The second generation Audio Video Coding Standard (AVS2) is the most recent video coding standard. By introducing several new coding techniques, AVS2 can provide more efficient compression for scene videos such as sur...The second generation Audio Video Coding Standard (AVS2) is the most recent video coding standard. By introducing several new coding techniques, AVS2 can provide more efficient compression for scene videos such as surveillance videos, conference videos, etc. Due to the limited scenes, scene videos have great redundancy especially in background region. The new scene video coding techniques applied in AVS2 mainly focus on reducing redundancy in order to achieve higher compression. This paper introduces several important AVS2 scene video coding techniques. Experimental results show that with scene video coding tools, AVS2 can save nearly 40%BD?rate (Bj?ntegaard?Delta bit?rate) on scene videos.展开更多
Following the success of the audio video standard （AVS） for 2D video coding, in 2008, the China AVS workgroup started developing 3D video （3DV） coding techniques. In this paper, we discuss the background, technica...Following the success of the audio video standard （AVS） for 2D video coding, in 2008, the China AVS workgroup started developing 3D video （3DV） coding techniques. In this paper, we discuss the background, technical features, and applications of AVS 3DV coding technology. We introduce two core techniques used in AVS 3DV coding： inter-view prediction and enhanced stereo packing coding. We elaborate on these techniques, which are used in the AVS real-time 3DV encoder. An application of the AVS 3DV coding system is presented to show the great practical value of this system. Simulation results show that the advanced techniques used in AVS 3DV coding provide remarkable coding gain compared with techniques used in a simulcast scheme.展开更多
针对多功能视频编码(Versatile Video Coding,VVC)标准中跨通道线性预测模型(Cross-Component Linear Model,CCLM)无法很好地拟合色度与亮度之间的非线性对应关系这一不足,提出了一种基于注意力机制卷积神经网络的VVC色度预测算法。该...针对多功能视频编码(Versatile Video Coding,VVC)标准中跨通道线性预测模型(Cross-Component Linear Model,CCLM)无法很好地拟合色度与亮度之间的非线性对应关系这一不足,提出了一种基于注意力机制卷积神经网络的VVC色度预测算法。该算法主要思想是在进行色度预测时,使用对应亮度块的信息与待预测色度块上方与左方的信息作为参考信息输入进卷积神经网络,利用注意力机制对参考信息中的亮度与色度间的内在联系进行分配权重后输入预测网络。实验结果表明,相较于VVC标准算法U分量和V分量的平均码率节省分别为0.64%和0.68%,有效提升了VVC编码性能。展开更多
基金supported by the National Basic Research Program of China under grant 2015CB351806the National Natural Science Foundation of China under contract No.61425025,No.61390515 and No.61421062Shenzhen Peacock Plan
文摘The second generation Audio Video Coding Standard (AVS2) is the most recent video coding standard. By introducing several new coding techniques, AVS2 can provide more efficient compression for scene videos such as surveillance videos, conference videos, etc. Due to the limited scenes, scene videos have great redundancy especially in background region. The new scene video coding techniques applied in AVS2 mainly focus on reducing redundancy in order to achieve higher compression. This paper introduces several important AVS2 scene video coding techniques. Experimental results show that with scene video coding tools, AVS2 can save nearly 40%BD?rate (Bj?ntegaard?Delta bit?rate) on scene videos.
文摘Following the success of the audio video standard （AVS） for 2D video coding, in 2008, the China AVS workgroup started developing 3D video （3DV） coding techniques. In this paper, we discuss the background, technical features, and applications of AVS 3DV coding technology. We introduce two core techniques used in AVS 3DV coding： inter-view prediction and enhanced stereo packing coding. We elaborate on these techniques, which are used in the AVS real-time 3DV encoder. An application of the AVS 3DV coding system is presented to show the great practical value of this system. Simulation results show that the advanced techniques used in AVS 3DV coding provide remarkable coding gain compared with techniques used in a simulcast scheme.
文摘针对多功能视频编码(Versatile Video Coding,VVC)标准中跨通道线性预测模型(Cross-Component Linear Model,CCLM)无法很好地拟合色度与亮度之间的非线性对应关系这一不足,提出了一种基于注意力机制卷积神经网络的VVC色度预测算法。该算法主要思想是在进行色度预测时,使用对应亮度块的信息与待预测色度块上方与左方的信息作为参考信息输入进卷积神经网络,利用注意力机制对参考信息中的亮度与色度间的内在联系进行分配权重后输入预测网络。实验结果表明,相较于VVC标准算法U分量和V分量的平均码率节省分别为0.64%和0.68%,有效提升了VVC编码性能。
