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A min-max approach to the multidimensional nonuniform FFT: application to tomographic image reconstruction

机译:多维非均匀FFT的最小-最大值方法:在断层图像重建中的应用

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The FFT is used widely in signal processing for efficient computation of the Fourier transform (FT) over a set of uniformly spaced frequency locations. However, in many applications, one requires nonuniform sampling in the frequency domain, i.e., a nonuniform FT. Several papers have described fast approximations for the nonuniform FT based on interpolating an oversampled FFT. This paper presents a method for the nonuniform FT that is optimal in a min-max sense. The proposed method minimizes the worst-case approximation error over all signals of unit norm. Unlike many previous methods for the nonuniform FT, the proposed method easily generalizes to multidimensional signals. We are investigating this method as a fast algorithm for computing the Radon transform in 2D iterative tomographic image reconstruction.
机译:FFT在信号处理中被广泛使用,以在一组均匀间隔的频率位置上高效地进行傅立叶变换(FT)的计算。但是,在许多应用中,需要在频域中进行非均匀采样,即非均匀FT。几篇论文描述了基于内插过采样FFT的非均匀FT的快速逼近。本文提出了一种在最小-最大意义上最优的非均匀傅立叶变换方法。所提出的方法使所有单位范数信号的最坏情况下的近似误差最小。与许多以前的非均匀FT方法不同,所提出的方法很容易推广到多维信号。我们正在研究此方法,作为在2D迭代层析图像重建中计算Radon变换的快速算法。

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