A turbulence-degraded image blind restoration method called ADRL-IBD using the accelerated and damped Richardson-Lucy (ADRL) algorithm is proposed. The ADRL algorithm is based on damped Richardson-Lucy algorithm and vector extrapolation acceleration technique. The observed image or the physical model of long exposure atmospheric turbulence optical transfer function is used to obtain the initial point spread function (PSF), and threshold segmentation technology is used for getting reliable support domain of the target image. The support domain restraint of image is exerted at each iteration. The restored images of simulation data and real turbulence-degraded data show that the iterative blind deconvolution (IBD) method based on Richardson-Lucy algorithm is better than the IBD method based on Wiener filtering, and ADRL-IBD. Compared with RL-IBD algorithm, it has better performance suppressing noise, greater convergence rate, and better restoration result.