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Parallel AMVP candidate list construction for HEVC

机译:HEVC的并行AMVP候选清单构建

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Advanced motion vector prediction (AMVP) is one of the most important inter prediction coding tools adopted in the state-of-the-art HEVC coding standard, which does great effect on the coding efficiency. However, the current AMVP design is highly sequential and thus restricts the throughput both on the encoder and the decoder sides. To facilitate the parallel processing and enlarge the throughput, a parallel AMVP candidate list (AMVPCL) construction solution is proposed. The proposed parallel scheme consists of a three level fine granularity solutions. The first level is a CU-based approach and it constructs AMVPCL of all PUs in the same CU in parallel. The second level is also at CU level but it generates a single set of AMVPCL for all PUs inside a CU. Specifically, we only apply this method to 8×8 CU to balance the parallelism degree and rate-distortion performance. The third level is a CU-group based approach, in which AMVPCL of all PUs in the same CU-group are constructed in parallel. Experimental results show the proposed algorithm can efficiently achieve parallel motion estimation with negligible 0.0%∼1.3% BD-rate loss at different degree of parallelism.
机译:先进运动矢量预测(AMVP)是最新的HEVC编码标准中采用的最重要的帧间预测编码工具之一,它对编码效率有很大影响。但是,当前的AMVP设计是高度顺序的,因此限制了编码器和解码器端的吞吐量。为了促进并行处理并增加吞吐量,提出了一种并行AMVP候选列表(AMVPCL)构建解决方案。提出的并行方案由三级精细粒度解决方案组成。第一级是基于CU的方法,它并行构造同一CU中所有PU的AMVPCL。第二级也处于CU级,但是它为CU内部的所有PU生成了一组AMVPCL。具体而言,我们仅将此方法应用于8×8 CU,以平衡并行度和速率失真性能。第三层是基于CU组的方法,其中并行构建同一CU组中的所有PU的AMVPCL。实验结果表明,在不同的并行度下,该算法可以有效地实现并行运动估计,而BD速率损失为0.0%〜1.3%。

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