FSVM- and DAG-SVM-Based Fast CU-Partitioning Algorithm for VVC Intra-Coding

Wang, Fengqin; Wang, Zhiying; Zhang, Qiuwen

doi:10.3390/sym15051078

Cited by 3 publications

(2 citation statements)

References 36 publications

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“…Kim et al suggested a fast CU partition approach based on Bayesian decision making that predicts whether the CU partition should be terminated via offline and online joint learning [20]. Wang et al proposed a fast CU decision algorithm based on FSVMs and DAG-SVMs for coding complexity reduction, which divides the CU-partitioning process into two stages and symmetrically extracts some of the same CU features [21]. The fast CU size decision method was guided by the SVM classification of the complexity degree [22].…”

Section: Machine Learning Methodsmentioning

confidence: 99%

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Fast Versatile Video Coding (VVC) Intra Coding for Power-Constrained Applications

Chen,

Cheng,

Zhu

et al. 2024

Electronics

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Versatile Video Coding (VVC) achieves impressive coding gain improvement (about 40%+) over the preceding High-Efficiency Video Coding (HEVC) technology at the cost of extremely high computational complexity. Such an extremely high complexity increase is a great challenge for power-constrained applications, such as Internet of video things. In the case of intra coding, VVC utilizes the brute-force recursive search for both the partition structure of the coding unit (CU), which is based on the quadtree with nested multi-type tree (QTMT), and 67 intra prediction modes, compared to 35 in HEVC. As a result, we offer optimization strategies for CU partition decision and intra coding modes to lessen the computational overhead. Regarding the high complexity of the CU partition process, first, CUs are categorized as simple, fuzzy, and complex based on their texture characteristics. Then, we train two random forest classifiers to speed up the RDO-based brute-force recursive search process. One of the classifiers directly predicts the optimal partition modes for simple and complex CUs, while another classifier determines the early termination of the partition process for fuzzy CUs. Meanwhile, to reduce the complexity of intra mode prediction, a fast hierarchical intra mode search method is designed based on the texture features of CUs, including texture complexity, texture direction, and texture context information. Extensive experimental findings demonstrate that the proposed approach reduces complexity by up to 77% compared to the latest VVC reference software (VTM-23.1). Additionally, an average coding time saving of 70% is achieved with only a 1.65% increase in BDBR. Furthermore, when compared to state-of-the-art methods, the proposed method also achieves the largest time saving with comparable BDBR loss. These findings indicate that our method is superior to other up-to-date methods in terms of lowering VVC intra coding complexity, which provides an elective solution for power-constrained applications.

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Section: Machine Learning Methodsmentioning

confidence: 99%

“…We compare our algorithm with three of the most advanced methods, namely, those of Ni 2022 [14], Wang 2023 [21], and Li 2024 [22]. As shown in Table 8, the T/B = TS/BDBR denotes the measurement for the trade-off between the time savings and BDBR performance.…”

Section: Comparison With Othersmentioning

confidence: 99%

Fast Versatile Video Coding (VVC) Intra Coding for Power-Constrained Applications

Chen,

Cheng,

Zhu

et al. 2024

Electronics

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Fast CU size decision and intra-prediction mode decision method for H.266/VVC

Li,

Wang,

Zhang

2024

J Image Video Proc.

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H.266/Versatile Video Coding (VVC) is the most recent video coding standard developed by the Joint Video Experts Team (JVET). The quad-tree with nested multi-type tree (QTMT) architecture that improves the compression performance of H.266/VVC is introduced. Moreover, H.266/VVC contains a greater number of intra-prediction modes than H.265/High Efficiency Video Coding (HEVC), totalling 67. However, these lead to extremely the coding computational complexity. To cope with the above issues, a fast intra-coding unit (CU) size decision method and a fast intra-prediction mode decision method are proposed in this paper. Specifically, the trained Support Vector Machine (SVM) classifier models are utilized for determining CU partition mode in a fast CU size decision scheme. Furthermore, the quantity of intra-prediction modes added to the RDO mode set decreases in a fast intra-prediction mode decision scheme based on the improved search step. Simulation results illustrate that the proposed overall algorithm can decrease 55.24% encoding runtime with negligible BDBR.

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Основанный На Генетическом Подходе Алгоритм Внутрикодирования Для H.266/VVC

Ibraheem,

Abdalameer,

Hatif Naji

2024

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This paper presents a genetic approach for optimizing intra coding in H.266/VVC. The proposed algorithm efficiently selects coding tools and Multi-Type Tree (MTT) partitions to achieve a balance between encoding time and video quality. The fitness evaluation function, which combines perceptual metrics and coding efficiency metrics, is used to assess the quality of each candidate solution. The results demonstrate a significant reduction in encoding time without compromising video quality. The proposed algorithm selects coding tools from a set of available tools in H.266/VVC. These tools include intra prediction modes, transform units, quantization parameters, and entropy coding modes. The MTT partitioning scheme includes four types of partitions: quadtree, binary tree, ternary tree, and quad-binary tree. Perceptual metrics are used to evaluate the visual quality of the encoded video. Coding efficiency metrics are used to evaluate the coding efficiency of the encoded video. The fitness evaluation function combines perceptual metrics and coding efficiency metrics to assess the quality of each candidate solution.

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FSVM- and DAG-SVM-Based Fast CU-Partitioning Algorithm for VVC Intra-Coding

Cited by 3 publications

References 36 publications

Fast Versatile Video Coding (VVC) Intra Coding for Power-Constrained Applications

Fast Versatile Video Coding (VVC) Intra Coding for Power-Constrained Applications

Fast CU size decision and intra-prediction mode decision method for H.266/VVC

Основанный На Генетическом Подходе Алгоритм Внутрикодирования Для H.266/VVC

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