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.

翻译：我们最近提出了一种新方法，用于从大气湍流条件下获取的帧序列中重建稳定图像。该算法的目标在于消除由大气运动引起的几何畸变。该方法基于变分公式构建，并通过Bregman迭代与算子分裂法实现高效求解。本文旨在研究模型中正则化项选择的影响，进而对文献中常用的若干正则化约束条件进行实验验证。