To solve the problem as ringing and discontinuous connection effect in repaired images induced by ignoring the correlation between image blocks when filling and repairing damaged areas in current image inpainting algorithm, this paper aims to design an image inpainting algorithm based on smoothness measurement factor coupling and cross-correlation constraints. The Laplace operator was introduced into the priority calculation process to increase the edge information of the image, optimize the components of the data items, and construct the priority calculation model by using the confidence and the Laplace operator and data items of the image to obtain the priority repair module. The smoothness measurement factor was constructed with the second-order differential of the equal illumination line to obtain the smoothness of the image. And the search area of the optimal matching block was located based on the smoothness of the image. In order to improve the accuracy of the optimal matching block, the error square sum function was used to search the optimal matching block in the searching area of the location, and the cross-correlation coefficient function was used to restrict the uniqueness of the optimal matching block. The experimental results showed that the image restored by the proposed method had more complete edge continuity and clarity than the image restored by the current method, and the visual effect of the restored image can be effectively improved. The proposed scheme can achieve better visual restoration of damaged images, which has a certain reference value in the field of image information processing.