Atmospheric Correction of Satellite Images Using a Neural Network

During remote sensing of the Earth, satellite equipment registers solar radiation reflected by the Earth’s surface. This reflected radiation travels through the atmosphere, distorting the spectral characteristics of the radiation that would reach the satellite’s sensors. The task of atmospheric correction is to eliminate the influence of these distortions. The paper proposes a method for correcting satellite images using a simple neural network with an encoder-decoder architecture. This method allows for automation of the process of atmospheric correction for “raw” satellite images.