Quality degradation occurs during transmission of video streaming over the error-prone network. By jointly using redundant slice, reference frame selection, and intra/inters mode decision, a content and end-to-end rat...Quality degradation occurs during transmission of video streaming over the error-prone network. By jointly using redundant slice, reference frame selection, and intra/inters mode decision, a content and end-to-end rate-distortion based error resilience method is proposed. Firstly, the intra/inter mode decision is implemented using macro-block(MB) refresh, and then redundant picture and reference frame selection are utilized together to realize the redundant coding. The estimated error propagation distortion and bit consumption of refresh MB are used for the mode and reference frame decision of refresh MB. Secondly, by analyzing the statistical property in the successive frames, the error propagation distortion and bit consumption are formulated as a function of temporal distance. Encoding parameters of the current frame is determined by the estimated error propagation distortion and bit consumption. Thirdly, by comparing the rate-distortion cost of different combinations, proper selection of error resilience method is performed before the encoding process of the current frame. Finally, the MB mode and bit distribution of the primary picture are analyzed for the derivation of the texture information. The motion information is subsequently incorporated for the calculation of video content complexity to implement the content based redundant coding. Experimental results demonstrate that the proposed algorithm achieves significant performance gains over the LA-RDO and HRP method when video is transmitted over error-prone channel.展开更多
高效视频编码(high efficiency video coding,HEVC)相较于上一代编码标准H.264降低了约50%的比特率,但为了提高帧内预测的准确性,HEVC提出的35种预测模式导致计算量大幅增加,对软件和硬件实现均构成了挑战.针对该问题,在HEVC的基础上提...高效视频编码(high efficiency video coding,HEVC)相较于上一代编码标准H.264降低了约50%的比特率,但为了提高帧内预测的准确性,HEVC提出的35种预测模式导致计算量大幅增加,对软件和硬件实现均构成了挑战.针对该问题,在HEVC的基础上提出了一种依据图片纹理方向,结合预测模式之间的关联性来确定帧内预测模式的快速算法.实验结果表明,本算法与HEVC参考软件HM16.20相比,在BD-Rate损失仅为5.79%的情况下,节省46%以上的编码时间,显著降低了帧内预测模式决策的复杂度,便于在嵌入式系统等硬件资源有限的端侧实现算法落地.展开更多
基金Project(40927001)supported by the National Natural Science Foundation of ChinaProject(2011R09021-06)supported by the Program of Key Scientific and Technological Innovation Team of Zhejiang Province,ChinaProject supported by the Fundamental Research Funds for the Central Universities of China
文摘Quality degradation occurs during transmission of video streaming over the error-prone network. By jointly using redundant slice, reference frame selection, and intra/inters mode decision, a content and end-to-end rate-distortion based error resilience method is proposed. Firstly, the intra/inter mode decision is implemented using macro-block(MB) refresh, and then redundant picture and reference frame selection are utilized together to realize the redundant coding. The estimated error propagation distortion and bit consumption of refresh MB are used for the mode and reference frame decision of refresh MB. Secondly, by analyzing the statistical property in the successive frames, the error propagation distortion and bit consumption are formulated as a function of temporal distance. Encoding parameters of the current frame is determined by the estimated error propagation distortion and bit consumption. Thirdly, by comparing the rate-distortion cost of different combinations, proper selection of error resilience method is performed before the encoding process of the current frame. Finally, the MB mode and bit distribution of the primary picture are analyzed for the derivation of the texture information. The motion information is subsequently incorporated for the calculation of video content complexity to implement the content based redundant coding. Experimental results demonstrate that the proposed algorithm achieves significant performance gains over the LA-RDO and HRP method when video is transmitted over error-prone channel.
文摘高效视频编码(high efficiency video coding,HEVC)相较于上一代编码标准H.264降低了约50%的比特率,但为了提高帧内预测的准确性,HEVC提出的35种预测模式导致计算量大幅增加,对软件和硬件实现均构成了挑战.针对该问题,在HEVC的基础上提出了一种依据图片纹理方向,结合预测模式之间的关联性来确定帧内预测模式的快速算法.实验结果表明,本算法与HEVC参考软件HM16.20相比,在BD-Rate损失仅为5.79%的情况下,节省46%以上的编码时间,显著降低了帧内预测模式决策的复杂度,便于在嵌入式系统等硬件资源有限的端侧实现算法落地.
