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Research on image restoration algorithm for atmospheric turbulence degradation based on serial images

机译:基于串行图像的大气湍流劣化图像恢复算法研究

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In the field of space measurement and control, photoelectric theodolites are an important part of optical measurement system. They are mainly responsible for acquiring flight images of targets. Through processing the acquired images,we get the targets’ flight data. Therefore, the image quality affects the measurement accuracy of photoelectric theodolites. However, when acquiring nearground targets, they are susceptible to atmospheric turbulence, which can lead to image distortion. For this reason, the degraded image restoration algorithm affected by atmospheric turbulence is studied. In this paper, highspeed cameras of optical devices are used to obtain high-frequency images. Reference images are obtained by averaging the serial images. At last the affected images are restored by the reference images with Demons algorithm. The result shows thatDemons algorithm significantly reduces the impact of atmospheric turbulence and improves the image quality.
机译:在空间测量和控制领域,光电经纬仪是光学测量系统的重要组成部分。它们主要负责获取目标的飞行图像。通过处理所获取的图像,我们得到目标的飞行数据。因此,图像质量影响光电经纬仪的测量精度。然而,当获取附近的目标时,它们易受大气湍流的影响,这可能导致图像失真。因此,研究了受大气湍流影响的降级图像恢复算法。在本文中,使用光学装置的高速相机来获得高频率图像。通过平均串行图像获得参考图像。最后,受影响的图像由具有Demons算法的参考图像恢复。结果表明,该算法显着降低了大气湍流的影响并提高了图像质量。

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