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Joint source channel rate-distortion analysis for adaptive modeselection and rate control in wireless video coding

机译:无线视频编码中自适应模式选择和速率控制的联合源信道速率失真分析

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We first develop a rate-distortion (R-D) model for DCT-based video coding incorporating the macroblock (MB) intra refreshing rate. For any given bit rate and intra refreshing rate, this model is capable of estimating the corresponding coding distortion even before a video frame is coded. We then present a theoretical analysis of the picture distortion caused by channel errors and the subsequent inter-frame propagation. Based on this analysis, we develop a statistical model to estimate such channel errors induced distortion for different channel conditions and encoder settings. The proposed analytic model mathematically describes the complex behavior of channel errors in a video coding and transmission system. Unlike other experimental approaches for distortion estimation reported in the literature, this analytic model has very low computational complexity and implementation cost, which are highly desirable in wireless video applications. Simulation results show that this model is able to accurately estimate the channel errors induced distortion with a minimum delay in processing. Based on the proposed source coding R-D model and the analytic channel-distortion estimation, we derive an analytic solution for adaptive intra mode selection and joint source-channel rate control under time-varying wireless channel conditions. Extensive experimental results demonstrate that this scheme significantly improves the end-to-end video quality in wireless video coding and transmission
机译:我们首先为结合了宏块(MB)帧内刷新率的基于DCT的视频编码开发了一种率失真(R-D)模型。对于任何给定的比特率和帧内刷新率,即使在对视频帧进行编码之前,该模型也能够估计相应的编码失真。然后,我们提出了由通道错误和随后的帧间传播引起的图像失真的理论分析。基于此分析,我们开发了一种统计模型,以估算在不同的通道条件和编码器设置下,此类通道错误导致的失真。所提出的分析模型在数学上描述了视频编码和传输系统中信道错误的复杂行为。与文献中报道的其他用于失真估计的实验方法不同,该分析模型的计算复杂度和实现成本非常低,在无线视频应用中非常需要。仿真结果表明,该模型能够以最小的处理延迟准确估计信道误差引起的失真。基于提出的源编码R-D模型和信道失真分析估计,我们推导了在时变无线信道条件下自适应帧内模式选择和联合源信道速率控制的解析解决方案。大量的实验结果表明,该方案可显着提高无线视频编码和传输中的端到端视频质量

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