Super-resolution of video using key frames and motion estimation
Many scalable video coding systems use frame down- sampling in order to reduce complexity and to enable enhancement layers. Super-resolution (SR) can be used to help the up-sampling and recovering processes of those frames. We are interested in reversed-complexity (distributed) coding methods, wherein few key frames are encoded at normal resolution, while the rest are down- sampled and encoded at reduced resolution along with the enhancement layers. We are only interested on the decoder side, wherein we carry motion estimation of the down- sampled frames using the key frames as references. When a match is made, the high-frequency components of the key frames (KF) are used to super-resolve the non-key frames (NKF). The motion estimation process is performed using blocks of band-pass versions of the frames, rather than low- pass ones. Results indicate the improved performance of the proposed super-resolution algorithm.