针对Criminisi等人提出的基于样本的图像修复算法存在修复耗时长、效率低的问题，提出一种采用双线性插值算法收缩待修复的图像，并结合样本块进行图像修复的方法。首先，采用双线型插值算法将待修复图像的长宽同时收缩0.2～0.5倍，在收缩图像的目标区域中计算优先级最高的目标像素点,并在源区域中搜索最佳匹配修复块。然后，在待修复图像中根据一定规则找到对应的优先级最高的目标像素点和最佳匹配修复块，并将其填充到待修复图像的修复区域，循环运行直到目标区域修复完毕。实验结果表明，采用本文提出的算法进行图像修复时，其时效约为Criminisi等人提出的算法的5～40倍，该方法可以在获得高的修复效率同时保持良好的修复质量。

To overcome the shortcomings of long time-consuming and low efficiency from the exemplar-based image inpainting algorithm proposed by Criminisi, an image inpainting algorithm was presented,in which the bilinear interpolation algorithm was used to downscale the original image and to improve inpainting efficiency.Firstly,the dimension of the original image was downscaled by a factor 0.2-0.5, then the inpainted point with the highest priority from a target region was evaluated and a best-exemplar was searched from the source region in the downscaled image.Furthermore, those counterparts were obtained by the proposed rules from the original image and were filled into the whole damaged region in the origin image.The above steps were iterated until the target regions were completely filled.Experimental results demonstrate that the proposed image inpainting algorithm can inhance 5-40 times the inpainting efficiency of the Criminisi’s, while good inpainting images are achieved.This method can obtain good inpainting results in efficiency and quality.