Abstract: Due to the influence of atmospheric turbulence, the images obtained by the remote optical imaging equipment will appear serious degradation phenomena, such as geometric distortion, motion blur and defocus blur, etc. At present, the mainstream turbulence restoration algorithms usually rely on the non-rigid registration, reconstruction or finding rare lucky regions from long-term video sequences. These methods require huge calculated amount or complete video data in advance, which cannot meet the real-time requirements of actual application scenarios. Therefore, a real-time turbulence restoration algorithm that could be implemented in field programmable gate array (FPGA) was proposed. This method used the randomness of atmospheric turbulence to filter the image in the time domain through the continuous frames and solved the problem of image geometric distortion. Then, the Wiener filter in the frequency domain was converted into a convolution in the spatial domain, which was easier to implement, and solved the problem of image blur. The experimental results show that the proposed algorithm not only meets the real-time requirements, but also effectively realizes the restoration of turbulence images.