Abstract
Abstract3D visualization of meteorological radar data can not only reflect the basic characteristics of atmospheric motion and clouds spatial distribution, but also help forecasters predict weather changes more efficiently and accurately. The cone information obtained by radar has the features of sparse, discrete, uneven and irregular distribution, which will lead roughly drawn in the process of 3D rendering due to less triangular surfaces. In this paper, a surface drawing method including Point Cloud Completion and improved Poisson Surface reconstruction was proposed to implement high quality radar data surface drawing. Firstly, the skills of Point Cloud was introduced to complete irregular and scattered sparse cloud data, mathematical models were established for different types of echo data, and corresponding completion was investigated to fill the missing spatial data. Secondly, the improved Poisson Surface Reconstruction based on bilateral filtering (BPSR) was used to render the 3D surface data after completion to make 3D visualization more realistic. Experiments showed that the proposed method could well complete and plot irregular meteorological radar data, the data were more denser after processing with the Point Cloud Completion, and the BPSR improved the efficiency and fineness and realized higher reconstruction quality.KeywordsPoint cloud completionPoisson surface reconstruction3D visualizationMeteorological radar data
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