Turbulence is an important motion of atmosphere, which affects the imaging system seriously, and causes image distortion and blur. The randomly changing turbulence makes it difficult to estimate the devolution kernel and the atmospheric turbulence image restoration is ill-conditioned. we propose an atmospheric turbulence image restoration method based on priors of distinct edges. Firstly, the images are rectified. Then, we fuse the registered images and deblur the image to obtain the final image using a new method based on the distinct edge prior. In the single image deblurring schedule, we detect the distinct edges and predict the “sharp vision” of them, and use them to estimate the value of blur kernel. Finally, in order to restore the sharp images, we employ winner filter to deconvolute the images. The algorithm archives recovering much image details and sharpening edges and avoids the artifacts, which is of great practice.