Estimating Apparent Motion on Satellite Acquisitions with a Physical Dynamic Model
Estimating Apparent Motion on Satellite Acquisitions with a Physical Dynamic Model
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使用物理动态模型估计卫星捕获的表观运动
DOI：
10.1109/icpr.2010.19
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
E. Plotnikov
中科院分区：
文献类型：
--
作者：
E. Huot;I. Herlin;Nicolas Mercier;E. Plotnikov
本文提出了一种基于动态模型（称为图像模型）中数据同化的运动估计方法，该模型表达了图像上观察到的量的物理演变。该应用程序涉及检索的表观表面速度从一系列的卫星数据，获得了海洋。图像模型包括速度场动态的浅水近似（两个运动分量的演变由水层厚度联系起来）和图像场的传输方程。为了反演海面速度，一系列的海表温度（SST）收购同化的图像模型与4D-Var方法。这是基于成本函数的最小化，包括模型输出和SST数据之间的差异和正则化项。已经研究了几种类型的正则化范数。结果进行了讨论，分析同化系统的不同组成部分的影响。
The paper presents a motion estimation method based on data assimilation in a dynamic model, named Image Model, expressing the physical evolution of a quantity observed on the images. The application concerns the retrieval of apparent surface velocity from a sequence of satellite data, acquired over the ocean. The Image Model includes a shallow-water approximation for the dynamics of the velocity field (the evolution of the two components of motion are linked by the water layer thickness) and a transport equation for the image field. For retrieving the surface velocity, a sequence of Sea Surface Temperature (SST) acquisitions is assimilated in the Image Model with a 4D-Var method. This is based on the minimization of a cost function including the discrepancy between model outputs and SST data and a regularization term. Several types of regularization norms have been studied. Results are discussed to analyze the impact of the different components of the assimilation system.