Multiscale motion estimation for scalable video coding

Abstract

Motion estimation is an important component of video coding systems because it enables us to exploit the temporal redundancy in the sequence. The popular block-matching algorithms (BMAs) produce unnatural, piecewise constant motion fields that do not correspond to "true" motion. In contrast, our focus here is on high-quality motion estimates that produce a video representation that is less dependent on the specific frame-rate or resolution. To this end, we present an iterated registration algorithm that extends previous work on multiscale motion models and gradient-based estimation for coding applications. We obtain improved motion estimates and higher overall coding performance. Promising applications are found in temporally-scalable video coding with motion-compensated frame interpolation at the decoder. We obtain excellent interpolation performance and video quality; in contrast, BMA leads to annoying artifacts near moving image edges.