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EXPECTATION-MAXIMIZATION TECHNIQUE AND SPATIAL - ADAPTATION APPLIED TO PEL-RECURSIVE MOTION ESTIMATION

机译:期望最大化技术和空间 - 适用于PEL递归运动估计

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Pel-recursive motion estimation is a well-established approach. However, in the presence of noise, it becomes an ill-posed problem that requires regularization. In this paper, motion vectors are estimated in an iterative fashion by means of the Expectation-Maximization (EM) algorithm and a Gaussian data model. Our proposed algorithm also utilizes the local image properties of the scene to improve the motion vector estimates following a spatially adaptive approach. Numerical experiments are presented that demonstrate the merits of our method.
机译:PEL递归运动估计是一种良好的方法。然而,在存在噪声的情况下,它成为需要正规化的不良问题。在本文中,通过期望最大化(EM)算法和高斯数据模型以迭代方式估计运动向量。我们所提出的算法还利用场景的本地图像属性来改善在空间自适应方法之后改善运动矢量估计。提出了数值实验,证明了我们方法的优点。

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