A High-Throughput and Memory-Efficient Deblocking Filter Hardware Architecture for VVC
Video coding has become more and more important since high-resolution and high-quality videos have been used in a variety of application areas. Deblocking filter (DBF) is a video coding technology which can improve both video quality and coding efficiency. However, its hardware architecture design suffers from huge computations and high memory requirements. Moreover, the latest Versatile Video Coding (VVC) standard extends DBF with several complex enhancements, which makes the design more difficult. In this paper, a high-throughput and memory-efficient DBF hardware architecture for VVC systems is presented. By analyz-ing the DBF algorithm, we firstly propose a unified filter core to perform edge filtering process with low complexity, and two resource sharing techniques are utilized to reduce hardware costs. Furthermore, we propose a whole DBF architecture to process all the edges in a coding tree unit (CTU). To improve its throughput, we propose novel pre-calculation processing flow and double processing flow to fully utilize pipelining and parallel processing techniques. At the same time, to reduce its memory requirements, we propose four novel data reuse approaches to fully utilize intermediate data reusabilities. Synthesis results show that our proposed hardware architecture can support real-time VVC DBF processing of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$7680\times 4320$ </tex-math></inline-formula> at 158 frames/s at 500 MHz working frequency. The hardware costs are only 163.2k gate count and three two-port on-chip SRAMs with data width of 128 bits and depth of 32. Compared with other state-of-the-art works for previous standards, our proposed VVC DBF hardware architecture achieves good results in performance, area efficiency and memory efficiency.
Authors
- Leilei Huang (ORCID: https://orcid.org/0000-0002-8900-4109)
- Minge Jing (ORCID: https://orcid.org/0009-0005-0446-5600)
- Yibo Fan (ORCID: https://orcid.org/0000-0003-2523-8261)
- Bingjing Hou (ORCID: https://orcid.org/0009-0009-2560-9721)
Institutions
- Fudan University (CN)
- East China Normal University (CN)
Publication Details
- Journal
- IEEE Transactions on Circuits and Systems for Video Technology
- Published
- 2024-08-22
- DOI
- https://doi.org/10.1109/tcsvt.2024.3447698
- Citations
- 2
- Primary Topic
- Advanced Data Storage Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.70
Funders
- National Natural Science Foundation of China