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Complexity-Constrained H.264 Video Encoding

机译:复杂度受限的H.264视频编码

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摘要

In this paper, a joint complexity-distortion optimization approach is proposed for real-time H.264 video encoding under the power-constrained environment. The power consumption is first translated to the encoding computation costs measured by the number of scaled computation units consumed by basic operations. The solved problem is then specified to be the allocation and utilization of the computational resources. A computation allocation model (CAM) with virtual computation buffers is proposed to optimally allocate the computational resources to each video frame. In particular, the proposed CAM and the traditional hypothetical reference decoder model have the same temporal phase in operations. Further, to fully utilize the allocated computational resources, complexity-configurable motion estimation (CAME) and complexity-configurable mode decision (CAMD) algorithms are proposed for H.264 video encoding. In particular, the CAME is performed to select the path of motion search at the frame level, and the CAMD is performed to select the order of mode search at the macroblock level. Based on the hierarchical adjusting approach, the adaptive allocation of computational resources and the fine scalability of complexity control can be achieved.
机译:本文针对功率受限环境下的实时H.264视频编码提出了一种联合复杂度-失真优化方法。首先将功耗转换为编码运算成本,该编码运算成本由基本操作所消耗的按比例缩放的计算单元的数量来衡量。然后将解决的问题指定为计算资源的分配和利用。提出了一种具有虚拟计算缓冲区的计算分配模型(CAM),以将计算资源最佳地分配给每个视频帧。特别地,所提出的CAM和传统的假设参考解码器模型在操作中具有相同的时间相位。此外,为了充分利用分配的计算资源,提出了用于H.264视频编码的复杂度可配置运动估计(CAME)和复杂度可配置模式决策(CAMD)算法。特别地,执行CAME以在帧级别选择运动搜索的路径,并且执行CAMD以在宏块级别选择模式搜索的顺序。基于分层调整的方法,可以实现计算资源的自适应分配和复杂度控制的良好可扩展性。

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