Content-Adaptive Motion Compensated Temporal Filter for Versatile Video Coding

Abstract

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The exploitation of spatial and temporal correlation within video signals is a cornerstone of video coding, which is extensively employed to achieve high coding efficiency. The presence of noise in video signal deteriorates the correlations, leading to a degradation in coding efficiency. Motion Compensated Temporal Filter (MCTF) is a pre-processing tool designed to remove noise from the source signal, thereby enhancing temporal correlations among adjacent frames. In this paper, a Content-Adaptive MCTF method (CAMCTF) is proposed to enhance the filtering adaptability of MCTF for diverse video contents. The proposed CAMCTF method consists of Quadtree Block Partitioning Scheme (QBPS), Offset Block Weighted Compensation (OBWC) and Structural Similarity (SSIM) based Filtering Weight Adjustment (SSFWA). Specifically, QBPS generates size-adaptive Motion Compensation Block (MCB) to better cater to the video content characteristics. Subsequently, OBWC is employed to address the uneven prediction quality of MCBs. Furthermore, the filtering weights of each MCB are fine-tuned by SSFWA based on the SSIM index. The simulation results show that the proposed CAMCTF method can achieve 1.23% and 0.94% BD-rate gains for RA and LD configurations, respectively, on top of Versatile Video Coding (VVC) reference software VTM-23.4.