Band-limited 2-D interpolation using NUFFT

R. Bloom
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引用次数: 1

Abstract

There exists a class of algorithms for fast approximate evaluation of trigonometric sums arising from extension of discrete Fourier transforms (DFT and IDFT) to irregular sample locations. These are referred to in the literature as “Non-uniform Fast Fourier Transforms” or “NUFFT”. These allow Fourier (trigonometric) interpolation to be done, for a given set of complex DFT coefficients, to a high degree of uniform approximation, in order O(N2) flops. This facilitates the theoretically pleasing prospect of using a Discrete Fourier Series to interpolate image data from a regularly sampled grid to intermediate irregular sample locations. Brute-force evaluation at N2 spatial locations, of a discrete 2-D Fourier series consisting of N2 modes scales as O(N4) and is prohibitive for image arrays on the order N ≈ 103 and above.. There are three variants of the trigonometric sums to be evaluated by such algorithms. The “Type-2” variant is that in which we sum a set of regular locations in the discrete Fourier domain, to evaluate the inverse transform at an irregular set of locations in the image domain. In other words, it is a method that allows us to use Fourier interpolation, with a relatively large number of DFT modes and a relatively large number of interpolation sites.
使用NUFFT的带限制二维插值
存在一类由离散傅里叶变换(DFT和IDFT)扩展到不规则样本位置引起的三角函数和的快速近似求值算法。这些在文献中被称为“非均匀快速傅里叶变换”或“NUFFT”。这允许傅里叶(三角)插值,对于给定的一组复DFT系数,以O(N2)次浮点数的高度均匀近似完成。这促进了使用离散傅立叶级数将图像数据从规则采样网格插值到中间不规则采样位置的理论上令人愉快的前景。由N2模态组成的离散二维傅立叶级数在N2个空间位置上的蛮力评估尺度为O(N4),并且对于N≈103阶及以上的图像阵列是禁止的。用这种算法计算三角和有三种变体。“Type-2”变体是我们在离散傅里叶域中对一组规则位置求和,以计算图像域中一组不规则位置的反变换。换句话说,它是一种允许我们使用傅里叶插值的方法,具有相对大量的DFT模式和相对大量的插值点。
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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