Turbulence stabilization

Abstract

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.

Figures (8)

• Figure 1: The model of deformation used in the restoration process.
• Figure 2: The first three columns are example frames and the magnification of their top right part. The last column shows our reconstructed result.
• Figure 3: Input examples of the test sequence 1.
• Figure 4: Input examples of the test sequence 2.
• Figure 5: Restored images obtained from the different regularizers (30 input frames). From left to right: NLTV, TV, Framelet, Curvelet.