Rate control using enhanced frame complexity measure for H.264 video

Xiaoquan Yi, N. Ling
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引用次数: 16

Abstract

Bit rate control is an important issue for wireless and Internet video streaming. The paper presents a revised rate control scheme based on an improved frame complexity measure. Rate control adopted by both MPEG-4 VM18 and H.264/AVC uses a quadratic rate-distortion (R-D) model that determines quantization parameters (QPs). The classical quadratic R-D model is suitable for MPEG-4, but it performs poorly for H.264/AVC because one of the important parameters, mean absolute difference (MAD), is predicted through a linear model, whereas the MAD used in MPEG-4 VM18 is the actual MAD. Inaccurately predicted MAD results in the wrong QP and consequently degrades rate distortion optimization (RDO) performance in H.264/AVC. To overcome the limitation of the existing rate control schemes, we introduce an enhanced linear model for predicting MAD, utilizing some knowledge of current frame complexity. Moreover, we propose a more accurate frame complexity measure, namely, normalized MAD, to replace the current use of MAD parameters. Normalized MAD has a stronger correlation with optimally allocated bits than that of the predicted MAD. Finally, a dynamic bit allocation scheme among basic units is implemented. Extensive simulation results show that our method, with inexpensive added computational complexity, improves the average peak signal-to-noise ratio (PSNR) considerably, by up to 1.2 dB, and reduces PSNR variances significantly, by up to 63%.
基于增强帧复杂度度量的H.264视频速率控制
比特率控制是无线和互联网视频流的一个重要问题。本文提出了一种基于改进的帧复杂度度量的改进速率控制方案。MPEG-4 VM18和H.264/AVC采用的速率控制都使用二次率失真(R-D)模型来确定量化参数(QPs)。经典的二次R-D模型适用于MPEG-4,但它在H.264/AVC中表现不佳,因为其中一个重要参数平均绝对差(MAD)是通过线性模型预测的,而MPEG-4 VM18中使用的MAD是实际的MAD。不准确的预测MAD会导致错误的QP,从而降低H.264/AVC的率失真优化(RDO)性能。为了克服现有速率控制方案的局限性,我们引入了一种增强的线性模型来预测MAD,利用当前帧复杂度的一些知识。此外,我们提出了一种更准确的帧复杂度度量,即规范化MAD,以取代目前使用的MAD参数。与预测的MAD相比,规范化的MAD与最佳分配位的相关性更强。最后,实现了基本单元之间的动态位分配方案。大量的仿真结果表明,我们的方法在不增加计算复杂度的情况下,显著提高了平均峰值信噪比(PSNR),最高可达1.2 dB,并显著降低了PSNR方差,最高可达63%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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