由于H.264/AVC采用的码率控制模型忽略了视频特性对初始帧量化参数(Initial Quantization Parameter, QP0)选择的影响, 本文提出了一种新的基于视频特性的QP0估计算法来提高H.264/AVC的码率控制精度。首先, 分析影响QP0的视频特性, 包括每像素比特数(bpp)、视频序列的复杂度和图像组(GOP)长度; 然后, 通过大量的测试仿真建立了QP0与bpp和视频序列复杂度之间的函数关系; 最后, 结合GOP长度对QP0的影响, 修正了QP0模型。实验结果表明: 相比JM12.2中的算法, 提出的算法使四分之一通用中间格式(QCIF)和通用中间格式序列重建帧的平均峰值信噪比(PSNR)分别提高了0.185 dB和0.144 dB; 码率控制误差的控制幅度分别提高了37.3%和11.2%; 序列中每帧图像间的质量波动均降低了约50%。该方法在提高重建帧质量的同时, 大幅度降低了码率控制误差, 有效地抑制了序列间每帧图像的质量波动, 获得了更优质、平稳的编码视频流, 并能很好地适应不同特性的视频序列。

As the rate control model in H.264/AVC ignores the influence of video features on the selection of a Initial Quantization Parameter (QP0), this paper proposes a novel QP0 algorithm based on video features to improve the performance of H.264/AVC rate control. First, video features which have influence on the determination of QP0 were analyzed, such as (bit per pix, bpp), video complexities and length of Group of Picture (GOP). Then, functional relationships between QP0 and bpp, QP0 and video complexity were established through extensive simulation. Finally, considering the influence of the length of GOP on the QP0, the QP0 model was revised. Experimental results show that the proposed algorithm increases the average Peak Signal-to-Noise Ratio(PSNR) of reconstructed video by 0.185 dB for Quarter Common Interchange format(QCIF) and 0.144 dB for Common Interchange format (CIF) sequence as compared with the algorithm in JM12.2. According to the error of rate control, the control amplitude is increased to 37.3% for the QCIF sequence and 11.2% for the CIF sequence. Moreover, the PSNR fluctuations are reduced by 50% for both sequences. In conclusion, the proposed method not only decreases the error of rate control, but also depresses PSNR fluctuations effectively.