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Improved rate distortion optimized quantization for HEVC with adaptive thresholding

机译:具有自适应阈值的HEVC改进的速率失真优化量化

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Coefficient-level rate distortion optimized quantization (RDOQ) is an efficient tool to improve rate-distortion performance with 6%-8% bit-rate saving. It has been widely adopted in video encoders such as JM, x264, HM and so on. However, software implementation of RDOQ suffers from high computation complexity due to intensive path search and from data dependency caused by context based entropy coding. In this paper, a fast RDOQ algorithm with accurate rate estimation between the two candidates quantized level for high efficient video coding (HEVC) is proposed to decrease the computation complexity and break the data dependency. Firstly, the preselection of candidate quantized levels is preformed according to hard decision quantization (HDQ) level and the coefficient position in transform unit (TU). The reduction of candidate quantized levels can significant decrease the computation complexity of RDOQ. Secondly, a model of delta bit-rate is constructed to estimate bitrate change between the rest two candidate quantized levels. With this delta bit-rate model, the high computation complexity of bitrate computation based on context adaptive binary arithmetic coding (CABAC) can be avoided, and coefficients can be parallel processed. Experiment results demonstrate that the proposed algorithm can decrease the encoding time of RDOQ by 54.36% in average with no more than 0.88% BD-rate loss.
机译:系数级速率失真优化量化(RDOQ)是提高速率失真性能的有效工具,节省了6%-8%的比特率。它已被JM,x264,HM等视频编码器广泛采用。然而,由于密集的路径搜索以及基于上下文的熵编码所引起的数据依赖性,RDOQ的软件实现遭受高计算复杂度的困扰。在本文中,提出了一种快速RDOQ算法,该算法在两个候选量化级别之间具有准确的速率估计,以实现高效视频编码(HEVC),从而降低了计算复杂性并打破了数据依赖性。首先,根据硬判决量化(HDQ)级别和变换单元(TU)中的系数位置来执行候选量化级别的预选择。减少候选量化级别可以显着降低RDOQ的计算复杂度。其次,构建增量比特率模型以估计其余两个候选量化级别之间的比特率变化。使用这种增量比特率模型,可以避免基于上下文自适应二进制算术编码(CABAC)的比特率计算的高计算复杂性,并且可以并行处理系数。实验结果表明,该算法平均可以减少RDOQ的编码时间54.36%,而BD率损失不超过0.88%。

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