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In this paper, a joint decision tree and visual feature optimization rate control scheme for ultrahigh-definition (UHD) versatile video coding (VVC) is proposed. First, we design a new rate-distortion (R-D) model for UHD videos, and we establish a decision-tree-based multiclass classification scheme to improve the prediction accuracy of the R-D model by fully considering visual features. Second, based on the proposed R-D model, the globally optimal solution is obtained through convex optimization. Finally, we embed our algorithm into the latest VVC reference software, VTM 10.2. According to our experimental results, compared with the latest algorithm in VTM 10.2 and other state-of-the-art algorithms, our method can achieve significant bit rate reductions while maintaining a given peak signal-to-noise ratio (PSNR) or structural similarity index measure (SSIM).
Bibliographical noteFunding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 62176027; in part by the General Program of the National Natural Science Foundation of Chongqing under Grant cstc2020jcyj-msxmX0790; in part by the Human Resources and Social Security Bureau Project of Chongqing under Grant cx2020073; in part by the Hong Kong GRF-RGC General Research Fund under Grant 11209819 and Grant CityU 9042816; in part by the Hong Kong GRF-RGC General Research Fund under Grant 11203820 and Grant CityU 9042598; in part by the Zhuhai Postdoctoral Research Fund under Grant 110321001; in part by the International Postdoctoral Exchange Fellowship Program; and in part by the Hong Kong Innovation and Technology Commission, InnoHK Project Centre for Intelligent Multidimensional Data Analysis (CIMDA).
© 1992-2012 IEEE.
- Decision tree
- rate control
- visual feature
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- 1 Active
KWONG, S. T. W., KUO, C. J., WANG, S. & ZHANG, X.
1/01/21 → 30/06/24
Project: Grant Research