Existing wavefront reconstruction methods generally have low resolution when we examine wavefront distortion caused by turbulence in the atmosphere. They are also limited by the structures of sensors and deformable mirrors. In this paper, a method based on wavelet fractal-difference wavefront correction is proposed. A wavefront reconstruction method based on wavelet fractal interpolation is also proposed, and it is applied after performing self-similarity analysis of wavefront distortion caused by atmospheric turbulence. The multi-resolution analysis of the wavefront phase spectrum is performed by the fast wavelet decomposition method and soft threshold denoising is performed in this process. Subsequently, the fractal interpolation method is used to increase the resolution of the estimated wavefront phase. Finally, the recovery of the wavefront phase is achieved by applying the fast wavelet reconstruction method. Experimental results show that the fast wavelet reconstruction is capable of recovering the wavefront phase. Compared with the minimum variance estimation (MVE) method, the proposed method improves the light intensity value and residual wavefront root-mean-square value, thereby effectively reducing noise interference. A higher imaging quality is obtained and the corrected spot shape is reliable and stable.