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Motion vector processing in compressed video and its applications to motion compensated frame interpolation.

机译:压缩视频中的运动矢量处理及其在运动补偿帧插值中的应用。

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摘要

The objective of this thesis is to investigate algorithms that yield improved image quality for motion compensated frame interpolation or frame rate up-conversion. We address the problems of having broken edges and deformed structures in an interpolated frame by hierarchically refining motion vectors on different block sizes. The proposed novel, low complexity motion vector processing algorithm at the decoder explicitly considers the reliability of each received motion vector based on the received residual energy and motion vector correlation. By analyzing the distribution of residual energies and effectively merging blocks that have unreliable motion vectors, the structure information can be preserved.;In addition to the unreliable motion vectors due to high residual energies, there are still other unreliable motion vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion compensated frame interpolation. We further propose a correlation-based motion vector processing to classify motion vector reliability and correct identified unreliable motion vectors by analyzing motion vector correlation in the neighborhood. These unreliable motion vectors are gradually corrected based on their bidirectional difference energy levels so that we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. For these areas, we further propose an adaptive frame interpolation scheme by analyzing their surrounding motion distribution and accurately choosing forward or backward predictions.;Since the proposed motion vector processing method exploits the spatial information such as residual energy and motion vector correlation, experimental results show that our interpolated results have better visual quality than other methods. However, we still can observe the flickering effects during video display especially in motion boundaries and areas having uniformly distributed texture. Therefore, to further ensure the temporal stability in these motion sensitive areas or video frames, a novel motion vector processing approach based on motion temporal reliability analysis is proposed. For each motion vector candidate, its temporal variation of absolute bidirectional prediction difference along the motion trajectory is examined and classified into several predefined curvatures that are obtained by motion reliability statistic analysis. Any motion vectors that can match one of the predefined curvatures will be considered as possibly temporal reliable motion. This algorithm is employed to improve the motion quality for the proposed motion vector processing method. As a result, the proposed method can effectively improve the motion accuracy for the bidirectional motion vector processing and outperforms other approaches in terms of visual quality, PSNR (Peak Signal to Noise Ratio), and structure similarity.
机译:本文的目的是研究可提高运动补偿帧插值或帧速率上转换的图像质量的算法。我们通过对不同块大小的运动矢量进行分层细化来解决插值帧中边缘断裂和结构变形的问题。在解码器处提出的新颖的,低复杂度的运动矢量处理算法基于接收到的残余能量和运动矢量相关性来明确考虑每个接收到的运动矢量的可靠性。通过分析剩余能量的分布并有效地合并运动矢量不可靠的块,可以保留结构信息。除了由于残余能量高而导致的运动矢量不可靠之外,还有其他不可靠的运动矢量会导致视觉伪影,但是在运动补偿帧插值中无法通过高残留能量或双向预测差异检测到。我们进一步提出了一种基于相关性的运动矢量处理,以对运动矢量的可靠性进行分类,并通过分析邻域中的运动矢量相关性来纠正识别出的不可靠的运动矢量。这些不可靠的运动矢量会根据它们的双向差能级进行逐步校正,以便我们可以有效地发现无法使用可靠运动的区域,例如遮挡和变形结构。对于这些区域,我们通过分析其周围的运动分布并准确地选择前向或后向预测,进一步提出了一种自适应帧插值方案。由于所提出的运动矢量处理方法利用了剩余能量和运动矢量相关性等空间信息,实验结果表明我们的插值结果比其他方法具有更好的视觉质量。但是,我们仍然可以观察到视频显示期间的闪烁效果,尤其是在运动边界和纹理均匀分布的区域。因此,为了进一步保证这些运动敏感区域或视频帧的时间稳定性,提出了一种基于运动时间可靠性分析的运动矢量处理方法。对于每个候选运动矢量,检查其沿运动轨迹的绝对双向预测差异的时间变化,并将其分类为通过运动可靠性统计分析获得的几个预定义曲率。可以匹配预定义曲率之一的任何运动矢量将被视为可能是时间可靠的运动。对于提出的运动矢量处理方法,采用该算法来提高运动质量。结果,所提出的方法可以有效地提高双向运动矢量处理的运动精度,并且在视觉质量,PSNR(峰值信噪比)和结构相似性方面优于其他方法。

著录项

  • 作者

    Huang, Ai-Mei.;

  • 作者单位

    University of California, San Diego.;

  • 授予单位 University of California, San Diego.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 131 p.
  • 总页数 131
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:00

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