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Data Compression using Non - Uniform Sampling

机译:使用非均匀采样数据压缩

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This paper is concerned with the problem of non-uniform sampling and reconstruction of data. A fast and robust method for approximation of contour from a set of non-uniformly distributed sample points is described here. Data is represented by irregular samples distributed in space. The samples are chosen along the contour with spacing determined by the error between the original contour and the contour reconstructed by uniform set of sample points. Lagrange's interpolation is used to reconstruct the contour back from non-uniform set of samples. The algorithm iteratively finds the minimum number of samples along the contour. The error analysis between original and reconstructed contour reveals that iterative algorithm of selecting irregular samples is satisfactory.
机译:本文涉及非统一采样和数据重建问题。这里描述了一种用于从一组非均匀分布的样本点近似的快速且鲁棒的方法。数据由在空间中分布的不规则样本表示。沿着轮廓选择样品,其由由原始轮廓之间的误差和由均匀的样本点组成的轮廓确定的间隔确定。拉格朗日的插值用于重建从非均匀样本集的轮廓。该算法迭代地找到轮廓的最小样本数。原始和重建轮廓之间的误差分析揭示了选择不规则样本的迭代算法是令人满意的。

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