Memory bandwidth-scalable motion estimation for mobile video coding

Abstract

The heavy memory access of motion estimation (ME) execution consumes significant power and could limit ME execution when the available memory bandwidth (BW) is reduced because of access congestion or changes in the dynamics of the power environment of modern mobile devices. In order to adapt to the changing BW while maintaining the rate-distortion (R-D) performance, this article proposes a novel data BW-scalable algorithm for ME with mobile multimedia chips. The available BW is modeled in a R-D sense and allocated to fit the dynamic contents. The simulation result shows 70% BW savings while keeping equivalent R-D performance compared with H.264 reference software for low-motion CIF-sized video. For high-motion sequences, the result shows our algorithm can better use the available BW to save an average bit rate of up to 13% with up to 0.1-dB PSNR increase for similar BW usage.