Data Compression using Non - Uniform Sampling

Vibhutesh Kumar Singh, N. Rajpal
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引用次数: 8

Abstract

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
使用非均匀采样的数据压缩
本文研究了数据的非均匀采样和重构问题。本文描述了一种快速且鲁棒的从非均匀分布的样本点逼近轮廓的方法。数据由分布在空间中的不规则样本表示。沿等高线选取样本,样本间距由原始等高线与均匀采样点重构等高线之间的误差决定。采用拉格朗日插值法从非均匀的样本集中重建轮廓。该算法沿轮廓迭代地寻找最小样本数。对原始轮廓和重构轮廓的误差分析表明,迭代算法对不规则样本的选择是令人满意的
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