CABAC的高精度概率估计

A. Alshin, E. Alshina, Jeonghoon Park
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引用次数: 20

摘要

熵编码是所有高级视频压缩方案的重要组成部分。上下文自适应二进制算术编码(CABAC)是H.264/MPEG-4 AVC和H.265/HEVC标准中使用的熵编码。概率估计是影响CABAC性能效率的关键因素。本文提出了CABAC的高精度概率估计方法。该技术基于使用不同模型的多重估计。该方法在整数算法中得到了有效的实现。高精度的CABAC概率估计可提供高达1.4%的bd速率增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High precision probability estimation for CABAC
Entropy coding is the main important part of all advanced video compression schemes. Context-adaptive binary arithmetic coding (CABAC) is entropy coding used in H.264/MPEG-4 AVC and H.265/HEVC standards. Probability estimation is the key factor of CABAC performance efficiency. In this paper high accuracy probability estimation for CABAC is presented. This technique is based on multiple estimations using different models. Proposed method was efficiently realized in integer arithmetic. High precision probability estimation for CABAC provides up-to 1,4% BD-rate gain.
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