用二维傅里叶变换分析一些二维函数:图像重建和物理意义

G. K. Jagatheswari, G. Honnavar, M. R
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引用次数: 3

摘要

傅里叶变换可以被认为是将图像分解成二维空间正弦频率分量。二维高斯,矩形(Rect)和圆形(Circ)函数是使用二维傅里叶级数和变换近似创建的。傅里叶域或频域表示空间域图像中包含的特定频率的点。本文从衍射图样的角度分析了二维基本信号(包括图像)的光谱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of some two dimensional functions using two dimensional Fourier transforms: Image reconstruction and physical significance
The Fourier transform can be thought of being the decomposition of the image into two dimensional spatial sinusoidal frequency components. Two dimensional Gaussian, Rectangular (Rect) and Circular (Circ) functions were created using two dimensional Fourier series and transform approximations. The Fourier domain or frequency domain represents a point of a particular frequency contained in the spatial domain image. Here the spectrum of two dimensional basic signals (including images) is analyzed from the point of view of diffraction patterns.
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