The Experimental Demonstration of Correcting the Atmospheric Dispersion Using Image Processing Based on Edge Extension

Abstract EN

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.