W. Li, Xiantao Jiang, Jiayuan Jin, Tian Song, F. Yu
{"title":"一种基于纹理特征的VVC快速CU划分算法","authors":"W. Li, Xiantao Jiang, Jiayuan Jin, Tian Song, F. Yu","doi":"10.1145/3582177.3582193","DOIUrl":null,"url":null,"abstract":"Abstract: Different from the traditional quaternary tree (QT) structure utilized in the previous generation video coding standard H.265/HEVC, a new partition structure named quadtree with nested multi-type tree (QTMT) is applied in the latest codec H.266/VVC. The introduction of QTMT brings in superior encoding performance at the cost of great time-consuming. Therefore, this paper proposes a fast coding unit (CU) partitioning algorithm based on CU texture complexity and texture direction. First, we terminate further splitting of a CU when its texture is judged as simple. Then, we use the gray level co-occurrence matrix (GLCM) to extract the texture direction of the block to decide whether to partition this CU by QT, thus terminating further MT partitions. Finally, a final partition type is selected from the four MT partitions in combination with the multi-level texture complexity and texture direction of the block. The simulation results show that the overall algorithm can significantly reduce the encoding time, while the loss of coding efficiency is reasonably low. In comparison with the reference model, the encoding time is reduced by up to 44.71%, while the BDBR is increased by only 0.84% on average.","PeriodicalId":170327,"journal":{"name":"Proceedings of the 2023 5th International Conference on Image Processing and Machine Vision","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Fast CU Partitioning Algorithm Based on Texture Characteristics for VVC\",\"authors\":\"W. Li, Xiantao Jiang, Jiayuan Jin, Tian Song, F. Yu\",\"doi\":\"10.1145/3582177.3582193\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract: Different from the traditional quaternary tree (QT) structure utilized in the previous generation video coding standard H.265/HEVC, a new partition structure named quadtree with nested multi-type tree (QTMT) is applied in the latest codec H.266/VVC. The introduction of QTMT brings in superior encoding performance at the cost of great time-consuming. Therefore, this paper proposes a fast coding unit (CU) partitioning algorithm based on CU texture complexity and texture direction. First, we terminate further splitting of a CU when its texture is judged as simple. Then, we use the gray level co-occurrence matrix (GLCM) to extract the texture direction of the block to decide whether to partition this CU by QT, thus terminating further MT partitions. Finally, a final partition type is selected from the four MT partitions in combination with the multi-level texture complexity and texture direction of the block. The simulation results show that the overall algorithm can significantly reduce the encoding time, while the loss of coding efficiency is reasonably low. In comparison with the reference model, the encoding time is reduced by up to 44.71%, while the BDBR is increased by only 0.84% on average.\",\"PeriodicalId\":170327,\"journal\":{\"name\":\"Proceedings of the 2023 5th International Conference on Image Processing and Machine Vision\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2023 5th International Conference on Image Processing and Machine Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3582177.3582193\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 5th International Conference on Image Processing and Machine Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3582177.3582193","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Fast CU Partitioning Algorithm Based on Texture Characteristics for VVC
Abstract: Different from the traditional quaternary tree (QT) structure utilized in the previous generation video coding standard H.265/HEVC, a new partition structure named quadtree with nested multi-type tree (QTMT) is applied in the latest codec H.266/VVC. The introduction of QTMT brings in superior encoding performance at the cost of great time-consuming. Therefore, this paper proposes a fast coding unit (CU) partitioning algorithm based on CU texture complexity and texture direction. First, we terminate further splitting of a CU when its texture is judged as simple. Then, we use the gray level co-occurrence matrix (GLCM) to extract the texture direction of the block to decide whether to partition this CU by QT, thus terminating further MT partitions. Finally, a final partition type is selected from the four MT partitions in combination with the multi-level texture complexity and texture direction of the block. The simulation results show that the overall algorithm can significantly reduce the encoding time, while the loss of coding efficiency is reasonably low. In comparison with the reference model, the encoding time is reduced by up to 44.71%, while the BDBR is increased by only 0.84% on average.