Spatiotemporal super-resolution for multiview video in transform domain
Yawei Li, Xiaofeng Li, Zhizhong Fu, Tingting Niu, Keyu Long · 2016
Super-resolution (SR) algorithms for multiview videos aim at refining the low-resolution (LR) views using high-frequency detail information from adjacent high-resolution (HR) views. However, to refine a LR view, the state-of-the-art methods only exploit the spatial redundancy of a multiview video. To take full advantage of the spatial and temporal redundancy, a new spatiotemporal SR algorithm is proposed in this paper. Depth-image-based rendering (DIBR) establishes coordinate correspondences between different views. Motion estimation handles object motion between different frames. The high-frequency details are extracted in transform domain and added to LR images. In order to merge the details from different HR images, a combination of global and local weights is proposed. The effectiveness of the proposed algorithm is proved theoretically and shown experimentally.