Power laws and inverse motion modelling: application to turbulence measurements from satellite images
Power laws and inverse motion modelling: application to turbulence measurements from satellite images
复制标题
DOI：
10.3402/tellusa.v64i0.10962
复制
发表时间：
2012-01-01
影响因子：
2
通讯作者：
Mininni, Pablo D.
中科院分区：
文献类型：
--
作者：
Heas, Patrick;Memin, Etienne;Mininni, Pablo D.
在处理图像序列运动估计的病态逆问题的背景下，我们建议引入由湍流统计模型给出的关于流动规律的先验知识。先验正则性是使用湍流功率定律来形式化的，该定律描述了跨尺度运动增量的统计自相似结构。该运动估计方法使图像观测模型的误差最小化，同时约束二阶结构函数在规定的范围内表现为幂定律。多亏了贝叶斯建模框架，运动估计方法能够直接从图像数据联合推断最可能的幂定律。该方法在二维或准二维流的速度场上进行了评估。首先对均匀和各向同性二维湍流的合成图像序列的估计精度进行了评估。用基于流体物理的方法获得的结果超过了最先进的水平。然后，该方法使用真实的气象图像序列来分析大气湍流。选择最可能的幂定律模型可以恢复物理量，这是湍流大气特征的主要兴趣。特别是，从气象图像中我们能够估计出湍流叶栅的能量通量和拟能通量，这与以前的现场测量结果是一致的。
In the context of tackling the ill-posed inverse problem of motion estimation from image sequences, we propose to introduce prior knowledge on flow regularity given by turbulence statistical models. Prior regularity is formalised using turbulence power laws describing statistically self-similar structure of motion increments across scales. The motion estimation method minimises the error of an image observation model while constraining second-order structure function to behave as a power law within a prescribed range. Thanks to a Bayesian modelling framework, the motion estimation method is able to jointly infer the most likely power law directly from image data. The method is assessed on velocity fields of 2-D or quasi-2-D flows. Estimation accuracy is first evaluated on a synthetic image sequence of homogeneous and isotropic 2-D turbulence. Results obtained with the approach based on physics of fluids outperform state-of-the-art. Then, the method analyses atmospheric turbulence using a real meteorological image sequence. Selecting the most likely power law model enables the recovery of physical quantities, which are of major interest for turbulence atmospheric characterisation. In particular, from meteorological images we are able to estimate energy and enstrophy fluxes of turbulent cascades, which are in agreement with previous in situ measurements.