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On generalizing the estimation-theoretic framework to scalable video coding with quadtree structured block partitions

机译:关于将估计理论框架推广到具有四叉树结构块分区的可伸缩视频编码

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Scalable video coding suffers from the under-utilization of base layer information, where usually only the reconstruction in the base layer is used for enhancement layer prediction. Prior work from our lab proposed an optimal estimation-theoretic (ET) approach for quality scalable coding, wherein the estimates are obtained by utilizing all the available information from base layer quantization interval and enhancement layer distribution for transform coefficients. While this approach was proposed for fixed block size encoding, modern codecs employ variable block size quadtree structured partitioning, which results in different partitions at base layer and enhancement layer based on the rate-distortion trade-off, thus makes the base layer information not directly usable in the enhancement layer. Other new tools such as hybrid transform and the rate-distortion optimized quantizer (RDOQ) also have an impact on the information available for optimal estimation. In this paper, we generalize the ET framework for quality scalable video coding to account for the quadtree structured partitioning, hybrid transform and the RDOQ adjustment. Experimental evidence is provided for consistent coding gains over standard SHVC.
机译:可伸缩视频编码遭受基础层信息利用不足的困扰,其中通常仅将基础层中的重建用于增强层预测。我们实验室的先前工作提出了一种用于质量可伸缩编码的最佳估计理论(ET)方法,其中,估计是通过利用来自基础层量化间隔和增强层分布的所有可用信息获得的变换系数来获得的。虽然此方法是针对固定块大小编码而提出的,但现代编解码器采用可变块大小四叉树结构化分区,这导致基于速率失真的折衷在基础层和增强层进行不同的分区,从而使基础层信息不直接在增强层中可用。其他新工具,例如混合变换和速率失真优化量化器(RDOQ),也会对可用于最佳估计的信息产生影响。在本文中,我们概括了质量可伸缩视频编码的ET框架,以说明四叉树结构化分区,混合变换和RDOQ调整。实验证据提供了优于标准SHVC的一致编码增益。

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