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Fast CU size decision and mode decision algorithm for HEVC intra coding

机译:HEVC帧内编码的快速CU大小决策和模式决策算法

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摘要

The emerging international standard of High Efficiency Video Coding (HEVC) is a successor to H.264/AVC. In the joint model of HEVC, the tree structured coding unit (CU) is adopted, which allows recursive splitting into four equally sized blocks. At each depth level, it enables up to 34 intra prediction modes. The intra mode decision process in HEVC is performed using all the possible depth levels and prediction modes to find the one with the least rate distortion (RD) cost using Lagrange multiplier. This achieves the highest coding efficiency but requires a very high computational complexity. In this paper, we propose a fast CU size decision and mode decision algorithm for HEVC intra coding. Since the optimal CU depth level is highly content-dependent, it is not efficient to use a fixed CU depth range for a whole image. Therefore, we can skip some specific depth levels rarely used in spatially nearby CUs. Meanwhile, there are RD cost and prediction mode correlations among different depth levels or spatially nearby CUs. By fully exploiting these correlations, we can skip some prediction modes which are rarely used in the parent CUs in the upper depth levels or spatially nearby CUs. Experimental results demonstrate that the proposed algorithm can save 21% computational complexity on average with negligible loss of coding efficiency1.
机译:新兴的高效视频编码(HEVC)国际标准是H.264 / AVC的继承者。在HEVC的联合模型中,采用树形结构的编码单元(CU),可以将其递归拆分为四个大小相等的块。在每个深度级别,它最多可以启用34种帧内预测模式。使用所有可能的深度级别和预测模式执行HEVC中的帧内模式决策过程,以使用拉格朗日乘数找到具有最小速率失真(RD)成本的模式。这实现了最高的编码效率,但是需要非常高的计算复杂度。在本文中,我们提出了一种用于HEVC帧内编码的快速CU大小决策和模式决策算法。由于最佳CU深度级别高度依赖于内容,因此对整个图像使用固定的CU深度范围效率不高。因此,我们可以跳过一些在空间上附近的CU中很少使用的特定深度级别。同时,在不同深度水平或空间上邻近的CU之间存在RD成本和预测模式的相关性。通过充分利用这些相关性,我们可以跳过一些在深度较高级别或空间上邻近的CU中很少在父CU中使用的预测模式。实验结果表明,该算法平均可节省21%的计算复杂度,而编码效率 1 的损失可忽略不计。

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