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An efficient motion vector prediction method for avoiding AMVP data dependency for HEVC

机译:一种避免HEVC AMVP数据依赖的有效运动矢量预测方法

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To achieve higher coding efficiency, the latest video coding standard called High Efficiency Video Coding (HEVC) has adopted the mechanism of Advanced Motion Vector Prediction (AMVP) to further improve the accuracy of motion vector predictor. However, the adoption of AMVP significantly increases the hardware realization overhead as well as the data access bandwidth requirements. In addition, the dependency between different coding units (CUs) or prediction units (PUs) for predicting AMVP also noticeably degrades the overall hardware coding throughput. To deal with this problem, this paper proposes an efficient motion vector prediction method for avoiding AMVP data dependency. By modeling the relationship between motion vector predictors of largest coding unit (LCU) and other small CU and PU sizes, the motion vectors of small CUs and PUs are estimated directly from the motion vectors of LCU. Furthermore, the predicted motion vectors of small CUs and PUs are also used to pre-fetch the corresponding reference data from external memory in advanced so that the data access time can be hided. Simulation results demonstrate that the proposed motion vector prediction method can achieve at least 53.8% coding throughput improvement with only 1.04% BD-rate increasing when compared to direct AMVP realization.
机译:为了获得更高的编码效率,称为高效视频编码(HEVC)的最新视频编码标准采用了高级运动矢量预测(AMVP)机制,以进一步提高运动矢量预测器的准确性。但是,采用AMVP会大大增加硬件实现开销以及数据访问带宽要求。另外,用于预测AMVP的不同编码单元(CU)或预测单元(PU)之间的依赖性也显着降低了整体硬件编码吞吐量。针对这一问题,本文提出了一种有效的运动矢量预测方法,可以避免AMVP数据的依赖性。通过对最大编码单元(LCU)的运动矢量预测变量与其他小CU和PU尺寸之间的关系进行建模,可以直接从LCU的运动矢量估算小CU和PU的运动矢量。此外,小型CU和PU的预测运动矢量还用于预先从外部存储器预取相应的参考数据,从而可以隐藏数据访问时间。仿真结果表明,与直接AMVP实现相比,提出的运动矢量预测方法可以实现至少53.8%的编码吞吐量改进,而BD速率仅增加1.04%。

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