A common problem for imaging in the atmosphere is fog and atmospheric turbulence. Over the years, many researchers have provided insight into the physics of either the fog or turbulence but not both. Most recently, researchers have proposed methods to remove fog in images fast enough for real-time processing. Additionally, methods have been proposed by other researchers that address the atmospheric turbulence problem. In this paper, we provide an analysis that incorporates both physics models: 1) fog and 2) turbulence. We observe how contrast enhancements (fog removal) can affect image alignment and image averaging. We present in this paper, a new joint contrast enhancement and turbulence mitigation (CETM) method that utilizes estimations from the contrast enhancement algorithm to improve the turbulence removal algorithm. We provide a new turbulent mitigation object metric that measures temporal consistency. Finally, we design the CETM to be efficient such that it can operate in fractions of a second for near real-time applications.

中文翻译：

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对比增强湍流缓解的分析和方法。

大气中成像的常见问题是雾和大气湍流。多年来，许多研究人员提供了对雾或湍流但并非两者兼有的物理学的见解。最近，研究人员提出了一些方法，可以以足够快的速度去除图像中的雾，以进行实时处理。另外，其他研究人员已经提出了解决大气湍流问题的方法。在本文中，我们提供了一个包含两种物理模型的分析：1）雾和2）湍流。我们观察到对比度增强（除雾）如何影响图像对齐和图像平均。我们在本文中介绍了一种新的联合对比度增强和湍流缓解（CETM）方法，该方法利用来自对比度增强算法的估计来改进湍流去除算法。我们提供了一种新的湍流缓解目标指标，用于衡量时间一致性。最后，我们将CETM设计为高效的，以便它可以在几分之一秒内运行，用于近实时应用。