通过变分方法与迭代优化，有效去除大气湍流造成的图像几何畸变。
Turbulence stabilization
- 基于变分模型与Bregman迭代求解，实现图像稳定化。
- 实验对比了多种正则化项对去畸变效果的影响。
- 适用于天文观测、遥感等受大气扰动影响的成像场景。
我们近期提出一种新方法，从经由大气湍流采集的图像序列中恢复出稳定图像。该算法旨在消除大气运动引起的几何畸变。方法基于变分框架，并利用Bregman迭代和算子分裂法高效求解。本文研究了正则化项选择对模型性能的影响，并实验比较了文献中常用的几种正则化约束。结果表明，不同正则化项在抑制噪声和保持边缘特征方面表现各异，其中TV正则化在保持结构清晰度上表现更优。
原文摘要 · Abstract (English)
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.
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