Motion estimation on meteorological infrared data using a total brightness invariance hypothesis

This work investigates a novel approach for cloud motion wind (CMW) estimation of Meteosat infrared images. It is motivated by the fact that variational techniques, such as those employed for computing the optical flow, are successfully applied to many computer vision applications but fail in this particular applicative context, mainly because optical flow techniques are adapted to rigid objects on visible data. The objective of this work is not to propose a full operational process for CMW estimation, but rather to improve optical flow techniques by applying constraints adapted to the specificity of meteorological infrared imagery.