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This repository contains our team's implementation of a desktop application using pyqt as an application of 2D Fourier Transform.

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Fourier Transform Mixer

The Fourier Transform Mixer is a desktop application designed to demonstrate the importance of magnitude and phase components in signal processing, particularly focusing on images. The program allows users to open and view up to four grayscale images simultaneously, visualize their Fourier Transform components, adjust brightness/contrast, mix components, select regions for mixing, and observe real-time mixing updates.

Features:

Image Viewers

  • Open and view up to four grayscale images simultaneously.
  • Automatically convert colored images to grayscale.
  • Resize images to the smallest size for uniformity.
  • Visualize Fourier Transform components (Magnitude, Phase, Real, Imaginary) for each image.

Output Ports

  • Display mixer results in one of two output viewports.
  • Switch between output viewports as desired.

Brightness/Contrast Adjustment

  • Adjust brightness and contrast using mouse moving up, down, right and left .
  • Apply adjustments to individual images and Fourier Transform components.

Components Mixer

  • Customize weights for each image's Fourier Transform components using sliders.
  • Calculate weighted averages for the Fourier Transforms.
  • Perform inverse Fourier Transform to obtain the output image.

Regions Mixer

  • Select inner or outer regions for Fourier Transform components.
  • Highlight selected regions and adjust their size or percentage.

Real-time Mixing

Screenshots:

WhatsApp Image 2024-02-26 at 20 21 08 WhatsApp Image 2024-02-26 at 20 21 53

Team members:

Acknowledgments:

This project was supervised by Dr. Tamer Basha and Eng. Abdullah Darwish, who provided invaluable guidance throughout its development as a part of the Digital Signal Processing course (Spring 2024) at Cairo University Faculty of Engineering

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This repository contains our team's implementation of a desktop application using pyqt as an application of 2D Fourier Transform.

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