Two fast algorithms of image inpainting

摘要

Digital image inpainting is an interesting new research topic in multimedia computing and image processing since 2000. This talk covers the most recent contributions in digital image inpainting and image completion, as well as concepts in video inpainting. Image inpainting refers to reconstructing the corrupt regions where the data are all destroyed. A primary class of the technique is to build up a Partial Differential Equation (PDE), consider it as a boundary problem, and solve it by some iterative method. The most representative and creative one of the inpainting algorithms is Bertalmio-Sapiro-Caselles-Bellester (BSCB) model. After summarizes the development of image inpainting technique, this paper points the research at the improvement on BSCB model, and proposes two algorithms to solve the two drawbacks of this model. The first is selective adaptive interpolation which develops the traditional adaptive interpolation algorithm by introducing a priority value. Besides much faster than BSCB model, it can improve the inpainting effects. The second takes selective adaptive interpolation as a preprocessing step, reduces the operation time and improves the inpainting quality further.