CTU-Level Adaptive Quantization Method Joint with GOP based Temporal Filter for Video Coding

Both Versatile Video Coding (VVC) and High Efficiency Video Coding (HEVC) introduce Group of Pictures (GOP) based temporal filter (GBTF) as a pre-filter to improve compression performance. While numerous efforts have been made to optimize GBTF, there is a limited amount of research that explicitly a...

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Bibliographic Details
Main Authors: He, Chenlong, Li, Wei, Chen, Xiaoxiang, Hao, Zhijian, Liu, Chao, Zeng, Xiaoyang, Fan, Yibo
Format: Conference Proceeding
Language:English
Subjects:
Adaptive Quantization
Bit rate
Circuits and systems
Encoding
GOP based temporal filter (GBTF)
Indexes
PSNR
Quantization (signal)
Resource management
Versatile Video Coding (VVC)
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Summary:Both Versatile Video Coding (VVC) and High Efficiency Video Coding (HEVC) introduce Group of Pictures (GOP) based temporal filter (GBTF) as a pre-filter to improve compression performance. While numerous efforts have been made to optimize GBTF, there is a limited amount of research that explicitly addresses why GBTF could improve compression performance. Additionally, most optimizations have focused on the design of the filter itself, rather than on how to better integrate it with other encoding tools. In this paper, we analyze the reasons behind the superior compression performance of GBTF. Subsequently, we introduce a Coding Tree Unit (CTU)-level adaptive quantization parameter allocation method joint with GBTF to further enhance compression performance for video coding. The experimental results demonstrate that, for VVC, our method provides Bjontegaard delta bit rate (BD-BR) savings of 2.0% for Peak Signal-to-Noise Ratio (PSNR) and 4.0% for Structural Similarity index (SSIM). Furthermore, for HEVC, our method provides BD-BR savings of 3.5% for PSNR and 7.6% for SSIM.
ISSN:2158-1525
DOI:10.1109/ISCAS58744.2024.10558129