Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 1
Articles | Volume 14, issue 1
https://doi.org/10.5194/amt-14-737-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-737-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 1
Research article
 | 
29 Jan 2021
Research article |  | 29 Jan 2021

Improving cloud type classification of ground-based images using region covariance descriptors

Yuzhu Tang, Pinglv Yang, Zeming Zhou, Delu Pan, Jianyu Chen, and Xiaofeng Zhao

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Short summary
An automatic cloud classification method on whole-sky images is presented. We first extract multiple pixel-level features to form region covariance descriptors (RCovDs) and then encode RCovDs by the Riemannian bag-of-feature (BoF) method to output the histogram representation. Reults show that a very high prediction accuracy can be obtained with a small number of training samples, which validate the proposed method and exhibit the competitive performance against state-of-the-art methods.
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