Package: vision
Two–dimensional inverse discrete Fourier transform
The vision.IFFT
object computes the inverse
2D discrete Fourier transform (IDFT) of a twodimensional input matrix.
The object uses one or more of the following fast Fourier transform
(FFT) algorithms depending on the complexity of the input and whether
the output is in linear or bitreversed order:
H = vision.IFFT
returns
a 2D IFFT object, H
, with the default property and
value pair settings.
H = vision.IFFT(
returns
a 2D IFFT object, Name
,Value
)H
, with each property set to the
specified value. You can specify additional namevalue pair arguments
in any order as (Name1
, Value1
,...,NameN
,ValueN
).
Code Generation Support 

Supports MATLAB^{®} Function block: Yes 
System Objects in MATLAB Code Generation. 
Code Generation Support, Usage Notes, and Limitations. 

FFT implementation Specify the implementation used for the FFT as one of 

Indicates whether input is in bitreversed order Set this property to 

Indicates whether input is conjugate symmetric Set this property to 

Divide output by FFT length Specify if the 2D IFFT output should be divided by the FFT length.
The value of this property defaults to 
clone  Create IFFT object with same property values 
getNumInputs  Number of expected inputs to step method 
getNumOutputs  Number of outputs from step method 
isLocked  Locked status for input attributes and nontunable properties 
release  Allow property value and input characteristics changes 
step  Compute 2D inverse discrete Fourier transform 
Use the 2D IFFT object to convert an intensity image.
hfft2d = vision.FFT; hifft2d = vision.IFFT; % Read in the image xorig = single(imread('cameraman.tif')); % Convert the image from the spatial % to frequency domain and back Y = step(hfft2d, xorig); xtran = step(hifft2d, Y); % Display the newly generated intensity image imshow(abs(xtran), []);
This object implements the algorithm, inputs, and outputs described on the 2D IFFT block reference page. The object properties correspond to the Simulink^{®} block parameters.
[1] FFTW (http://www.fftw.org
)
[2] Frigo, M. and S. G. Johnson, "FFTW: An Adaptive Software Architecture for the FFT,"Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, Vol. 3, 1998, pp. 13811384.