An Interpolation-Free Fractional Motion Estimation Algorithm and Hardware Implementation for VVC

Versatile video coding (VVC) introduces multi-type tree (MTT) and larger coding tree unit (CTU) to improve compression efficiency compared to its predecessor High Efficiency Video Coding (HEVC). This leads to higher throughput for fractional motion estimation (FME) to meet the needs of real-time processing. In this context, this article proposes an interpolation-free algorithm based on an error surface to improve the throughput of FME hardware. The error surface is constructed by the rate-distortion costs (RDCs) of the integer motion vector (IMV) and its neighbors. To improve the prediction accuracy, a hardware-friendly RDC estimation strategy is proposed to construct the error surface. The experimental results show that the corresponding Bjontegaard Delta Bit Rate (BDBR) in Random Access (RA), Low Delay P (LDP) and Low Delay B (LDB) configuration increases by only 0.358%, 0.479%, and 0.511% compared with the VVC test model (VTM) 16.0. Compared with the default FME algorithms of VVC, the time cost of FME is reduced by 53.47%, 56.28%, and 54.23%, respectively, in RA, LDP, and LDB configurations. The algorithm is free of iteration and interpolation, which can contribute to low-cost and high-throughput hardware. The proposed architecture can support FME of all coding units (CUs) in a CTU with one layer of MTT under the quaternary tree (QT), and the CU size can vary from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8\times 8$ </tex-math></inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$128\times 128$ </tex-math></inline-formula>. Synthesized using GF 28-nm process, the architecture can achieve <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>@60 fps throughput at 800 MHz, with a gate count of 244 K and power consumption of 76.5 mW. This proposed architecture can meet the real-time coding requirements of VVC.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Published
2024-09-17
DOI
https://doi.org/10.1109/tvlsi.2024.3455374
Citations
4
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
1.31

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Interpolation-Free Fractional Motion Estimation Algorithm and Hardware Implementation for VVC

Leilei Huang, Zhao Zan, Yibo Fan, Xiaoyang Zeng et al.
4 citations
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Iterative Learning Control Systems
1.31
article

An Interpolation-Free Fractional Motion Estimation Algorithm and Hardware Implementation for VVC

Leilei Huang, Zhao Zan, Yibo Fan, Xiaoyang Zeng, Shushi Chen
article en
4 citations

Abstract

Versatile video coding (VVC) introduces multi-type tree (MTT) and larger coding tree unit (CTU) to improve compression efficiency compared to its predecessor High Efficiency Video Coding (HEVC). This leads to higher throughput for fractional motion estimation (FME) to meet the needs of real-time processing. In this context, this article proposes an interpolation-free algorithm based on an error surface to improve the throughput of FME hardware. The error surface is constructed by the rate-distortion costs (RDCs) of the integer motion vector (IMV) and its neighbors. To improve the prediction accuracy, a hardware-friendly RDC estimation strategy is proposed to construct the error surface. The experimental results show that the corresponding Bjontegaard Delta Bit Rate (BDBR) in Random Access (RA), Low Delay P (LDP) and Low Delay B (LDB) configuration increases by only 0.358%, 0.479%, and 0.511% compared with the VVC test model (VTM) 16.0. Compared with the default FME algorithms of VVC, the time cost of FME is reduced by 53.47%, 56.28%, and 54.23%, respectively, in RA, LDP, and LDB configurations. The algorithm is free of iteration and interpolation, which can contribute to low-cost and high-throughput hardware. The proposed architecture can support FME of all coding units (CUs) in a CTU with one layer of MTT under the quaternary tree (QT), and the CU size can vary from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8\times 8$ </tex-math></inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$128\times 128$ </tex-math></inline-formula>. Synthesized using GF 28-nm process, the architecture can achieve <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>@60 fps throughput at 800 MHz, with a gate count of 244 K and power consumption of 76.5 mW. This proposed architecture can meet the real-time coding requirements of VVC.

IEEE Transactions on Very Large Scale Integration (VLSI) SystemsVol. 33(2)
Fudan University (CN), East China Normal University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 19%
Iterative Learning Control Systems
1.31
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.