Parallel-Based Fast Coding Mode Decision for Intra Coding in VVC SCC

In light of the growing popularity of screen content video applications, there is a increasing demand for Screen Content Coding (SCC). The latest standard, Versatile Video Coding (VVC), exhibits exceptionally high coding efficiency, albeit accompanied by a considerable coding complexity. This complexity, in turn, restricts the widespread applicability of VVC SCC. To address this issue, this paper introduces a parallel based approach to enhance the coding speed of VVC SCC Intra Coding. Specifically, we established a large-scale database and then design distinct neural networks for Coding Units (CUs) of various sizes to predict candidate Coding Modes (CMs). Subsequently, we formulate a loss function based on CM distributions and Rate Distortion(RD) costs to train the designed models. Finally, we introduce a threshold selection scheme to balance coding efficiency and coding speed. Experimental results demonstrate that the proposed method improves coding speed by an average of 36.36%, with an average increase of 0.95% in Bjøntegaard Delta Bit Rate (BDBR).

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Published
2025-08-18
DOI
https://doi.org/10.1109/icip55913.2025.11084476
Primary Topic
Video Coding and Compression Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Parallel-Based Fast Coding Mode Decision for Intra Coding in VVC SCC

Weian Li, Fréderic Dufaux, Xin Lu, Hongwei Guo et al.
Video Coding and Compression Technologies
article

Parallel-Based Fast Coding Mode Decision for Intra Coding in VVC SCC

Weian Li, Fréderic Dufaux, Xin Lu, Hongwei Guo, Dayong Wang, Shibin Zhang, Kongqing Peng
article en

Abstract

In light of the growing popularity of screen content video applications, there is a increasing demand for Screen Content Coding (SCC). The latest standard, Versatile Video Coding (VVC), exhibits exceptionally high coding efficiency, albeit accompanied by a considerable coding complexity. This complexity, in turn, restricts the widespread applicability of VVC SCC. To address this issue, this paper introduces a parallel based approach to enhance the coding speed of VVC SCC Intra Coding. Specifically, we established a large-scale database and then design distinct neural networks for Coding Units (CUs) of various sizes to predict candidate Coding Modes (CMs). Subsequently, we formulate a loss function based on CM distributions and Rate Distortion(RD) costs to train the designed models. Finally, we introduce a threshold selection scheme to balance coding efficiency and coding speed. Experimental results demonstrate that the proposed method improves coding speed by an average of 36.36%, with an average increase of 0.95% in Bjøntegaard Delta Bit Rate (BDBR).

Chongqing University of Posts and Telecommunications (CN), Centre National de la Recherche Scientifique (FR), Guizhou Normal University (CN), Laboratoire des signaux et systèmes (FR), Honghe University (CN), State Key Laboratory of Cryptology (CN), De Montfort University (GB)
National Natural Science Foundation of China
Peace, Justice and strong institutions
Openalex Percentile: Top 74%
Video Coding and Compression Technologies
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