Legendre polynomials in signal reconstruction and compression

Guoqi Li, C. Wen
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引用次数: 8

Abstract

In this paper, we present a method for signal reconstruction using orthogonal transform based on discrete Legendre polynomials. Using such a transform provides computational advantages over polynomial basis. We extend the discrete Legendre polynomials to two-dimensional discrete Legendre polynomials for reconstructing and compressing an image. In the applications, we notice that when the order of a polynomial becomes large, the proposed method tends to exhibit numerical instabilities. We bring forward a possible way to avoid such instabilities. Simulation results illustrate that the error resulted from compression is usually low with a satisfactory compression ratio by using the proposed method. An application in system identification is also presented.
信号重构与压缩中的勒让德多项式
本文提出了一种基于离散勒让德多项式的正交变换信号重构方法。使用这样的变换提供了优于多项式基的计算优势。我们将离散的Legendre多项式扩展到二维离散的Legendre多项式,用于图像的重构和压缩。在实际应用中,我们注意到当多项式的阶数变大时,所提出的方法往往表现出数值不稳定性。我们提出了一种避免这种不稳定的可能方法。仿真结果表明,采用该方法得到的压缩误差较小,压缩比较好。并给出了该方法在系统识别中的应用。
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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