Prediction of quad-tree partitioning for budgeted energy HEVC encoding

Abstract

High Efficiency Video Coding (Hevc), the newest video encoding standard, provides up to 50% bitrate savings compared to the state-of-art H.264/AVC standard for the same perceptual video quality. In the last few years, the Internet of Things (IoT) has become a reality. Forthcoming applications are likely to boost mobile video demand to an unprecedented level. A large number of systems are likely to integrate HEVC codec in the long run and will need to be energy aware. In this context, constraining the energy consumption of HEVC encoder becomes a challenging task for embedded applications based on a software encoder. The most frequent approach to overcome this issue consists in optimising the coding tree structure to balance compression efficiency and energy consumption. In the purpose of budgeting the energy consumption of real-time HEVC encoder, we propose in this paper a variance-aware quad-tree prediction to limit the recursive RDO process. The experimental results show that the proposed energy reduction scheme achieve on average 60% of energy reduction for a slight bit rate increase of 3.4%.