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High-speed implementation of rate-distortion optimized quantization for H.264/AVC - Springer

机译：H.264 / AVC的速率失真优化量化的高速实现-Springer

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摘要

Rate-distortion optimized quantization (RDOQ) is generally employed in video coding as an effective tool for pursuing high coding efficiency. Nevertheless, RDOQ requires an exhaustive search over multiple candidates to determine the optimal quantized level by comparing their rate-distortion cost, which leads to considerable complexity in practice. The utilization of inherently strong data dependency and highly sequential process in entropy coding to obtain the information of the bit-rate for each candidate further aggravates the issue of large computational burden. In this paper, a high-speed implementation of RDOQ is proposed to substitute the conventional RDOQ in H.264/AVC. The proposed scheme is low in computational complexity and economical in the requirement of hardware resources. The candidates of quantized levels that are unlikely to be selected are firstly excluded, and then a bit-rate estimation model is constructed for the rest candidates, to avoid the actual entropy coding of context-adaptive binary arithmetic coding for the calculation of the rate-distortion cost. Eventually, the fast algorithm of RDOQ is designed to determine the optimal quantized level, which supports parallel processing and is therefore favorable for hardware implementations. Experimental results demonstrate that the proposed method can decrease the time of RDOQ by 60.5 % in average with a superior RD performance in terms of encoding.
机译：率失真优化量化（RDOQ）通常在视频编码中用作追求高编码效率的有效工具。然而，RDOQ需要对多个候选者进行详尽搜索，以通过比较它们的速率失真成本来确定最佳量化级别，这在实践中导致相当大的复杂性。在熵编码中利用固有的强数据依赖性和高度顺序的处理来获得每个候选者的比特率信息进一步加剧了大计算量的问题。本文提出了一种RDOQ的高速实现方案，以代替H.264 / AVC中的常规RDOQ。所提出的方案计算复杂度低并且对硬件资源的需求是经济的。首先排除不太可能被选择的量化级别的候选者，然后为其余候选者构建一个比特率估计模型，以避免上下文自适应二进制算术编码的实际熵编码来计算速率。失真成本。最终，RDOQ的快速算法被设计为确定最佳量化级别，该级别支持并行处理，因此有利于硬件实现。实验结果表明，所提出的方法可以平均减少RDOQ的时间60.5％，在编码方面具有出色的RD性能。

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