Bellcore, Morristown, NJ.
IEEE Trans Image Process. 1997;6(12):1606-20. doi: 10.1109/83.650115.
We present a systematic approach to forward-motion-compensated predictive video coding. The first step is the definition of a flexible model that compactly represents motion fields. The inhomogeneity and spatial coherence properties of motion fields are captured using linear multiscale models. One possible design is based on linear finite elements and yields a multiscale extension of the triangle motion compensation (TMC) method. The second step is the choice of a computational technique that identifies the coefficients of the linear model. We study a modified optical flow technique and minimize a cost function closely related to Horn and Schunck's (1981) criterion. The cost function balances accuracy and complexity of the motion compensated predictor and is viewed as a measure of goodness of the motion field. It determines not only the coefficients of the model, but also the quantization method. We formulate the estimation and quantization problems jointly as a discrete optimization problem and solve it using a fast multiscale relaxation algorithm. A hierarchical extension of the algorithm allows proper handling of large displacements. Simulations on a variety of video sequences have produced improvements over TMC and over the half-pel-accuracy, full-search block matching algorithm, in excess of 0.5 dB in average. The results are visually superior as well. In particular, the reconstructed video is entirely free of blocking artifacts.
我们提出了一种用于前向运动补偿预测视频编码的系统方法。第一步是定义一个灵活的模型，该模型可以紧凑地表示运动场。运动场的非均匀性和空间相干性特性使用线性多尺度模型来捕获。一种可能的设计基于线性有限元，并为三角形运动补偿 (TMC) 方法提供了多尺度扩展。第二步是选择一种用于识别线性模型系数的计算技术。我们研究了一种改进的光流技术，并最小化了与 Horn 和 Schunck（1981）准则密切相关的成本函数。该成本函数平衡了运动补偿预测器的准确性和复杂性，被视为运动场质量的度量。它不仅确定了模型的系数，还确定了量化方法。我们将估计和量化问题联合表述为一个离散优化问题，并使用快速多尺度松弛算法来解决。算法的分层扩展允许正确处理大位移。在各种视频序列上的仿真表明，与 TMC 相比，与半像素精度、全搜索块匹配算法相比，平均提高了 0.5dB 以上。结果在视觉上也更好。特别是，重建的视频完全没有块效应。
