多功能视频编码(versatile video coding,VVC)是最新的视频编码标准,与高效视频编码(high efficiency video coding,HEVC)相比进一步提高了压缩效率,但由于引入了包括二叉树和三叉树在内的多类树结构,同时帧内角度模式从35种增加到67种...多功能视频编码(versatile video coding,VVC)是最新的视频编码标准,与高效视频编码(high efficiency video coding,HEVC)相比进一步提高了压缩效率,但由于引入了包括二叉树和三叉树在内的多类树结构,同时帧内角度模式从35种增加到67种,导致编码复杂度剧增。为了降低计算复杂度,本文提出了一种基于快速编码单元(coding unit,CU)划分和角度模式决策的VVC帧内编码算法。首先根据自适应标准差阈值对CU纹理复杂度进行分类,初步缩减划分模式列表;然后采用Sobel梯度算子确定纹理方向,跳过非最优划分模式;最后根据统计结果筛选淘汰掉概率小于2%的角度模式。实验结果表明,与VTM-2.1相比,该算法能节省51.05%的编码时间,BDBR(Bjontegarrd delta bit rate)仅上升1.98%。展开更多
With CO combustion promoters, the role of combustion air flow rate for concerns of economics and control is important. The combustion air is conceptually divided to three parts: the air consumed by coke burning,the ai...With CO combustion promoters, the role of combustion air flow rate for concerns of economics and control is important. The combustion air is conceptually divided to three parts: the air consumed by coke burning,the air consumed by CO combustion and the air unreacted. A mathematical model of a fluid catalytic cracking(FCC)unit, which includes a quantitative correlation of CO heterogeneous combustion and the amount of CO combustion promoters, is introduced to investigate the effects of promoters on the three parts of combustion air. The results show that the air consumed by coke burning is almost linear to combustion air flow rate, while the air consumed by CO combustion promoters tends to saturate as combustion air flow rate increases, indicating that higher air flow rate can only be used as a manipulated variable to control the oxygen content for an economic concern.展开更多
通用视频编码(Versatile Video Coding,VVC)是正在探索中的下一代视频编解码标准,在新标准的制定过程中,加入了许多新技术,在提升编码性能的同时,增加了编码复杂度。针对这种情况,通过对新标准编码过程中帧间预测单元划分算法的研究发现...通用视频编码(Versatile Video Coding,VVC)是正在探索中的下一代视频编解码标准,在新标准的制定过程中,加入了许多新技术,在提升编码性能的同时,增加了编码复杂度。针对这种情况,通过对新标准编码过程中帧间预测单元划分算法的研究发现,在VVC进行帧间单元划分时,进行了多余的更深层次的划分,从而提高了编码复杂度。因此提出了一种划分层次限制的快速帧间预测算法,使单元划分提前结束,避免了多余的划分层次。实验结果表明,新算法在RA配置下,在增加1.58%的压缩率,损失0.0362的图像失真度的情况下,编码复杂度降低了46.39%,从而验证了优化算法能有效降低编码复杂度。展开更多
Versatile video coding(H.266/VVC),which was newly released by the Joint Video Exploration Team(JVET),introduces quad-tree plus multitype tree(QTMT)partition structure on the basis of quad-tree(QT)partition structure i...Versatile video coding(H.266/VVC),which was newly released by the Joint Video Exploration Team(JVET),introduces quad-tree plus multitype tree(QTMT)partition structure on the basis of quad-tree(QT)partition structure in High Efficiency Video Coding(H.265/HEVC).More complicated coding unit(CU)partitioning processes in H.266/VVC significantly improve video compression efficiency,but greatly increase the computational complexity compared.The ultra-high encoding complexity has obstructed its real-time applications.In order to solve this problem,a CU partition algorithm using convolutional neural network(CNN)is proposed in this paper to speed up the H.266/VVC CU partition process.Firstly,64×64 CU is divided into smooth texture CU,mildly complex texture CU and complex texture CU according to the CU texture characteristics.Second,CU texture complexity classification convolutional neural network(CUTCC-CNN)is proposed to classify CUs.Finally,according to the classification results,the encoder is guided to skip different RDO search process.And optimal CU partition results will be determined.Experimental results show that the proposed method reduces the average coding time by 32.2%with only 0.55%BD-BR loss compared with VTM 10.2.展开更多
文摘多功能视频编码(versatile video coding,VVC)是最新的视频编码标准,与高效视频编码(high efficiency video coding,HEVC)相比进一步提高了压缩效率,但由于引入了包括二叉树和三叉树在内的多类树结构,同时帧内角度模式从35种增加到67种,导致编码复杂度剧增。为了降低计算复杂度,本文提出了一种基于快速编码单元(coding unit,CU)划分和角度模式决策的VVC帧内编码算法。首先根据自适应标准差阈值对CU纹理复杂度进行分类,初步缩减划分模式列表;然后采用Sobel梯度算子确定纹理方向,跳过非最优划分模式;最后根据统计结果筛选淘汰掉概率小于2%的角度模式。实验结果表明,与VTM-2.1相比,该算法能节省51.05%的编码时间,BDBR(Bjontegarrd delta bit rate)仅上升1.98%。
基金Supported by the National Natural Science Foundation of China(21006127)the National Basic Research Program of China(2012CB720500)
文摘With CO combustion promoters, the role of combustion air flow rate for concerns of economics and control is important. The combustion air is conceptually divided to three parts: the air consumed by coke burning,the air consumed by CO combustion and the air unreacted. A mathematical model of a fluid catalytic cracking(FCC)unit, which includes a quantitative correlation of CO heterogeneous combustion and the amount of CO combustion promoters, is introduced to investigate the effects of promoters on the three parts of combustion air. The results show that the air consumed by coke burning is almost linear to combustion air flow rate, while the air consumed by CO combustion promoters tends to saturate as combustion air flow rate increases, indicating that higher air flow rate can only be used as a manipulated variable to control the oxygen content for an economic concern.
文摘通用视频编码(Versatile Video Coding,VVC)是正在探索中的下一代视频编解码标准,在新标准的制定过程中,加入了许多新技术,在提升编码性能的同时,增加了编码复杂度。针对这种情况,通过对新标准编码过程中帧间预测单元划分算法的研究发现,在VVC进行帧间单元划分时,进行了多余的更深层次的划分,从而提高了编码复杂度。因此提出了一种划分层次限制的快速帧间预测算法,使单元划分提前结束,避免了多余的划分层次。实验结果表明,新算法在RA配置下,在增加1.58%的压缩率,损失0.0362的图像失真度的情况下,编码复杂度降低了46.39%,从而验证了优化算法能有效降低编码复杂度。
基金This paper is supported by the following funds:The National Key Research and Development Program of China(2018YFF01010100)Basic Research Program of Qinghai Province under Grants No.2021-ZJ-704,The Beijing Natural Science Foundation(4212001)Advanced information network Beijing laboratory(PXM2019_014204_500029).
文摘Versatile video coding(H.266/VVC),which was newly released by the Joint Video Exploration Team(JVET),introduces quad-tree plus multitype tree(QTMT)partition structure on the basis of quad-tree(QT)partition structure in High Efficiency Video Coding(H.265/HEVC).More complicated coding unit(CU)partitioning processes in H.266/VVC significantly improve video compression efficiency,but greatly increase the computational complexity compared.The ultra-high encoding complexity has obstructed its real-time applications.In order to solve this problem,a CU partition algorithm using convolutional neural network(CNN)is proposed in this paper to speed up the H.266/VVC CU partition process.Firstly,64×64 CU is divided into smooth texture CU,mildly complex texture CU and complex texture CU according to the CU texture characteristics.Second,CU texture complexity classification convolutional neural network(CUTCC-CNN)is proposed to classify CUs.Finally,according to the classification results,the encoder is guided to skip different RDO search process.And optimal CU partition results will be determined.Experimental results show that the proposed method reduces the average coding time by 32.2%with only 0.55%BD-BR loss compared with VTM 10.2.