Consistent quality oriented rate control in video coding has attracted much more attention. However, the existing efforts only focus on decreasing variations between every two adjacent frames, but neglect coding trade-off problem between intra and inter frames. In this paper, we deal with it from a new perspective, where intra frame quantization parameter (IQP) and rate control are optimized for balanced coding. First, due to the importance of intra frames, a new framework is proposed for consistent quality oriented IQP prediction, and then we remove unqualified IQP candidates using the proposed penalty term. Second, we extensively evaluate possible features, and select target bits per pixel for all remaining frames, average and standard variance of frame QPs, where equivalent acquisition methods for QP features are given. Third, predicted IQPs are clipped effectively according to bandwidth and previous information for better bit rate accuracy. Compared with High Efficiency Video Coding (HEVC) reference baseline, experiments demonstrate that our method reduces quality fluctuation greatly by 37.2% on frame-level standard variance of peak-signal-noise-ratio (PSNR) and 45.1% on that of structural similarity (SSIM). Moreover, it also can have satisfactory results on Rate-Distortion (R-D) performance, bit accuracy and buffer control.
翻译:在视频编码中,以质量为导向的统一费率控制吸引了更多的关注。然而,目前的努力仅侧重于减少两个相邻框架之间的差异,而忽略了内部和内部框架之间的代码交换问题。在本文件中,我们从一个新的角度处理这一问题,即为平衡编码优化框架内量化参数和率控制。首先,由于内部框架的重要性,为一致的质量导向的互联网质量控制预测提议了新的框架,然后我们用拟议惩罚期删除不合格的互联网定量项目候选人。第二,我们广泛评价所有剩余框架的可能特点,并选择每像素的目标比特,选择框架QP的平均和标准差异,并给出QP等特征的同等购置方法。第三,预测的互联网量化指标根据带宽和以往信息有效剪短,以更精确的比值。与高效率视频编码参考基准相比,实验表明我们的方法大大降低了质量波动的37.2%(PSNR)和45.1%的框架标准差异(PS-NIS-R),同时,对结构性能的精确度(S-M)和45.D级的精确度也令人满意。