基于图像拼接的可信图像修补方法

Trustable Image Inpainting Method Based on Image Mosaics

为了尽可能地恢复被损坏图像的原始场景,获得最真实的复原效果,针对大区域破损图像的修复,提出了一个基于移位参考图像的可信图像修补与基于图像本身的自修复算法相结合的图像修复方法。首先,受启于图像拼接技术,若存在可以利用的参考图像,便利用SIFT(scale invariant feature transform)算法和RANSAC(random sample consensus)算法将参考图像与目标图像进行配准并投影拼接至目标图像,完成目标图像的可信修补。然后对仍未修复的破损区域进行图像自修复,其中自修复部分采用Criminisi算法。所得到的图像修复结果真实性与可信度较高,与实际景象偏差较小,说明该方法合理可行。

In order to restore the original scene of a damaged image and obtain the most realistic restoration effect as much as possible, an image inpainting method was proposed based on the reliable repairing of a shifted reference image combined with the self-repair of the target image. It was inspired by the image stitching technology, if there was a reference image that can be used, it was convenient to use the SIFT（scale invariant feature transform） algorithm and RANSAC（random sample consensus）algorithm to register the reference image and the target image, and then project it to the target image.Then the Criminisi algorithm was used to self-repair the areas that had not been repaired. The authenticity and reliability of the image restoration are higher, and the repair results are less different from the actual scene, which shows the rationality of this method.