Python Computer Vision Tutorials — Image Fourier Transform / part 1 (Introduction and Basics)
CONTENTS LIST
Introduction
Do you know Fourier Transform on signal processing? Fourier Transform is a mathematical method to analyze frequency components in one dimensional signal, such as sound or radio wave. By applying Fourier Transform on such signal, which is time domain information, we can know, for example, how much 3000 Hz component is included in the signal.
But it also can be applied on 2-dimensional information, such as images. This type of Fourier Transform is called 2-D Fourier Transform. In the next few tutorials, I’m going to show you how to use 2-D Fourier on images and why it is so popular on computer vision.
What is 2-D Fourier Transform
This is a type of Fourier Transform which takes 2-dimensional data (2-D numpy array) as input, and returns another 2-dimensional data. We usually use this 2-D Fourier Transform on images.
