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一种用于增强运动补偿的两步离散余弦基导向运动建模方法

A Two-Step Discrete Cosine Basis Oriented Motion Modeling Approach for Enhanced Motion Compensation.

作者信息

Ahmmed Ashek, Paul Manoranjan, Pickering Mark

出版信息

IEEE Trans Image Process. 2023;32:4893-4906. doi: 10.1109/TIP.2023.3288980. Epub 2023 Sep 1.

Abstract

Video coding algorithms attempt to minimize the significant commonality that exists within a video sequence. Each new video coding standard contains tools that can perform this task more efficiently compared to its predecessors. Modern video coding systems are block-based wherein commonality modeling is carried out only from the perspective of the block that need be coded next. In this work, we argue for a commonality modeling approach that can provide a seamless blending between global and local homogeneity information in terms of motion. For this purpose, at first a prediction of the current frame, the frame that need be coded, is generated by performing a two-step discrete cosine basis oriented (DCO) motion modeling. The DCO motion model is employed rather than traditional translational or affine motion model since it has the ability to efficiently model complex motion fields by providing a smooth and sparse representation. Moreover, the proposed two-step motion modeling approach can yield better motion compensation at a reduced computational complexity since an informed guess is designed for initializing the motion search procedure. After that the current frame is partitioned into rectangular regions and the conformance of these regions to the learned motion model is investigated. Depending on the non-conformance to the estimated global motion model, an additional DCO motion model is introduced to increase the local motion homogeneity. In this way, the proposed approach generates a motion compensated prediction of the current frame through the minimization of both global and local motion commonality. Experimental results show an improved rate-distortion performance of a reference high efficiency video coding (HEVC) encoder, specifically up to around 9% savings in bit rate, that employs the DCO prediction frame as a reference frame for encoding the current frame. When compared to the more recent video coding standard, the versatile video coding (VVC) encoder, a bit rate savings of 2.37% is reported.

摘要

视频编码算法试图最小化视频序列中存在的显著共性。与之前的标准相比,每个新的视频编码标准都包含能更高效执行此任务的工具。现代视频编码系统基于块,其中共性建模仅从接下来要编码的块的角度进行。在这项工作中,我们主张一种共性建模方法,该方法能在运动方面提供全局和局部同质性信息之间的无缝融合。为此,首先通过执行两步离散余弦基导向(DCO)运动建模来生成当前帧(即需要编码的帧)的预测。采用DCO运动模型而非传统的平移或仿射运动模型,因为它能够通过提供平滑且稀疏的表示来高效地对复杂运动场进行建模。此外,所提出的两步运动建模方法能够以降低的计算复杂度产生更好的运动补偿,因为设计了一个明智的猜测来初始化运动搜索过程。之后,将当前帧划分为矩形区域,并研究这些区域与所学习的运动模型的一致性。根据与估计的全局运动模型的不一致性,引入额外的DCO运动模型以增加局部运动同质性。通过这种方式,所提出的方法通过最小化全局和局部运动共性来生成当前帧的运动补偿预测。实验结果表明,采用DCO预测帧作为参考帧来编码当前帧的参考高效视频编码(HEVC)编码器的率失真性能得到了改善,具体而言,比特率节省了约9%。与更新的视频编码标准通用视频编码(VVC)编码器相比,报告的比特率节省为2.37%。

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