基于小波域高斯尺度混合模型的天气雷达图像高分辨率插值

High resolution interpolation for weather radar data based on Gaussian-scale mixtures model in wavelet domain

中文关键词:  雷达回波强度数据  小波系数  高斯尺度混合模型  插值

英文关键词:Radar reflectivity data  Wavelet coefficients  Gaussian-scale mixtures (GSM) model  Interpolation

中文摘要:

      采用可精确刻画雷达回波强度数据统计特征的小波域高斯尺度混合（GSM）模型作为雷达图像先验模型，进行天气雷达图像插值，在提高图像分辨率的同时有效重建降水回波中局部强回波值、小尺度变化细节等一些重要空间分布统计特征。分析和总结雷达回波强度数据小波频率域统计特点，建立小波域GSM模型；匹配天气雷达图像小波系数和GSM模型，利用贝叶斯理论估计更小尺度的小波系数，进行小波逆变换，完成高分辨率天气雷达图像插值。试验表明，该算法能从低分辨率图像中估计出高分辨率高频系数，且所利用的先验模型充分考虑降水数据本身的特点，可有效捕获降水回波结构的非高斯特征和局部相关特性，重建雷达图像中的局部变化细节。

英文摘要:

      An interpolation algorithm for radar reflectivity data is proposed using the Gaussian-scale mixtures (GSM) in the wavelet domain as the prior model, which can accurately describe the statistical characteristics of radar precipitation reflectivity data. The objective is to improve the radar image resolution while effectively reproduce those important spatial statistical characteristics of the precipitation echoes like local extreme intensity values and small scale variation gradient. Firstly, the statistical characteristics of radar precipitation reflectivity data in the wavelet domain are analyzed and the reflectivity data are modeled with the GSM. Then, the wavelet coefficients of the radar reflectivity data are matched with the GSM in the wavelet domain, and the wavelet coefficients at smaller scale are estimated by Bayesian theory. The high resolution radar reflectivity image can be recovered from inverse wavelet transform of the estimated coefficients at smaller scale. The case study shows that the proposed algorithm can get the high frequency coefficients of the high resolution images through the parameters estimations of low resolution images and the model used considers the statistical characteristics of precipitation reflectivity data; the interpolation result can capture the non-Gaussian singularities and local correlated features of the precipitation echoes, and the local details of the high resolution radar reflectivity images can be well reproduced.