Statistical properties of image pixel brightness from the onboard optical location system

Main Article Content

Andrei Sergeevich Solonar
Sergei Viktorovich Tsuprik
Petr Aleksandrovich Khmarski

Abstract

The statistical properties of image pixel brightness were investigated to provide a rationale for the choice of the necessary mathematical image model. Video recordings of the ground situation, obtained from the onboard optical-location system of an unmanned aerial vehicle, were generated and analyzed. The requirements for a mathematical model of brightness under ground-based background-target conditions were formulated. Based on these requirements, a semi-Markov model of brightness with Poisson moments of transition from one state to another was proposed to describe pixel brightness. The adequacy of the proposed model in describing pixel brightness has been verified.

Downloads

Download data is not yet available.

Article Details

How to Cite
Solonar, A. S., Tsuprik, S. V., & Khmarski, P. A. (2023). Statistical properties of image pixel brightness from the onboard optical location system . Advanced UAV, 3(2), 142–152. Retrieved from https://publish.mersin.edu.tr/index.php/uav/article/view/1173
Section
Articles

References

Ali, B., Sadekov, R. N., & Tsodokova, V. V. (2022). A review of navigation algorithms for unmanned aerial vehicles based on computer vision systems. Gyroscopy and Navigation, 13(4), 241-252. https://doi.org/10.1134/S2075108722040022

Artemiev, V. M., Naumov, A. O., & Kohan, L. L. (2014). Image processing in passive survey and search optoelectronic systems. Minsk, Belaruskaya navuka. ISBN 978-985-08-1657-3

Artemiev V. M., Naumov A. O., & Kohan L. L. (2010). Point objects detection in the case of uncertainty. Informatika = Informatics, 2, 15–24.

Mueller, K., Atman, J., & Trommer, G. F. (2019). Combination of wide baseline image matching and tracking for autonomous uav approaches to a window. Gyroscopy and Navigation, 10, 206-215. https://doi.org/10.1134/S2075108719040138

Hecker, P., Angermann, M., Bestmann, U., Dekiert, A., & Wolkow, S. (2019). Optical aircraft positioning for monitoring of the integrated navigation system during landing approach. Gyroscopy and Navigation, 10, 216-230. https://doi.org/10.1134/S2075108719040084

Solonar, A. S., & Khmarski, P. A. (2021). Main problems of trajectory processing and approaches to their solution within the framework of multitarget tracking. In Journal of Physics: Conference Series, 1864(1), 012004. https://doi.org/10.1088/1742-6596/1864/1/012004

Solonar, A. S., Khmarskiy, P. A., Mihalkovskiy, A. A., & Tsuprik, S. V. (2018). Features of trajector measurement coordinates and parameters of movement of ground objects in on-board optical-location systems. In 2018 25th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS), 1-5. https://doi.org/10.23919/ICINS.2018.8405853

Farina, A, & Studer, F. A. (1985) Radar data processing: Vol. 1 – Introduction and tracking. ISBN 0863800262.

Kosachev, I. M., Nefedov, D. S. (2015). Methods of calculation of reability and accuracy indicators of the estimated tactical and technical characteristics of weapons, military and special equipment. Vest. Military Academy, Republic of Belarus, 1, 107–134.

Solonar, A. S., Tsuprik, S. V., & Khmarski, P. A. (2023). Semi-Markov model of brightness change of the ground object image formed by the optical-location system. Vest. Military Academy, Republic of Belarus, 1, 97 – 107.

Akhloufi, M. A., Castro, N. A., & Couturier, A. (2018). UAVs for wildland fires. In Autonomous systems: Sensors, vehicles, security, and the Internet of Everything, 10643, 134-147. https://doi.org/10.1117/12.2304834

Jordan, S., Moore, J., Hovet, S., Box, J., Perry, J., Kirsche, K., ... & Tse, Z. T. H. (2018). State‐of‐the‐art technologies for UAV inspections. IET Radar, Sonar & Navigation, 12(2), 151-164. https://doi.org/10.1049/iet-rsn.2017.0251

Scherer, J., Yahyanejad, S., Hayat, S., Yanmaz, E., Andre, T., Khan, A., ... & Rinner, B. (2015, May). An autonomous multi-UAV system for search and rescue. In Proceedings of the First Workshop on Micro Aerial Vehicle Networks, Systems, and Applications for Civilian Use, 33-38. https://doi.org/10.1145/2750675.2750683

Mittal, M., Mohan, R., Burgard, W., & Valada, A. (2019). Vision-based autonomous UAV navigation and landing for urban search and rescue. In the International Symposium of Robotics Research, 575-592. https://doi.org/10.1007/978-3-030-95459-8_35

Lu, Y., Xue, Z., Xia, G. S., & Zhang, L. (2018). A survey on vision-based UAV navigation. Geo-spatial Information Science, 21(1), 21-32. https://doi.org/10.1080/10095020.2017.1420509

Schleiss, M. (2019). Translating aerial images into street-map-like representations for visual self-localization of UAVs. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 575-580. https://doi.org/10.5194/isprs-archives-XLII-2-W13-575-2019.

Silva Filho, P., Shiguemori, E. H., & Saotome, O. (2017). UAV visual autolocalizaton based on automatic landmark recognition. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 4, 89-94. https://doi.org/10.5194/isprs-annals-IV-2-W3-89-2017

Saranya, K. C., Naidu, V. P. S., Singhal, V., & Tanuja, B. M. (2016). Application of vision-based techniques for UAV position estimation. International Conference on Research Advances in Integrated Navigation Systems (RAINS), 1-5. https://doi.org/10.1109/RAINS.2016.7764392

Masselli, A., Hanten, R., & Zell, A. (2016). Localization of unmanned aerial vehicles using terrain classification from aerial images. In Intelligent Autonomous Systems 13: Proceedings of the 13th International Conference IAS-13, 831-842. https://doi.org/10.1007/978-3-319-08338-4_60

Kwiatkowski, D., Phillips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?. Journal of Econometrics, 54(1-3), 159-178. https://doi.org/10.1016/0304-4076(92)90104-Y

Solonar, A. S., Tsuprik, S. V., & Khmarskiy, P. A. (2023). Statistical properties of image pixel brightness from the onboard optical system. Advanced Engineering Days (AED), 7, 172-174.