Adaptive Probability Estimation Techniques for Context Adaptive Arithmetic Coding

M. Krishnan, Xin Zhao, Shanchun Liu
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Abstract

Context-adaptive arithmetic coding is an essential entropy coding scheme used in all modern video codecs. An arithmetic coder with binary symbol size is used by video codecs like H.264/AVC, HEVC and VVC while AV1 utilizes an arithmetic coder with syntax adaptive M-ary symbols. Recently, the Alliance for Open Media (AOMedia) has initiated exploration activities towards next-generation video coding tools beyond AV1. In this regard, improvements on probability estimation techniques for the context-adaptive M-ary arithmetic coder in AV1, are explored in this paper. The proposed improvements are applied and tested on top of the reference implementation of the exploratory codec beyond AV1, known as AVM (AOMedia Video Model). Experimental results show that, compared to AVM, the proposed method achieves an average 0.27%, 0.34% and 0.32% overall BD-rate coding gains for All Intra (AI), Random Access (RA) and Low Delay (LD) coding configurations for a wide range of video content.
上下文自适应算术编码的自适应概率估计技术
上下文自适应算术编码是一种基本的熵编码方案,在现代视频编解码器中得到广泛应用。H.264/AVC, HEVC和VVC等视频编解码器使用具有二进制符号大小的算术编码器,而AV1使用具有语法自适应M-ary符号的算术编码器。最近,开放媒体联盟(AOMedia)已经开始探索AV1以外的下一代视频编码工具。在这方面,本文探讨了AV1中上下文自适应M-ary算法编码器的概率估计技术的改进。提出的改进在AV1之外的探索性编解码器的参考实现上进行了应用和测试,称为AVM (amedia Video Model)。实验结果表明,与AVM相比,该方法在大范围视频内容的所有Intra (AI)、Random Access (RA)和Low Delay (LD)编码配置下平均获得0.27%、0.34%和0.32%的总bd率编码增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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