodionov, I.D. Line of aviation hyper-spectrometers of the ultraviolet, visible, and near infrared ranges // Optical Journal, 2016, Vol. 88, # 4, pp. 54–62. 2. Pozhar, V.E., Machikhin, A.S., Gaponov, M.I., Shirokov, C.V., Mazur, M.M., Sheryshev, A.E. Hyper-spectrometer Based on an Acousto-Optic Tuneable Filters for UAVS // Light & Engineering J. 2019, # 4, pp. 47–50. 3. Mazur, M.M., Pozhar, V.E. Spectrometers on acousto-optic filters // Measuring technique, 2015, # 9, pp. 29–33. 4. Mazur, M.M., Suddenok, Yu.A., Pozhar, V.E. Multi-window acousto-optic filters for correlation spectroscopy // Optics and spectroscopy J. 2020, Vol. 128, # 2, pp. 284–289. 5. Pozhar, V.E., Velikovsky, D. Yu. Spectral recognition of objects using multi-window acousto-optic filters // Optics and spectroscopy, 2020, Vol. 128, # 7, pp. 1035–1041. 6. Gorbachev, A.A., Korotaev, V.V., Yaryshev, S.N. Solid-state matrix photo converters and cameras based on them / St. Petersburg: ITMO Research Institute, 2013, 98 p. 7. Balakshiy, V.I., Parygin, V.N., Chirkov, L.E. Physical foundations of acoustic optics / Moscow: Radio and Communications, 1985, 279 p. 8. Wu, H., Haibach, F.G., Bergles, E., Qian, J., Zhang, Ch., Yang, W. Miniaturized handheld hyperspectral imager // Proc. SPIE, 2014, Vol. 9101, 91010W. 9. Hu, P., Lu, Q., Shu, R., Wang, J. An airborne push broom hyperspectral imager with wide field of view // Chinese optics letters, 2005, Vol. 3, # 12, pp. 689–691. 10. Saari, H., Pölönen, I., Salo, H., et al. Miniaturized hyperspectral imager calibration and UAV flight campaigns // 2013, Proc. SPIE, Vol. 8889, 88891O. 11. Lucey, P.G., Akagi, J.T., Hinrichs. J.L., Crites, S.T., Wright, R. A long-wave infrared hyperspectral sensor for Shadow class UAVs // Proc. SPIE, 2013. V. 8713, 87130D. 12. Downing, J., Harvey, A.R. Multi-aperture hyperspectral imaging // OSA Technical Digest (online) (Optical Society of America, 2013) https://doi.org/10.1364/AIO.2013.JW2B.2. 13. Mitchell, P.A. Hyperspectral digital imagery collection experiment HYDICE // Proc. SPIE, 1995, Vol. 2587, pp. 70–95. 14. https://aviris.jpl.nasa.gov/aviris (2022). 15. Berezin, V.V., Umbitaliev, A.A., Fahmi, S.S., Tsitsulin, A.K., N.N. Shipilov, N.N. Edited by Umbita liev A.A. and Tsitsulin, A.K. Solid-state revolution in television: Television parameters based on charge-coupled devices, systems on a crystal and video systems on a crystal / Moscow: Radio and communication, 2006. 16.Yakubovsky, S.V., Nisselson, L.I., Kuleshova, V.I., et al.; edited by Yakubovsky, S.V. Digital and analog integrated circuits: Handbook / Moscow: Radio and Communications, 1990. 496p. 17. Brindley, K., Carr, J. Pocket handbook of an electronic engineering engineer / Translated from English 2nd ed., ster. Moscow: Publishing House “Dodeka–XXI”, 2005, 480 p. 18. Del Aguila, A., Efremenko, D.S., Trautmann, T. A Review of Dimensionality Reduction Techniques for Processing Hyper-Spectral Optical Signal // Light & Engineering J. 2019, # 3. pp. 85–98. 19. Borzov, S.M., Potaturkin O.I. The choice of an informative system of features in the classification of agricultural crops by hyperspectral data // Autometry, 2020, Vol. 56, # 4, pp. 134–144.
Keywords
- hyperspectral system
- analogueto-digital converter
- acousto-optic filter
- photodetector
- mathematical modelling
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