On Reconstruction from Non-uniform Spectral Data

被引：21

作者：

Viswanathan, Adityavikram ^{[1
]}

Gelb, Anne ^{[2
]}

Cochran, Douglas ^{[1
]}

Renaut, Rosemary ^{[2
]}

机构：

[1] Arizona State Univ, Sch Elect Comp & Energy Engn, Tempe, AZ 85287 USA

[2] Arizona State Univ, Sch Math & Stat Sci, Tempe, AZ 85287 USA

来源：

JOURNAL OF SCIENTIFIC COMPUTING | 2010年 / 45卷 / 1-3期

基金：

美国国家科学基金会;

关键词：

Non-harmonic Fourier reconstruction; Sampling density; Convolutional gridding; Spectral re-projection; FAST FOURIER-TRANSFORMS; DENSITY COMPENSATION; MRI; EDGES;

D O I：

10.1007/s10915-010-9364-3

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper addresses the reconstruction of compactly supported functions from non-uniform samples of their Fourier transform. We briefly investigate the consequences of acquiring non-uniform spectral data. We summarize two often applied reconstruction methods, convolutional gridding and uniform re-sampling, and investigate the reconstruction accuracy as it relates to sampling density. Finally, we provide preliminary results from employing spectral re-projection methods in the reconstruction.

引用

页码：487 / 513

页数：27

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