Frequency transform Image¶
Apply 2D Discrete Fourier Transform to input image, decomposing it into frequency components.
Documentation¶
The Discrete Fourier Transform takes an image and decomposes it into its constituent components in the frequency domain. This has many applications in image processing.
All different transforms in this node are variants of the two-dimensional Discrete Fourier Transform (DFT), and they all use the Fast Fourier Transform (FFT) algorithm under the hood.
To inverse a transform you select that same transform and check the Inverse.
Force real values on inverse¶
When doing inverse transforms you might find that the result is complex, even when you expect it to be real. Mathematically, any hermitian or conjugare-symmetric function should result in a real function after inverse transform. Unfortunately because of discretization and/or the inherent inaccuracy or floating-point arithmetics, this can not be guarateed in practice. Instead the result will be almost real in these cases.
If you check the option Force real values on inverse the node will do element-wise absolute value of the result of the inverse transform, ensuring that the output is real-valued.
Definition¶
Input ports¶
- input image
Input image
Output ports¶
- output image
Transformed image
Configuration¶
- Inverse transformation (inverse)
Compute the inverse of the selected transform
- Operation (operation)
Transform to apply.
- Force real values on inverse (real)
If checked, ensure that output after inverse transform is real-valued by taking absolute value of each pixel value.
Examples¶
Implementation¶
- class node_frequency_image.FrequencyTransformImage[source]
