Restoration of non-uniformly warped noisy images based on coarse-to-fine optical flow estimation

This paper proposes a high accuracy and fast image restoration approach to restore a sequence of atmospheric turbulence degraded frames of a remote object or scene. A coarse-to-fine optical flow technique is employed to estimate the dense motion fields of the frames against a reference frame. The First Register Then Average And Subtract (FRTAAS) method is used to correct the geometric distortions and restore a high quality sequence. Finally, a non-local means filter is applied to extract noise from each frame of the sequence. A performance comparison is presented between the proposed restoration method and an earlier method in terms of computational time and accuracy. The effectiveness of the proposed approach is demonstrated on both synthetic and real-life videos.