Image inpainting with texture synthesis

Natural images and photographs sometimes may contain stains or undesired objects covering significant portions of the images. Inpainting is a method to fill in such portions using the information from the remaining area of the image. In this paper, we propose a novel photograph editing framework that utilizes texture synthesis techniques. Major contributions of our algorithm are: 1) a constraint-based candidate patch searching method which limits the searching within neighboring region with similar texture; 2) a metric of Coherence Confidence for selecting the best fit candidate preventing error accumulation and propagation; 3) integration of graphcut optimization to make the seam visually invisible. Experiments show that our system can efficiently handle different cases especially large regions in complex background.

Examples of portrait or Chinese calligraphy inpainting..

Examples of image inpainting. The left: orginal images, and the right: inpainted images

Our system can also edit the image, and remove the unwanted part of the image.