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vision.FFT System object

Two-dimensional discrete Fourier transform

Description

The vision.FFT object computes the 2D discrete Fourier transform (DFT) of a two-dimensional input matrix.

Note

Starting in R2016b, instead of using the step method to perform the operation defined by the System object™, you can call the object with arguments, as if it were a function. For example, y = step(obj,x) and y = obj(x) perform equivalent operations.

Construction

fftObj = vision.FFT returns a 2D FFT object, fftObj, that computes the fast Fourier transform of a two-dimensional input.

fftObj = vision.FFT(Name,Value) configures the System object properties, specified as one or more name-value pair arguments. Unspecified properties have default values.

To compute FFT:

  1. Define and set up your FFT object using the constructor.

  2. Call the step method with the input image, I and the FFT object, fftObj. See the syntax below for using the step method.

J = step(fftObj,I) computes the 2-D FFT, J, of an M-by-N input matrix I, where M and N specify the dimensions of the input. The dimensions M and N must be positive integer powers of two when any of the following are true:

The input is a fixed-point data type
You set the BitReversedOutput property to true.
You set the FFTImplementation property to Radix-2.

Properties

FFTImplementation

FFT implementation

Specify the implementation used for the FFT as one of Auto | Radix-2 | FFTW. When you set this property to Radix-2, the FFT length must be a power of two.

Default: Auto

BitReversedOutput

Output in bit-reversed order relative to input

Designates the order of output channel elements relative to the order of input elements. Set this property to true to output the frequency indices in bit-reversed order.

Default: false

Normalize

Divide butterfly outputs by two

Set this property to true if the output of the FFT should be divided by the FFT length. This option is useful when you want the output of the FFT to stay in the same amplitude range as its input. This is particularly useful when working with fixed-point data types.

Default: false with no scaling

 Fixed-Point Properties

Methods

stepCompute 2D discrete Fourier transform of input
Common to All System Objects
clone

Create System object with same property values

getNumInputs

Expected number of inputs to a System object

getNumOutputs

Expected number of outputs of a System object

isLocked

Check locked states of a System object (logical)

release

Allow System object property value changes

Examples

expand all

Create the FFT object

fftObj = vision.FFT; 

Read in an image.

I = im2single(imread('pout.tif'));

Compute the FFT.

J = step(fftObj, I); 

Shift zero-frequency components to the center of the spectrum.

J_shifted = fftshift(J);

Display original image and visualize its FFT magnitude response.

figure; imshow(I); title('Input image, I'); 

figure; imshow(log(max(abs(J_shifted), 1e-6)),[]), colormap(jet(64));
title('Magnitude of the FFT of I');

References

[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. 1381-1384.

Extended Capabilities

Introduced in R2012a