"Mind the gap": tele-registration for structure-driven image completion

Hui Huang, Kangxue Yin, Minglun Gong, Dani Lischinski, Daniel Cohen-Or, Uri M. Ascher, Baoquan Chen

Abstract: Concocting a plausible composition from several non-overlapping image pieces, whose relative positions are not fixed in advance and without having the benefit of priors, can be a daunting task. Here we propose such a method, starting with a set of sloppily pasted image pieces with gaps between them. We first extract salient curves that approach the gaps from non-tangential directions, and use likely correspondences between pairs of such curves to guide a novel tele-registration method that simultaneously aligns all the pieces together. A structure-driven image completion technique is then proposed to fill the gaps, allowing the subsequent employment of standard in-painting tools to finish the job.