In order to realize the blind recovery of motion blurred image, we present a blind recovery method based on combining l1/l2 norm with the high order and low order total variation. We adopt the ratio of l1/l2 norm regularization prior item which has high sparse expression ability, and add the high order and low order total variation regularization item. High order total variation regularization model can suppress the ladder effect and ringing effect that may occur in the region of non-edges. Low order total variation regularization model can protect the sparse feature of natural image edges. The solution of high-quality image and the solution of blurred kernel are given respectively, both of which employing Bregman iterative algorithms to split the objective function into multiple sub-problems. The experimental results show that the proposed method can restrain ringing effect and protect the image edge details. The robustness of proposed algorithm is better in the visual quality and objective quality evaluation comparing with other methods for blind recovery of motion blurred images.