Hybrid texture synthesis and interpolated structure image completion

Abstract

The issue of image completion has been extensively developed for a few dozen years and many computational methods exist to tackle various image completion problems. When only one incomplete image is available, the missing regions are relatively large but their texture can be recovered from surrounding regions, then the texture synthesis methods are usually the most efficient. If an incomplete image contains a large number of missing pixels (e.g. 90%) or small missing regions uniformly distributed across it, low-rank approximation or interpolation-based methods seem to be the best choice. However, when the image of interest contains both types of incompleteness, none of the mentioned methods can be applied. In this study, we propose a hybrid computational method combining the radial basis function interpolation with the texture synthesis to tackle the mentioned problem. The experiments, carried out on various image completion problems, demonstrate that our hybrid strategy considerably outperforms the baseline and selected low-rank completion methods.