imager: FFT – R documentation

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FFT

Compute the Discrete Fourier Transform of an image

Description

This function is equivalent to R's builtin fft, up to normalisation (R's version is unnormalised, this one is). It calls CImg's implementation. Important note: FFT will compute a multidimensional Fast Fourier Transform, using as many dimensions as you have in the image, meaning that if you have a colour video, it will perform a 4D FFT. If you want to compute separate FFTs across channels, use imsplit.

Usage

FFT(im.real, im.imag, inverse = FALSE)

Arguments

`im.real`	The real part of the input (an image)
`im.imag`	The imaginary part (also an image. If missing, assume the signal is real).
`inverse`	If true compute the inverse FFT (default: FALSE)

Value

a list with components "real" (an image) and "imag" (an image), corresponding to the real and imaginary parts of the transform

Author(s)

Simon Barthelme

Examples

im <- as.cimg(function(x,y) sin(x/5)+cos(x/4)*sin(y/2),128,128)
ff <- FFT(im)
plot(ff$real,main="Real part of the transform")
plot(ff$imag,main="Imaginary part of the transform")
sqrt(ff$real^2+ff$imag^2) %>% plot(main="Power spectrum")
#Check that we do get our image back
check <- FFT(ff$real,ff$imag,inverse=TRUE)$real #Should be the same as original
mean((check-im)^2)

imager

Image Processing Library Based on 'CImg'

v0.42.10

LGPL-3

Authors

Simon Barthelme [aut], David Tschumperle [ctb], Jan Wijffels [ctb], Haz Edine Assemlal [ctb], Shota Ochi [cre]

Initial release

FFT