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Illumination Correction of Multi-Time RGB Images Obtained with an Unmanned Aerial Vehicle L&E, Vol. 29, No. 2, 2021

Light & Engineering 29 (2)

Volume 29
Date of publication 04/22/2021
Pages 50–58

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Illumination Correction of Multi-Time RGB Images Obtained with an Unmanned Aerial Vehicle L&E, Vol. 29, No. 2, 2021
Articles authors:
Michael Yu. Kataev, Maria M. Dadonova, Dmitry S. Efremenko

Michael Yu. Kataev, Doctor of Technical Science. He graduated in 1984 from Tomsk State University as an engineer-researcher in optic. At present, he is a Professor of the Department of Automated Control Systems (ACS) TU-RMS and Professor of Yurginsky Technological Institute (branch) of the Tomsk Polytechnic University (TPU), scientific leadership, and a member of the Earth from Space Monitoring Centre, TUSUR

Maria M. Dadonova, master’s student at the Department of Automated Control Systems (ACS) TUSUR

Dmitry S. Efremenko, Ph. D. He graduated from the Moscow Power Engineering institute (MPEI) in 2009. He received his Ph. D. degree from the Moscow State University in 2011 and the habilitation degree from MPEI in 2017. Since 2011 he works as a Research Scientist at the German Aerospace Centre (DLR). He is a docent at the Technical University of Munich. He has over 70 peer-reviewed publications. His scientific interests include radiate transfer, remote sensing, and machine learning

Abstract:
The goal of this research was to study and optimize multi-temporal RGB images obtained by a UAV (unmanned aerial vehicle). A digital camera onboard the UAV allows obtaining data with a high temporal and spatial resolution of ground objects. In the case considered by us, the object of study is agricultural fields, for which, based on numerous images covering the agricultural field, image mosaics (orthomosaics) are constructed. The acquisition time for each orthomosaic takes at least several hours, which imposes a change in the illuminance of each image, when considered separately. Orthomosaics obtained in different periods of the year (several months) will also differ from each other in terms of illuminance. For a comparative analysis of different parts of the field (orthomosaic), obtained in the same time interval or comparison of areas for different periods of time, their alignment by illumination is required. Currently, the majority of alignment approaches rely rather on colour (RGB) methods, which cannot guarantee finding efficient solutions, especially when it is necessary to obtain a quantitative result. In the paper, a new method is proposed that takes into account the change in illuminance during the acquisition of each image. The general formulation of the problem of light correction of RGB images in terms of assessing the colour vegetation index Greenness is considered. The results of processing real measurements are presented.
References:
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