Content Adaptive Quantization Parameter Cascading for Surveillance Video Coding Using Versatile Video Coding

GONG Yanchao; ZHANG Sensen; HE Shuting; LI Baogui; LIU Ying; LIM Keng-Pang

doi:10.7652/xjtuxb202312004

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Content Adaptive Quantization Parameter Cascading for Surveillance Video Coding Using Versatile Video Coding

更新时间：2025-07-09

- Content Adaptive Quantization Parameter Cascading for Surveillance Video Coding Using Versatile Video Coding
- Vol. 57, Issue 12, Pages: 30-40(2023)
- 作者机构：
  
  1. 西安邮电大学通信与信息工程学院,西安,710121
  2. 陕西省法庭科学电子信息实验研究中心,西安,710121
  3. 陕西省无线通信与信息处理技术国际联合研究中心,西安,710121
  4. 新加坡XsecPro公司,新加坡,787820
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202312004
  CLC： TN911.7
- Online First：10 December 2023，
  
  Published：2023
- 稿件说明：
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GONG Yanchao, ZHANG Sensen, HE Shuting, et al. Content Adaptive Quantization Parameter Cascading for Surveillance Video Coding Using Versatile Video Coding[J]. 2023, 57(12): 30-40.
DOI：

GONG Yanchao, ZHANG Sensen, HE Shuting, et al. Content Adaptive Quantization Parameter Cascading for Surveillance Video Coding Using Versatile Video Coding[J]. 2023, 57(12): 30-40. DOI： 10.7652/xjtuxb202312004.

摘要

最新通用视频编码(VVC)标准测试模型VTM推荐的JCTVC-X0038量化参数级联方法未考虑监控视频的内容特性

编码效率低。针对这一问题

提出了一种有效考虑监控视频空时域内容特性的VVC量化参数级联方法(SCA-QPC)。基于VVC混合编码框架原理

理论分析得出时间层及监控视频的空时域内容特性是影响量化参数(QP)选择的关键因素

设计编码实验对理论分析结果进行验证; 采用梯度和背景帧差分别评测监控视频的空域和时域特性

将梯度和背景帧差作为反向传播神经网络的输入

构建预测低时延结构时间层对应最优QP的模型; 提出适用于VVC标准有效提高监控视频编码效率的量化参数级联方法。与当前最先进的JCTVC-X0038量化参数级联方法相比

对于所有测试序列

SCA-QPC对应的平均BD-rate为-4.26%。研究对于VVC编码框架中量化参数级联和码率控制模块的优化具有指导意义。

Abstract

The JCTVC-X0038 quantization parameter cascading(QPC)method recommended by the latest versatile video coding(VVC)standard test model VTM has low coding efficiency because the surveillance video content characteristics are not considered. For this problem

a VVC QPC method considering the spatio-temporal content characteristics of the surveillance videos

referred to as SCA-QPC

was proposed. First

based on the VVC hybrid coding framework principle

it was found that the temporal layer and spatio-temporal content characteristics of the surveillance videos were the key factors affecting the selection of quantization parameters(QP)by theoretical analysis. And the coding experiments were further carried out to verify the results of the theoretical analysis. Then the gradient and background frame difference were used to measure the spatio-temporal characteristics of the surveillance videos respectively and further used as the inputs to the back propagation neural network to construct a model predicting the optimal QPs corresponding to temporal layers in low delay structure. Finally

the SCA-QPC suitable for VVC standard was proposed to effectively improve the surveillance video coding efficiency. Compared with the state-of-the-art JCTVC-X0038 QPC method

the average BD-rate of SCA-QPC is -4.26% for all test sequences. This study can guide the optimization of QPC and rate control modules in the VVC coding framework.

关键词

Keywords

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