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Subblock Matching-Based Conditional Motion Estimation with Automatic Threshold Selection for Video Compression

机译:用于视频压缩的基于子块匹配的条件运动估计和自动阈值选择

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摘要

In this paper, we propose a block-based conditional motion estimation scheme for video compression. The blocks in a frame are classified as active or inactive based on a threshold and only the active blocks are subjected to motion estimation. The threshold value is decided automatically through an iterative algorithm. The motion vectors of the boundary active blocks are estimated using a subblock matching-based scheme. Unlike existing variable size block-matching algorithms, the proposed motion estimation scheme preserves the basic framework of the conventional block-matching algorithm, such as equal number of motion vectors and one-pass processing. A small amount of side information needs to be transmitted for the boundary blocks to indicate the displacements of the their subblocks. The proposed scheme provides a better tradeoff between the complexity and the rate-distortion performance of the encoder than other existing schemes and better subjective quality of the motion-compensated frames than the conventional motion compensation.
机译:在本文中,我们提出了一种基于块的视频压缩条件运动估计方案。帧中的块基于阈值分类为活动或不活动,并且仅对活动块进行运动估计。阈值通过迭代算法自动确定。使用基于子块匹配的方案来估计边界活动块的运动矢量。与现有的可变大小块匹配算法不同,所提出的运动估计方案保留了常规块匹配算法的基本框架,例如相等数量的运动矢量和一遍处理。需要为边界块发送少量辅助信息,以指示其子块的位移。与常规的运动补偿相比,所提出的方案在编码器的复杂度和速率失真性能之间提供了比其他现有方案更好的折衷,并且在运动补偿的帧上具有更好的主观质量。

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