Optical-flow for 3D atmospheric motion estimation

In this paper, we address the problem of estimating three-dimensional motions of a stratified atmosphere from satellite image sequences. The complexity of three-dimensional atmospheric fluid flows associated to incomplete observation of atmospheric layers due to the sparsity of cloud systems makes very difficult the estimation of dense atmospheric motion field from satellite images sequences. The recovery of the vertical component of 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 altitudes, 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 over the complete three-dimensional space using a multi-layer model describing a stack of dynamic horizontal layers of evolving thickness, interacting at their boundaries via vertical winds. The efficiency of our approach is demonstrated on synthetic and real sequences.