Combining coarse and fine registration for video frame super-resolution reconstruction

Abstract

Video-frame registration is a critical step in the video super-resolution process. However, many existing registration methods can handle only small local neighborhood movements or overall affine transformations. This limits the reconstruction of fast moving or significantly deforming objects. We propose a super-resolution registration method for video reconstruction. Considerable effort has been directed toward single-video and multivideo super-resolution methods. We aim to obtain a higher registration accuracy that maximally employs video frames to reconstruct the current frame, particularly for moving or deforming objects. To this end, we provide a content-based registration algorithm based on a propagation matching algorithm and the Lucas–Kanade method. The super-resolution step is implemented using robust iterative minimization. We compare our algorithm to others and demonstrate that our algorithm achieves high registration accuracy and more effectively reconstructs fast moving and significantly deforming objects.