RECHE23 / Accelerating-a-discrete-2d-convolution-using-FFT

Accelerating a discrete 2d convolution using FFT

Accelerating a discrete 2d convolution using FFT

This Jupyter Notebook demonstrates how to accelerate 2D convolution using the Fast Fourier Transform (FFT). FFT-based convolution is particularly useful for large convolutional filters and input images.

License

This project is licensed under the MIT License. Feel free to explore and modify the code as a learning exercise.

Author

This notebook was composed by René Chenard, a computer scientist and mathematician with a degree from Université Laval.

You can contact the author at: [e-mail]