A blind deconvolution image restoration algorithm based on prior information and regularization technique is proposed to eliminate the influence of atmospheric turbulence in the turbulence-degraded image restoration method. The basic principle of the algorithm is maximum likelihood theory. It uses the information of object image and point spread function(PSF),and transforms them into the penalizing function of maximum likelihood. At the same time,the regularization technique is introduced in the course of estimating object image and PSF to enhance the convergence speed and stability of the algorithm. The result of image restoration experiment shows when the model of turbulence-degrade is entirely unknown the algorithm can effectively realize the reconstruction of degraded image.