The Criminisi algorithm, as one representative of excellent image inpainting algorithms, can used to obtain a better visual effect when partially damaged images are inpainted, but when this algorithm is used to perform the matching block search, the matching range is too small because the amount of information provided by the blocks to be repaired is less during the matching block search. For this problem, an improved Criminisi image inpainting algorithm based on rough data-deduction is proposed, in which rough data-deduction can be used to expand the search space, increase the search data, expand the search scope, and deepen the search depth. The proposed algorithm has some improvements in the search rules. The image content is divided into a dataset according to the structural information of images. The amount of pending repairing information is extended by rough data-deduction. The matching block search range is expanded. Based on these, the matching blocks are searched and the broken images are repaired. The results show that compared with the traditional Criminisi algorithm, the improved algorithm can be used to expand the matching block data sizes, search more data, obtain better visual effects, and improve the peak signal-to-noise ratio of images.