基于广义高斯分布建模帧级变换系数的VVC编码失真预测模型

VVC coded distortion prediction model based on frame-level transform coefficient modeling of generalized Gaussian distribution

通用视频编码(versatile video coding,VVC)采用多种高级编码工具共同实现卓越的编码性能。与高效视频编码(high efficient video coding,HEVC)相比,VVC的变换系数分布(transform coefficient distribution,TCD)具有更尖锐的峰值。针对这一现象,对帧级TCD进行概率密度函数(probability density function,PDF)建模,并提出一种基于统计建模的帧级编码失真预测模型,将帧级失真建模为TCD分布参数和量化参数的函数。实验结果表明,相比于拉普拉斯分布以及柯西分布,广义高斯分布在TCD概率密度拟合方面表现最佳;基于广义高斯分布的失真预测模型的预测结果最接近实际编码失真。

In versatile video coding(VVC),a variety of advanced coding tools work together to achieve excellent coding performance.Compared with high efficient video coding(HEVC),the transform coefficient distribution(TCD)of VVC has sharper peaks.In order to solve this phenomenon,the probability density function(PDF)of frame-level TCD was modeled,and a frame-level coding distortion prediction model based on statistical modeling was proposed,which modeled frame-level distortion as a function of TCD distribution parameters and quantization parameters.The experimental results show that compared with the Laplace distribution and Cauchy distribution,the generalized Gaussian distribution has the best performance in TCD probability density fitting.The prediction results based on the generalized Gaussian distribution distortion prediction model are closest to the actual coding distortion.