Highly scalable video compression using a lifting-based 3D wavelet transform with deformable mesh motion compensation

Andrew Secker, D. Taubman
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引用次数: 80

Abstract

This paper continues the development of a new framework for the construction of motion-compensated wavelet transforms for highly scalable video compression. The current authors recently proposed a motion adaptive wavelet transform based on motion-compensated lifting steps. This approach overcomes several limitations of existing methods. In particular, frame warping and block displacement methods cannot efficiently exploit complex motion without sacrificing invertibility. By contrast, the motion-compensated lifting transform remains invertible regardless of the motion model. The previous work was primarily in the context of a block motion model. However, block motion models inevitably yield discontinuous motion fields, which poorly represent complex motion in real video sequences. In this paper we consider the benefits of a continuous motion field, by incorporating a deformable mesh motion model into the existing framework. Experimental results show that this leads to improved compression performance. In addition, we show that the invertibility of continuous motion fields allows greater potential for compactly representing the motion information.
高度可扩展的视频压缩使用基于提升的三维小波变换与可变形的网格运动补偿
本文继续开发一种新的框架,用于构建用于高可伸缩视频压缩的运动补偿小波变换。作者最近提出了一种基于运动补偿提升步骤的运动自适应小波变换。这种方法克服了现有方法的一些局限性。特别是帧翘曲和块位移方法不能在不牺牲可逆性的情况下有效地利用复杂运动。相反,无论运动模型如何,运动补偿提升变换都是可逆的。之前的工作主要是在块运动模型的背景下进行的。然而,块运动模型不可避免地会产生不连续的运动场,这在真实的视频序列中很难表现复杂的运动。在本文中,我们考虑了连续运动场的好处,通过将可变形网格运动模型纳入现有框架。实验结果表明,该方法提高了压缩性能。此外,我们证明了连续运动场的可逆性允许更大的潜力来紧凑地表示运动信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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