Criminisi算法作为优秀的图像修复算法代表,在修复部分破损图像时可获得较好的视觉效果,但该算法在进行匹配块搜寻时,待修复块提供的信息量较少,因此可匹配范围小。针对这一问题,提出了一种基于粗糙数据推理理论的改进Criminisi图像修复算法,粗糙数据推理可以扩展搜索空间,增加搜索数据,扩大搜索范围,加深搜索深度。该算法在搜索规则上有以下改进:通过图像结构信息将图像内容划分为一个数据集,再通过粗糙数据推理扩充待修复块信息量,扩大匹配块可寻范围,以此搜索匹配块,修复破损图像。结果表明,与经典的Criminisi算法相比,改进后的算法能够扩展匹配块的数据量,可搜索到更多数据,获得较好的视觉效果,提高了图像的峰值信噪比。

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.