Reconstruction and visualization of 3D wind fields from satellite image sequences

In this paper, we address the problem of estimating and visualizing 3D atmospheric motion using top of cloud pressure image sequences. The reconstruction of 3D fluid motion from a monocular sequence of image observations is a very challenging problem for which no solution exists in the literature. Based on a physically sound vertical decomposition of the atmosphere into layers of different pressure interval, we propose here a dense motion estimator dedicated to the extraction of three-dimensional wind fields characterizing the dynamics of a layered atmosphere. Wind estimation is performed using a multi-layer model describing a stack of dynamic horizontal layers, interacting at their boundaries via vertical winds. Furthermore, a 3D graphical interface is proposed to visualize the horizontal and vertical components of the displacement of each layer. The wind fields are displayed in a physical 3D coordinate system. This system is deduced from pixel coordinates and altitudes estimated from the top of cloud temperature images. Smooth surfaces defining layer vertical boundaries are reconstructed through an altitude extrapolation scheme. An evaluation of the system is performed with Météosat image sequences of top of cloud pressure.