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Adaptive Quantization Parameter Cascading in HEVC Hierarchical Coding

机译:HEVC分层编码中的自适应量化参数级联

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The state-of-the-art High Efficiency Video Coding (HEVC) standard adopts a hierarchical coding structure to improve its coding efficiency. This allows for the quantization parameter cascading (QPC) scheme that assigns quantization parameters (Qps) to different hierarchical layers in order to further improve the rate-distortion (RD) performance. However, only static QPC schemes have been suggested in HEVC test model, which are unable to fully explore the potentials of QPC. In this paper, we propose an adaptive QPC scheme for an HEVC hierarchical structure to code natural video sequences characterized by diversified textures, motions, and encoder configurations. We formulate the adaptive QPC scheme as a non-linear programming problem and solve it in a scientifically sound way with a manageable low computational overhead. The proposed model addresses a generic Qp assignment problem of video coding. Therefore, it also applies to group-of-picture-level, frame-level and coding unit-level Qp assignments. Comprehensive experiments have demonstrated that the proposed QPC scheme is able to adapt quickly to different video contents and coding configurations while achieving noticeable RD performance enhancement over all static and adaptive QPC schemes under comparison as well as HEVC default frame-level rate control. We have also made valuable observations on the distributions of adaptive QPC sets in the videos of different types of contents, which provide useful insights on how to further improve static QPC schemes.
机译:最新的高效视频编码(HEVC)标准采用分层编码结构来提高其编码效率。这允许量化参数级联(QPC)方案,该方案将量化参数(Qps)分配给不同的层次层,以进一步提高速率失真(RD)性能。但是,在HEVC测试模型中仅提出了静态QPC方案,无法完全挖掘QPC的潜力。在本文中,我们针对HEVC分层结构提出了一种自适应QPC方案,以对以多种纹理,运动和编码器配置为特征的自然视频序列进行编码。我们将自适应QPC方案表述为非线性规划问题,并以科学合理的方式解决该问题,并且具有可管理的低计算开销。提出的模型解决了视频编码的一般Qp分配问题。因此,它也适用于图像组级别,帧级别和编码单位级别的Qp分配。全面的实验表明,所提出的QPC方案能够快速适应不同的视频内容和编码配置,同时在所有静态和自适应QPC方案以及HEVC默认帧级速率控制下,都可以实现显着的RD性能增强。我们还对不同类型的内容视频中的自适应QPC集的分布进行了有价值的观察,这为如何进一步改进静态QPC方案提供了有用的见解。

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