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Game-theory-based complexity allocation for 360-degree video coding
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AI
DOI：10.1016/j.sigpro.2024.109807.png)
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360-degree video applications with immersive experiences have been well spread in our daily life. However, 360-degree video with high resolution (e.g., 8192x4096,6144x 3072, and 3840 x 1920) leads to high coding computational complexity. To further optimize the complexity allocation and obtain the optimal coding performance, this paper proposes a game-theory-based complexity allocation algorithm for 360-degree video coding. The proposed method first constructs the latitude-level complexity allocation model by introducing game theory. Second, the optimal Lagrange coefficient lambda(& lowast;) value is obtained by the Newton method, and then, the complexity of the latitude can be further obtained. Finally, the overall complexity allocation algorithm is also designed. Experimental results indicate our method obtains Time Saving (TS) with 18.44%similar to 67.08% and BDBR performance with 0.10%similar to 3.11%. The proposed method also achieves the optimal Coding Gain (CG) values for the most global target complexity.
Keyword:
HEVC
Complexity optimization
Game theory
360-degree video
期刊
IF:
3.6
论文数:
9.9K
被引数:
1.7W
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