一种新的基于solpn的MPEG视频编码速率控制算法

Zhiming Zhang, Seung-Gi Chang, Jeonghoon Park, Yongje Kim
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引用次数: 0

摘要

提出了一种新的基于自组织学习Petri网的MPEG编码器速率控制算法。其思想是利用SOLPN实现在线自组织、逐帧自适应更新的RD (rate distortion)模型。该方法不需要离线预训练;因此它是面向实时编码的。实例的对比结果表明,与VM18相比,我们提出的速率控制方案编码的视频序列帧跳更少,具有良好的主观质量和更高的PSNR。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new SOLPN-based rate control algorithm for MPEG video coding
A new SOLPN (self-organizing learning Petri net)-based rate control algorithm for an MPEG encoder is proposed. The idea is to use SOLPN to realize the RD (rate distortion) model, which is self-organized on line and adaptively updated frame by frame. The method does not require off-line pre-training; hence it is geared toward real-time coding. The comparative results on the examples suggest that our proposed rate control schemes encode video sequences with fewer frame skips, providing good subjective quality and higher PSNR, compared to VM18.
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