ExplorerBiomedical EngineeringEngineering
Research PaperResearchia:202607.01030

Accelerating Merge with Motion Vector Difference via Filter Difference Analysis for VVenC

Xinmin Feng

Abstract

Merge with Motion Vector Difference (MMVD) is a key coding tool in Versatile Video Coding for improving motion prediction accuracy. However, its exhaustive search strategy imposes a significant computational burden on the encoder. To address this issue, we propose a novel fast MMVD algorithm for the VVenC encoder based on fractional motion vector filter difference analysis. By approximating the 8-tap interpolation filter with a 2-tap filter, we derive a criterion based on spatial gradients and p...

Submitted: July 1, 2026Subjects: Engineering; Biomedical Engineering

Description / Details

Merge with Motion Vector Difference (MMVD) is a key coding tool in Versatile Video Coding for improving motion prediction accuracy. However, its exhaustive search strategy imposes a significant computational burden on the encoder. To address this issue, we propose a novel fast MMVD algorithm for the VVenC encoder based on fractional motion vector filter difference analysis. By approximating the 8-tap interpolation filter with a 2-tap filter, we derive a criterion based on spatial gradients and prediction residuals for estimating the potential gain of MMVD candidates. We further generalize this criterion to accommodate both shifted integer reference samples and 2D separable filtering. To minimize the overhead of the proposed method, we introduce implementation optimizations, including symmetric offset inference and cross-shaped downsampled dot-product computation. Compared with existing fast MMVD algorithms in VVenC, our method reduces the average MMVD search ratio from 21.07% to 11.05% and decreases the efficiency-complexity metric ηη from 11.79 to 7.10 under the fast preset.


Source: arXiv:2606.31084v1 - http://arxiv.org/abs/2606.31084v1 PDF: https://arxiv.org/pdf/2606.31084v1 Original Link: http://arxiv.org/abs/2606.31084v1

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Submission Info
Date:
Jul 1, 2026
Topic:
Biomedical Engineering
Area:
Engineering
Comments:
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