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Adaptive Parallelization Based on Frame-Level and Tile-Level Parallelisms for VVC Encoding

delete2025-11-30
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OA
AI
K
Karin Onouchi *
M
Masayuki Sato
H
Hiroe Iwasaki
K
Kazuhiko Komatsu
H
Hiroaki Kobayashi
DOI:10.1002/cpe.70376delete
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Abstract

Abstract

En 中文
To meet the growing demand for high-efficiency video compression standards, Versatile Video Coding (VVC) has been developed as a successor to High Efficiency Video Coding (HEVC). VVC offers approximately a 50% reduction in bitrate compared to HEVC while maintaining comparable visual quality. However, the improved performance of VVC comes at the cost of a significantly higher computational complexity, resulting in longer encoding times. Consequently, accelerating the VVC encoding process remains a critical challenge for its practical deployment. Leveraging the evolution of multi-core processors and encoding tools designed for parallel processing, this study introduces an adaptive parallelization method that integrates frame-level and tile-level parallelisms. This method dynamically selects the number of concurrently processed frames and tiles by considering reference dependencies and their effects on coding efficiency. Moreover, the proposed method employs a content-aware, cyclic adjustment of tile configurations to further reduce the encoding time. The evaluation results demonstrate that the proposed method can achieve a 10.58x speedup over the baseline single-threaded implementation on average, while limiting the increase in BD-BR to 3.23% and the degradation in BD-PSNR to only -0.058 dB. These findings confirm that the method substantially decreases the encoding time without degrading coding efficiency. Furthermore, the results also demonstrate that the scalability of the proposed method is better than that of the conventional parallel method, Wavefront parallel processing.
Keywords:
parallelization
tile
video compression
VVC
VVenC
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Journal

C
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
IF:
1.5
Papers:
473
Citations:
0

Organization

T
tohoku university
Scholars:
4.3W
Papers: 3.6W
Citations: 31