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vision.FFT System object

Package: vision

Two-dimensional discrete Fourier transform

Description

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

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

Methods

 clone Create FFT 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 discrete Fourier transform of input

Examples

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Use 2-D FFT to View the Frequency Components of an Image

Create the FFT object.

`fftObj = vision.FFT;`

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

Compute the FFT.

`J = step(fftObj, I);`

Shift zero-frequency components to the center of 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

[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. 1381-1384.