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首页> 外文期刊>IEEE Transactions on Circuits and Systems for Video Technology >An Efficient Mode Preselection Algorithm for Fractional Motion Estimation in H.264/AVC Scalable Video Extension
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An Efficient Mode Preselection Algorithm for Fractional Motion Estimation in H.264/AVC Scalable Video Extension

机译:H.264 / AVC可扩展视频扩展中分数运动估计的高效模式预选算法

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摘要

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.
机译:视频编码标准H.264 / AVC可扩展视频扩展(SVC),采用各种高级层间预测模式来探索各层之间的数据冗余,以提高编码效率,但以显着增加的计算复杂性和数据访问带宽为代价,特别是对于分数运动估计模式决策的硬件实现。针对这一问题,本文提出了一种用于可伸缩视频编码中分数运动估计的模式预选算法。我们首先分析不同预测模式之间的比率失真成本关系。根据统计结果,提出了几种模式预选规则,以过滤出可能会跳过的预测模式。仿真结果表明,我们提出的算法平均减少了65.97%的预测模式和79.79%的编码时间,而BD峰信噪比(PSNR)的下降仅为0.036 dB,而BD率的上升仅为0.496%。此外,所提出的模式预选算法已在硬件中实现,并且在通过90 nm CMOS技术进行合成时,仅需9 k的门计数。

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