A blur kernel estimation method based on hybrid regularization is proposed to restore the blurred infrared image caused by turbulence. Firstly,according to the sparsity of the prominent edges and the smoothing of homogenous regions in the natural image,a L0-norm of image gradient is as regularization item. Through analyzing the feature of the blur kernel,a L0-L2-norm regularization constraint is applied to the complex blur situation. Secondly,the image and the blur kernel were estimated alternately by the variate splitting and augmented Lagrangian method in the optimization procedure of restoration model. The fast and accurate estimation of the blur kernel was achieved by FFT. Finally,the clear image was restored by the estimated blur kernel. Experimental results demonstrate that the proposed algorithm can better restore the degraded image,and the subjective vision and the objective measurement have been improved.