Clouds segmentation on panchromatic high spatial resolution remote sensing images using convolutional neural networks

V. Eremeev; A. Kuznetcov; A. Kochergin; A. Makarenkov

doi:10.1117/12.2536410

7 October 2019 Clouds segmentation on panchromatic high spatial resolution remote sensing images using convolutional neural networks

V. Eremeev, A. Kuznetcov, A. Kochergin, A. Makarenkov

Author Affiliations +

Proceedings Volume 11155, Image and Signal Processing for Remote Sensing XXV; 111552E (2019) https://doi.org/10.1117/12.2536410
Event: SPIE Remote Sensing, 2019, Strasbourg, France

Abstract

In the paper is described clouds segmentation algorithm based on convolutional neural network. It has been made an analysis of existed convolutional neural networks topologies and it was made a decision of using the modifying U-Net topology. The preliminary data processing has been made taking into account a source data specific. Learning dataset has been made using real high spatial resolution remote sensing data and manual segmented clouds mask. Methodology of using learning dataset in network learning process has been proposed. Results of learned network implementation on real data are shown in the paper.

Citation Download Citation

V. Eremeev, A. Kuznetcov, A. Kochergin, and A. Makarenkov "Clouds segmentation on panchromatic high spatial resolution remote sensing images using convolutional neural networks", Proc. SPIE 11155, Image and Signal Processing for Remote Sensing XXV, 111552E (7 October 2019); https://doi.org/10.1117/12.2536410

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