Abstract
Rain and snow contain particles generated by different physical and chemical processes. Weather radars send directional pulses of microwave radiation, on the order of a microsecond long. Between each pulse, the radar station serves as a receiver as it listens for return signals from particles in the air. This is the measurement principle of microwave weather (meteorological) radar. Limited by the information processing capability, the weather radar data published by the meteorological website often have a large time interval, such as 6 min. Video frame interpolation technology has made great progress in recent years with the development of deep learning technology. The frame interpolation of weather radar charts will bring users more accurate weather descriptions and more intuitive decision-making references. This paper propose a novel video frame interpolation algorithm for weather radar data, which is able to generate the intermediate frames between the frames at the sampling time.
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This work is financially supported by the National Key R &D Program of China, Project Number 2018YFE0208700.
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Ge, H., Chen, X., Tian, Y., Ding, H., Chen, P., Wakolo, F.K. (2023). Frame Interpolation for Weather Radar Data. In: Liang, Q., Wang, W., Mu, J., Liu, X., Na, Z. (eds) Artificial Intelligence in China. AIC 2022. Lecture Notes in Electrical Engineering, vol 871. Springer, Singapore. https://doi.org/10.1007/978-981-99-1256-8_25
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DOI: https://doi.org/10.1007/978-981-99-1256-8_25
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