Sample-based image completion using structure synthesis

Image completion technique is widely used in image processing applications such as textural recovery, object removal, image edit, etc. When filling in the missing areas of an image, it is often a challenge to keep local consistency of image structures while avoiding ambiguity and visual artifacts. To tackle with this problem, we propose a robust sample-based image completion scheme which is a cascade of two major procedures. First, we extract structural information from both source and sample images and then perform template matching under constraints of boundary band map and contour consistency to reconstruct the damaged structures. Second, a weighted exemplar-based image synthesis algorithm is further devised taking the previous structural information and matching results into account. Extensive experiments and comparative study show the reliability and superiority of our image completion algorithm.