Motion-based spatial-temporal image repairing

In this paper, we present a motion-based method for image repairing where images with large missing regions can be restored. The key idea of this method is to reconstruct motion fields for regions of missing data by exploring both temporal and spatial information. After the full motion fields are reconstructed, missing regions can be repaired by the replacement of good corresponding regions from other images. To handle general scenes, we employ dense optical flow as our motion model. To compute flow without correspondence (due to missing pixels), we propose an effective multi-resolution, multi-frame flow method. We demonstrate the efficacy of our method using real images.