Joint Decision Tree and Visual Feature Rate Control Optimization for VVC UHD Coding
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...
| Publié dans: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 32(2023) vom: 06., Seite 219-234 |
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| Auteur principal: | |
| Autres auteurs: | , , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2023
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| Accès à la collection: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Sujets: | Journal Article |
| Résumé: | 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) |
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| Description: | Date Revised 04.04.2025 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1941-0042 |
| DOI: | 10.1109/TIP.2022.3224876 |