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The repository contains an implementation of the Cooley-Tukey Fast Fourier Transform and Discrete Fourier Transform using Python.

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Fast Fourier Transform for Image Processing (Python 3.12)

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Created by Marc-Antoine Nadeau and Karl Bridi

Description

This Python program implements the Fast Fourier Transform. It was developed and tested using Python 3.12.

How to Run

To invoke the application, navigate to the src directory and use the following command in your terminal:

cd src
python fft.py [-m mode] [-i image]

Example

Here's an example:

python fft.py -m 3 -i Triumph.png

where Triumph.png is placed in the /Figures directory, and you are in the src directory

Features

Mode (optional):

  • 1. Fast mode (default): Convert image to FFT form and display.
  • 2. Denoise: The image is denoised by applying an FFT, truncating high frequencies, and then displayed.
  • 3. Compress: Compress image and plot.
  • 4. Plot runtime graphs.

Image (optional):

  • The filename of the image for the DFT (default: moonlanding.png).

Note: The files should be placed in the Figures folder.

Installation

To install the required packages, run the following command:

pip install numpy opencv-python matplotlib

This will install numpy, opencv-python, and matplotlib for your project.

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The repository contains an implementation of the Cooley-Tukey Fast Fourier Transform and Discrete Fourier Transform using Python.

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