An Efficient Mode Preselection Algorithm for Fractional Motion Estimation in H.264/AVC Scalable Video Extension

Abstract

The video coding standard, H.264/AVC scalable video extension (SVC), adopts various advanced interlayer prediction modes to explore the data redundancies between layers for better coding efficiency but at the expense of significantly increased computational complexity and data access bandwidth, especially for hardware realization of fractional motion estimation mode decision. To deal with this problem, this paper proposes a mode preselection algorithm for fractional motion estimation in scalable video coding. We first analyze the rate distortion cost relationship between different prediction modes. With the statistical results, several mode preselection rules are proposed to filter out the potentially skippable prediction modes. Simulation results show that our proposed algorithm reduces up to 65.97% prediction modes and 79.79% coding time on average with only 0.036 dB and 0.496% BD-peak signal-to-noise ratio (PSNR) degradation and BD-rate increase, respectively. Furthermore, the proposed mode preselection algorithm has been implemented in hardware and it costs only 9 k gate counts, when synthesized by 90 nm CMOS technology.