Image completion has attracted many researchers these years. The goal of image completion is to repair missing region of images

or to remove objects from images and fill the holes using background information

making it hard to distinguish by eyes. However

to repair huge structure is difficult. We divide the process of image completion into two parts. When the user specified the missing region and structure curves

we first define a global energy function; dynamic programming and belief propagation is used to decide the global minimal cost. This step is also called structure propagation and when it is completed

we scan the region left and implement texture synthesis. For the pixels on boundaries we use exemplar-based algorithm to copy and paste by patch; for the pixels inside the region

we employ a fast weighted Ashikhmin-WL algorithm. At last

the completed image is obtained. We construct a fast structural image completion system and get some results. Experimental results show that our algorithm is useful. Our algorithm will also be extended to video completion in the near future.