Contents-aware partitioning algorithm for parallel high efficiency video coding
Contents-aware partitioning algorithm for parallel high efficiency video coding
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DOI：
10.1007/s11042-018-6619-8
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发表时间：
2018-09
影响因子：
3.6
通讯作者：
Kyungah Kim;W. Ro
中科院分区：
文献类型：
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作者：
Kyungah Kim;W. Ro
我们引入了一种新的高效视频编码（HEVC）并行化方法，它解决了现有基于图块的并行处理方法的缺点。并行HEVC通过将帧划分为多个并行单元来执行编码。与顺序 HEVC 相比，这降低了压缩效率，因为它人为地破坏了帧内的数据相关性，这称为并行化开销。 Tiles 和波前并行处理 (WPP) 等传统并行技术本质上会引入较高的并行化开销，因为它们只是静态地划分帧而不考虑帧的内容。所提出的新的并行编码方案通过基于有意义的内容来划分帧来解决此类问题。为了分析帧内的相关性并定义内容，首先提取帧内的特征并进行聚类。在特征聚类算法中，考虑两个因素来平衡并行单元之间的工作量：（1）每个簇中的特征数量和（2）每个簇占用的编码树单元（CTU）的数量。根据聚类结果对帧进行分区，并对分区进行并行编码。与Tiles技术相比，所提出的方案节省了高达7.21%的比特，平均节省了3.71%，平均节省了20.50%的时间。
We introduce a new parallelization method for high-efficiency video coding (HEVC), which resolves the shortcomings of the existing tile-based parallel processing method. The parallel HEVC performs encoding by dividing a frame into numerous parallel units. This decreases the compression efficiency compared with sequential HEVC, because it artificially breaks the data correlation within a frame, which is called the parallelization overhead. The traditional parallel techniques such as Tiles and wavefront parallel processing (WPP) inherently introduce a high parallelization overhead because they simply divide a frame statically without considering the contents of the frame. The proposed new parallel encoding scheme resolves such problems by partitioning a frame based on the meaningful contents. In order to analyze the correlations within a frame and define the contents, the features within a frame are first extracted and clustered. In the feature clustering algorithm, two factors are considered to balance the workload between parallel units: (1) the number of features in each cluster and (2) the number of coding tree units (CTU) occupied by each cluster. The frame is partitioned based on the result of clustering, and the partitions are encoded in parallel. The proposed scheme achieves a bit-saving of up to 7.21%, with an average of 3.71%, along with an average time-saving of 20.50% compared to the Tiles technique.