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Improved strategy of QP decision for hierarchical B pictures structure in SVC

机译:SVC中分层B图片结构QP决策策略的改进策略

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In Scalable Video Coding (SVC) the coding efficiency for hierarchical prediction structures is highly dependent on how to choose the quantization parameters (QP) for pictures of different temporal layers. For pictures that have strong temporal correlation and pictures at low bitrate, large peak SNR (PSNR) fluctuations will be produced when using the strategy presented in the proposal JVT-P014. In order to decrease the fluctuations this paper proposed a new method which combines the persistence of vision to decrease the fluctuations of the video quality. Simulated results show that the proposed technique is efficient. When compared with the method in the proposal JVT-P014, the PSNR difference decreases is about 20%, and it is more effectively for the pictures with strong temporal correlation. The algorithm in this paper provides valuable references for further study of optimizing encoder.
机译:在可伸缩的视频编码(SVC)中,分层预测结构的编码效率高度依赖于如何选择不同时间层图片的量化参数(QP)。对于具有低比特率下的时间相关性和图片的图片,在使用提案JVT-P014中提出的策略时,将产生大峰值SNR(PSNR)波动。为了减少本文的波动,提出了一种新方法,该方法结合了视力的持久性来降低视频质量的波动。模拟结果表明,所提出的技术是有效的。与提案JVT-P014中的方法相比,PSNR差减小约为20%,并且更有效地用于具有强烈的时间相关性的图像。本文的算法提供了有价值的参考,用于进一步研究优化编码器。

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