the good visual effects can be got by the inpainting the small damage based on the current image inpainting algorithm; but these algorithm can not be applied to the image with high contrast edges and high frequency components, the obvious blur effect and blocking effect were existed to reduce the inpainting quality. So the large-scale damage image inpainting mechanism based on structural similarity index coupled optimal sparse representations. The optimal dictionary matrix was constructed to optimize the sparse representation for reconstructing the damage region of image by introducing the K-SVD algorithm and Lagrange multiplier mechanism; and the structural similarity index was designed to estimate the sparse representation coefficients and dynamic update the dictionary matrix to finish the image inpainting. Finally, the performance of this mechanism was tested. The results showed that: comparing with other image inpainting mechanism, the effect of image inpainting of this mechanism was best, and it can obviously eliminate the blur effect and blocking under the condition of large scale damage image inpainting.