Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video Coding
Despite the fact that Versatile Video Coding (VVC) achieves a superior coding performance to High-Efficiency Video Coding (HEVC), it takes a lot of time to encode video sequences due to the high computational complexity of the tools. Among these tools, Multiple Transform Selection (MTS) require the...
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MDPI AG
2022-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/15/5523 |
| _version_ | 1797412405974663168 |
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| author | Liqiang He Shuhua Xiong Ruolan Yang Xiaohai He Honggang Chen |
| author_facet | Liqiang He Shuhua Xiong Ruolan Yang Xiaohai He Honggang Chen |
| author_sort | Liqiang He |
| collection | DOAJ |
| description | Despite the fact that Versatile Video Coding (VVC) achieves a superior coding performance to High-Efficiency Video Coding (HEVC), it takes a lot of time to encode video sequences due to the high computational complexity of the tools. Among these tools, Multiple Transform Selection (MTS) require the best of several transforms to be obtained using the Rate-Distortion Optimization (RDO) process, which increases the time spent video encoding, meaning that VVC is not suited to real-time sensor application networks. In this paper, a low-complexity multiple transform selection, combined with the multi-type tree partition algorithm, is proposed to address the above issue. First, to skip the MTS process, we introduce a method to estimate the Rate-Distortion (RD) cost of the last Coding Unit (CU) based on the relationship between the RD costs of transform candidates and the correlation between Sub-Coding Units’ (sub-CUs’) information entropy under binary splitting. When the sum of the RD costs of sub-CUs is greater than or equal to their parent CU, the RD checking of MTS will be skipped. Second, we make full use of the coding information of neighboring CUs to terminate MTS early. The experimental results show that, compared with the VVC, the proposed method achieves a 26.40% reduction in time, with a 0.13% increase in Bjøontegaard Delta Bitrate (BDBR). |
| first_indexed | 2024-03-09T05:01:35Z |
| format | Article |
| id | doaj.art-ef85505e05fd4ebfa444b304fa47e97e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T05:01:35Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
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| spelling | doaj.art-ef85505e05fd4ebfa444b304fa47e97e2023-12-03T12:59:58ZengMDPI AGSensors1424-82202022-07-012215552310.3390/s22155523Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video CodingLiqiang He0Shuhua Xiong1Ruolan Yang2Xiaohai He3Honggang Chen4College of Electronics and Information Engineering, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, ChinaCollege of Electronics and Information Engineering, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, ChinaCollege of Electronics and Information Engineering, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, ChinaCollege of Electronics and Information Engineering, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, ChinaCollege of Electronics and Information Engineering, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, ChinaDespite the fact that Versatile Video Coding (VVC) achieves a superior coding performance to High-Efficiency Video Coding (HEVC), it takes a lot of time to encode video sequences due to the high computational complexity of the tools. Among these tools, Multiple Transform Selection (MTS) require the best of several transforms to be obtained using the Rate-Distortion Optimization (RDO) process, which increases the time spent video encoding, meaning that VVC is not suited to real-time sensor application networks. In this paper, a low-complexity multiple transform selection, combined with the multi-type tree partition algorithm, is proposed to address the above issue. First, to skip the MTS process, we introduce a method to estimate the Rate-Distortion (RD) cost of the last Coding Unit (CU) based on the relationship between the RD costs of transform candidates and the correlation between Sub-Coding Units’ (sub-CUs’) information entropy under binary splitting. When the sum of the RD costs of sub-CUs is greater than or equal to their parent CU, the RD checking of MTS will be skipped. Second, we make full use of the coding information of neighboring CUs to terminate MTS early. The experimental results show that, compared with the VVC, the proposed method achieves a 26.40% reduction in time, with a 0.13% increase in Bjøontegaard Delta Bitrate (BDBR).https://www.mdpi.com/1424-8220/22/15/5523versatile video codingmultiple transform selectionfast intra-codingCU partitionreal-time sensor networks |
| spellingShingle | Liqiang He Shuhua Xiong Ruolan Yang Xiaohai He Honggang Chen Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video Coding Sensors versatile video coding multiple transform selection fast intra-coding CU partition real-time sensor networks |
| title | Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video Coding |
| title_full | Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video Coding |
| title_fullStr | Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video Coding |
| title_full_unstemmed | Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video Coding |
| title_short | Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video Coding |
| title_sort | low complexity multiple transform selection combining multi type tree partition algorithm for versatile video coding |
| topic | versatile video coding multiple transform selection fast intra-coding CU partition real-time sensor networks |
| url | https://www.mdpi.com/1424-8220/22/15/5523 |
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