An Error-Surface-Based Fractional Motion Estimation Algorithm and Hardware Implementation for VVC

TL;DR

This paper introduces a novel error-surface-based fractional motion estimation algorithm for VVC that reduces computational complexity and power consumption, with a hardware implementation capable of real-time 4K and 8K video processing.

Contribution

It proposes the first hardware architecture for VVC FME using an interpolation-free, error-surface-based approach, enhancing efficiency and throughput.

Findings

BDBR loss of only 0.47% compared to VTM 16.0

Supports 13 CU sizes from 8x8 to 128x128

Achieves 4K@30fps at 400MHz and 8K@30fps at 631MHz

Abstract

Versatile Video Coding (VVC) introduces more coding tools to improve compression efficiency compared to its predecessor High Efficiency Video Coding (HEVC). For inter-frame coding, Fractional Motion Estimation (FME) still has a high computational effort, which limits the real-time processing capability of the video encoder. In this context, this paper proposes an error-surface-based FME algorithm and the corresponding hardware implementation. The algorithm creates an error surface constructed by the Rate-Distortion (R-D) cost of the integer motion vector (IMV) and its neighbors. This method requires no iteration and interpolation, thus reducing the area and power consumption and increasing the throughput of the hardware. The experimental results show that the corresponding BDBR loss is only 0.47% compared to VTM 16.0 in LD-P configuration. The hardware implementation was synthesized using GF 28nm process. It can support 13 different sizes of CU varying from 128x128 to 8x8. The measured throughput can reach 4K@30fps at 400MHz, with a gate count of 192k and power consumption of 12.64 mW. And the throughput can reach 8K@30fps at 631MHz when only quadtree is searched. To the best of our knowledge, this work is the first hardware architecture for VVC FME with interpolation-free strategies