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Adaptive quantization parameter cascading for hierarchical video coding

机译:分层视频编码的自适应量化参数级联

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Quantization parameter (QP) cascaded hierarchical prediction structures have been proved as efficient techniques in hybrid video coding. However, the current QP cascading method is empirical and not adaptive. The reason for the higher coding efficiency of this method has not been fully explored so far. In this paper, the rate-distortion performance of QP cascaded hierarchical video coding is first analyzed with dependent rate-distortion function. Then the optimal offset in linear QP cascading scheme is derived theoretically. It is shown that the widely accepted empirical QP cascading method is actually an approximation to the theoretical solution in fast movement environment. For slow sequences, an average gain of 0.43 dB can be achieved by the combination of two proposed adaptive algorithms.
机译:量化参数(QP)级联分层预测结构已被证明是混合视频编码中的有效技术。但是,当前的QP级联方法是经验性的,而不是自适应的。迄今为止,尚未充分探讨这种方法的较高编码效率的原因。本文首先对QP级联分层视频编码的速率失真性能进行了分析,并给出了相关的速率失真函数。然后从理论上推导了线性QP级联方案中的最佳偏移量。结果表明,被广泛接受的经验QP级联方法实际上是快速运动环境中理论解的近似值。对于慢速序列,可以通过两种建议的自适应算法的组合获得0.43 dB的平均增益。

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