Improved intra-subpartition coding mode for versatile video coding

Akbulut, Orhan; Konyar, Mehmet Zeki

doi:10.1007/s11760-021-02088-w

Cited by 7 publications

(2 citation statements)

References 14 publications

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“…Similarly, another scholarly work [8] presents a hierarchical convolutional neural network (CNN) architecture, serving as an alternative to the computationally intensive brute force method employed in the search for RDCost. Within the existing literature, a scholarly work [9] introduces an enhanced internal subdivision algorithm specifically tailored for partitioning CUs into sub-CUs based on diverse directional considerations. This algorithm further facilitates the identification of the optimal division pattern.…”

Section: Status Of H266/vvc Research For 2d Videomentioning

confidence: 99%

Fast Algorithm for CU Size Decision Based on Ensemble Clustering for Intra Coding of VVC 3D Video Depth Map

Song

Zhang

2023

Electronics

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As many new coding techniques and coding structures have been introduced to further improve the coding efficiency of depth maps in 3D video extensions, the coding complexity has been greatly increased. Fast algorithms are now needed to improve coding unit (CU) depth decisions as well as the coding pattern decision based on the coding. This paper presents an innovative machine learning-based approach aimed at mitigating the complexity associated with in-frame coding algorithms. We build different clustering models for different CU sizes to cluster CUs of the same size to decide their CU sizes. This is achieved by augmenting ensemble clustering through the expedited propagation of clustering similarities, considering CU with the same or similar texture complexity the same as for CU depth selection, which is informed by a comprehensive analysis of the original texture and its neighboring elements. The experimental findings demonstrate that the proposed scheme yields a substantial average reduction of 44.24% in the coding time. Remarkably, the corresponding Bjøntegaard delta bit rate (BDBR) increment observed for the synthetic view is a mere 0.26%.

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Section: Status Of H266/vvc Research For 2d Videomentioning

confidence: 99%

Fast Algorithm for CU Size Decision Based on Ensemble Clustering for Intra Coding of VVC 3D Video Depth Map

Song

Zhang

2023

Electronics

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“…In accordance with reference [9], a rapid algorithm for intra-CU partitioning on the basis of variance and the Sobel operator is presented, judging whether the CU needs to be split according to the gradient feature to avoid unnecessary partition. Reference [10] proposed an improved intra-sub-partition algorithm, which split the CU into sub-CUs according to different directions and then selected the optimal partitioning mode. Liu et al [11] proposed a fast intra-CU-partitioning algorithm on the basis of cross-block difference, which obtained the difference mainly through the gradient of CU and sub-CU, thus skipping unnecessary horizontal and vertical partitioning.…”

Section: Based On Traditional Algorithmsmentioning

confidence: 99%

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

Wang

Zhang

2023

Symmetry

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H.266/VVC introduces the QTMT partitioning structure, building upon the foundation laid by H.265/HEVC, which makes the partitioning more diverse and flexible but also brings huge coding complexity. To better address the problem, we propose a fast CU decision algorithm based on FSVMs and DAG-SVMs to reduce encoding time. The algorithm divides the CU-partitioning process into two stages and symmetrically extracts some of the same CU features. Firstly, CU is input into the trained FSVM model, extracting the standard deviation, directional complexity, and content difference complexity of the CUs, and it uses these features to make a judgment on whether to terminate the partitioning early. Then, the determination of the partition type of CU is regarded as a multi-classification problem, and a DAG-SVM classifier is used to classify it. The extracted features serve as input to the classifier, which predicts the partition type of the CU and thereby prevents unnecessary partitioning. The results of the experiment indicate that compared with the reference software VTM10.0 anchoring algorithm, the algorithm can save 49.38%~58.04% of coding time, and BDBR only increases by 0.76%~1.37%. The video quality and encoding performance are guaranteed while the encoding complexity is effectively reduced.

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Simultaneous context and motion learning in video prediction

Thu

2023

SIViP

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Improved intra-subpartition coding mode for versatile video coding

Cited by 7 publications

References 14 publications

Fast Algorithm for CU Size Decision Based on Ensemble Clustering for Intra Coding of VVC 3D Video Depth Map

Fast Algorithm for CU Size Decision Based on Ensemble Clustering for Intra Coding of VVC 3D Video Depth Map

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

Simultaneous context and motion learning in video prediction

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