We present an image processing algorithm based on edge extension to correct the influence of atmospheric dispersion. The Elden model is used to estimate the image dispersion index caused by atmospheric dispersion and the image affected by the atmospheric dispersion is regarded as the results of the original image convolution operation. When the direct convolution is used to compensate the blur of star, border effect and ill-posed problem make the result unacceptable. To solve these problems, we use image preprocessing and perform an edge extension method for images before the convolution. The simulated analysis and experimental results from a 300 mm telescope system show that the proposed method can effectively correct the influence of atmospheric dispersion even under relatively low signal to noise ratio (SNR<2). Compared with the traditional prism correction and fiber correction methods, this technique can greatly reduce the complexity of the optical system.

中文翻译：

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基于边缘扩展的图像处理校正大气色散的实验演示

我们提出一种基于边缘扩展的图像处理算法，以校正大气弥散的影响。Elden模型用于估计由大气弥散引起的图像弥散指数，并且受大气弥散影响的图像被视为原始图像卷积运算的结果。当直接卷积用于补偿恒星的模糊时，边界效应和不适定问题使结果不可接受。为了解决这些问题，我们使用图像预处理并对卷积之前的图像执行边缘扩展方法。300 mm望远镜系统的仿真分析和实验结果表明，即使在相对较低的信噪比（SNR <2）的情况下，该方法也可以有效地校正大气弥散的影响。