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Weather Radar Echo Super-Resolution Reconstruction Based on Nonlocal Self-Similarity Sparse Representation

1,2, 1,2, 1,2,* and 1,2
1
College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China
2
CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225, China
*
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(5), 254; https://doi.org/10.3390/atmos10050254
Received: 1 April 2019 / Revised: 2 May 2019 / Accepted: 6 May 2019 / Published: 8 May 2019
(This article belongs to the Section Climatology and Meteorology)
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Abstract

Weather radar echo plays an important role in early warning and timely forecasting of severe weather. However, the radar echo may not be accurate enough to predict or analyze small-scale weather phenomenon due to the degradation of the observed radar. In order to solve this problem, some radar echo super-resolution reconstruction algorithms have been proposed, but the algorithm may result in an excessively smooth edge and detail in a local region. To reconstruct radar echo with better edges and finer details, a novel nonlocal self-similarity sparse representation (NSSR) model is proposed. The NSSR model is based on the sparse representation of weather radar echoes to better reconstruct the echo edge and detail information. We exploit the radar echo nonlocal self-similarity to recover more realistic details based on the NSSR model. Experiment results demonstrate that the proposed NSSR outperforms current general-purpose radar echo super-resolution approaches on both visual effects and objective radar echo quality. View Full-Text
Keywords: super-resolution; sparse representation; weather radar; nonlocal self-similarity super-resolution; sparse representation; weather radar; nonlocal self-similarity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Zhang, X.; He, J.; Zeng, Q.; Shi, Z. Weather Radar Echo Super-Resolution Reconstruction Based on Nonlocal Self-Similarity Sparse Representation. Atmosphere 2019, 10, 254.

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