Image segmentation of clouds based on deep learning

Abstract

The paper is devoted to the development of the methods for segmentation of images of atmospheric clouds, which are obtained by remote sensing methods using aircraft or satellite onboard systems. The proposed approach is some extent further improvement of the convolutional neural network of the U-net type. The uses known quality criteria for segmentation, which allows us to compare the proposed approach with already known methods in the field of segmentation of images of atmospheric clouds. A large number of experiments on real images shows the feasi-bility of using the proposed method of segmentation for automated processing with the require-ments for real-time operation. Applied use of the results is possible in the tasks of monitoring and classification for weather forecasting, agriculture, and other areas related to observations of atmospheric clouds.