Turbulence stabilization
This is an incremental study for improving image stabilization in atmospheric turbulence applications.
The paper investigates how different regularization terms affect a variational method for stabilizing images distorted by atmospheric turbulence, testing several established constraints from the literature.
We recently developed a new approach to get a stabilized image from a sequence of frames acquired through atmospheric turbulence. The goal of this algorihtm is to remove the geometric distortions due by the atmosphere movements. This method is based on a variational formulation and is efficiently solved by the use of Bregman iterations and the operator splitting method. In this paper we propose to study the influence of the choice of the regularizing term in the model. Then we proposed to experiment some of the most used regularization constraints available in the litterature.