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

顾轶寅; 王鸿奎; 殷海兵

doi:10.11959/j.issn.1000-0801.2023088

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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

研究与开发 | 更新时间：2024-06-05

- 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
- 电信科学 2023年39卷第4期页码：101-110
- 作者机构：
- 作者简介：
  
  [ "顾轶寅（1997- ），男，杭州电子科技大学通信工程学院硕士生，主要研究方向为视频编解码" ]
  [ "王鸿奎（1990- ），男，博士，杭州电子科技大学通信工程学院讲师，主要研究方向为感知视频编码" ]
  [ "殷海兵（1974- ），男，博士，杭州电子科技大学通信工程学院教授，主要研究方向为数字视频编解码" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61972123);国家自然科学基金资助项目;The National Natural Science Foundation of China(61931008);国家自然科学基金资助项目;The National Natural Science Foundation of China(62202134);浙江省“尖兵”“领雁”研发攻关计划项目;Zhejiang Provincial “Pioneer” and“Leading Goose” Research and Development Project(2022C01068)
- DOI：10.11959/j.issn.1000-0801.2023088
  中图分类号： TP393
- 网络出版日期：2023-04，
  
  纸质出版日期：2023-04-20
- 稿件说明：
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顾轶寅, 王鸿奎, 殷海兵. 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[J]. 电信科学, 2023,39(4):101-110.

Yiyin GU, Hongkui WANG, Haibin YIN. VVC coded distortion prediction model based on frame-level transform coefficient modeling of generalized Gaussian distribution[J]. Telecommunications science, 2023, 39(4): 101-110.
顾轶寅, 王鸿奎, 殷海兵. 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[J]. 电信科学, 2023,39(4):101-110. DOI： 10.11959/j.issn.1000-0801.2023088.

Yiyin GU, Hongkui WANG, Haibin YIN. VVC coded distortion prediction model based on frame-level transform coefficient modeling of generalized Gaussian distribution[J]. Telecommunications science, 2023, 39(4): 101-110. DOI： 10.11959/j.issn.1000-0801.2023088.

摘要

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。

Abstract

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.

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references

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