{"title":"基于自适应树搜索和剪枝优化的AVS3快速CU分区算法","authors":"Jihang Yin;Honggang Qi;Liang Zhong;Zhiyuan Zhao;Qiang Wang;Jingran Wu;Xianguo Zhang","doi":"10.1109/TBC.2024.3465838","DOIUrl":null,"url":null,"abstract":"In the third generation of the Audio Video Coding Standard (AVS3), the size of Coding Tree Units (CTUs) has been expanded to four times larger than the previous generation, and more Coding Unit (CU) partition modes have been introduced, enhancing adaptability and efficiency in video encoding. CU partition in AVS3 not only brings improvements in encoding performance but also significantly increases the computational complexity, posing substantial challenges to real-time encoding. We propose a fast algorithm for CU partition, which features adaptive tree search and pruning optimization. Firstly, it adjusts the tree search order based on neighbor CU and lookahead information. Specifically, the analysis order of sub-blocks and parent blocks is adaptively adjusted: the potential optimal partition is prioritized, the non-optimal partitions are deferred, and an optimized order of first-full-then-sub or first-sub-then-full is selected. Secondly, the pruning optimization algorithm utilizes analyzed information to skip non-optimal partitions to reduce computational complexity. Due to the adjusted tree search order and the prioritization of potential optimal partitions, more analyzed information becomes available when evaluating non-optimal partitions, thereby improving the recall and precision rates of non-optimal partitions detection, saving more time, and introducing negligible loss in coding performance. The proposed algorithm has been implemented in the open-source encoder uavs3e. Experimental results indicate that under the three encoding configurations of AI, LD B, and RA, the algorithm achieves significant time saving of 51.41%, 40.57%, and 40.57%, with BDBR increases of 0.64%, 1.61%, and 1.04%, respectively. These results outperform the state-of-the-art fast CU partition algorithms.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 1","pages":"125-141"},"PeriodicalIF":4.8000,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Fast CU Partition Algorithm for AVS3 Based on Adaptive Tree Search and Pruning Optimization\",\"authors\":\"Jihang Yin;Honggang Qi;Liang Zhong;Zhiyuan Zhao;Qiang Wang;Jingran Wu;Xianguo Zhang\",\"doi\":\"10.1109/TBC.2024.3465838\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the third generation of the Audio Video Coding Standard (AVS3), the size of Coding Tree Units (CTUs) has been expanded to four times larger than the previous generation, and more Coding Unit (CU) partition modes have been introduced, enhancing adaptability and efficiency in video encoding. CU partition in AVS3 not only brings improvements in encoding performance but also significantly increases the computational complexity, posing substantial challenges to real-time encoding. We propose a fast algorithm for CU partition, which features adaptive tree search and pruning optimization. Firstly, it adjusts the tree search order based on neighbor CU and lookahead information. Specifically, the analysis order of sub-blocks and parent blocks is adaptively adjusted: the potential optimal partition is prioritized, the non-optimal partitions are deferred, and an optimized order of first-full-then-sub or first-sub-then-full is selected. Secondly, the pruning optimization algorithm utilizes analyzed information to skip non-optimal partitions to reduce computational complexity. Due to the adjusted tree search order and the prioritization of potential optimal partitions, more analyzed information becomes available when evaluating non-optimal partitions, thereby improving the recall and precision rates of non-optimal partitions detection, saving more time, and introducing negligible loss in coding performance. The proposed algorithm has been implemented in the open-source encoder uavs3e. Experimental results indicate that under the three encoding configurations of AI, LD B, and RA, the algorithm achieves significant time saving of 51.41%, 40.57%, and 40.57%, with BDBR increases of 0.64%, 1.61%, and 1.04%, respectively. 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引用次数: 0
摘要
第三代音视频编码标准AVS3 (Audio Video Coding Standard)将编码树单元(Coding Tree Units,简称ctu)的大小扩展到上一代的4倍,并引入了更多的编码单元(Coding Unit,简称CU)划分模式,提高了视频编码的适应性和效率。AVS3中的CU分区不仅提高了编码性能,但也显著增加了计算复杂度,给实时编码带来了很大的挑战。提出了一种基于自适应树搜索和剪枝优化的快速分区算法。首先,根据邻居CU和前瞻信息调整树的搜索顺序;具体来说,对子块和父块的分析顺序进行自适应调整:对潜在的最优分区进行优先级排序,对非最优分区进行延迟,并选择先满后子或先满后子的优化顺序。其次,剪枝优化算法利用分析信息跳过非最优分区,降低计算复杂度;由于调整了树的搜索顺序和潜在最优分区的优先级,在评估非最优分区时可以获得更多的分析信息,从而提高了非最优分区检测的召回率和准确率,节省了更多的时间,并且对编码性能的损失可以忽略不计。该算法已在开源编码器uavs3e中实现。实验结果表明,在AI、LD B和RA三种编码配置下,算法的时间节约率分别为51.41%、40.57%和40.57%,BDBR分别提高了0.64%、1.61%和1.04%。这些结果优于最先进的快速CU分区算法。
A Fast CU Partition Algorithm for AVS3 Based on Adaptive Tree Search and Pruning Optimization
In the third generation of the Audio Video Coding Standard (AVS3), the size of Coding Tree Units (CTUs) has been expanded to four times larger than the previous generation, and more Coding Unit (CU) partition modes have been introduced, enhancing adaptability and efficiency in video encoding. CU partition in AVS3 not only brings improvements in encoding performance but also significantly increases the computational complexity, posing substantial challenges to real-time encoding. We propose a fast algorithm for CU partition, which features adaptive tree search and pruning optimization. Firstly, it adjusts the tree search order based on neighbor CU and lookahead information. Specifically, the analysis order of sub-blocks and parent blocks is adaptively adjusted: the potential optimal partition is prioritized, the non-optimal partitions are deferred, and an optimized order of first-full-then-sub or first-sub-then-full is selected. Secondly, the pruning optimization algorithm utilizes analyzed information to skip non-optimal partitions to reduce computational complexity. Due to the adjusted tree search order and the prioritization of potential optimal partitions, more analyzed information becomes available when evaluating non-optimal partitions, thereby improving the recall and precision rates of non-optimal partitions detection, saving more time, and introducing negligible loss in coding performance. The proposed algorithm has been implemented in the open-source encoder uavs3e. Experimental results indicate that under the three encoding configurations of AI, LD B, and RA, the algorithm achieves significant time saving of 51.41%, 40.57%, and 40.57%, with BDBR increases of 0.64%, 1.61%, and 1.04%, respectively. These results outperform the state-of-the-art fast CU partition algorithms.
期刊介绍:
The Society’s Field of Interest is “Devices, equipment, techniques and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.” In addition to this formal FOI statement, which is used to provide guidance to the Publications Committee in the selection of content, the AdCom has further resolved that “broadcast systems includes all aspects of transmission, propagation, and reception.”