2D FFT (fft2) in SciPy - Mini Project: Build & Apply

2D FFT (fft2) Analysis of Image Data

📖 Scenario: You have a small 2D image represented as a grid of pixel brightness values. You want to analyze the image's frequency components using a 2D Fast Fourier Transform (FFT).

🎯 Goal: Build a Python program that creates a 2D array representing an image, sets up a configuration variable for the FFT, applies the 2D FFT using scipy.fft.fft2, and prints the transformed data.

📋 What You'll Learn

Create a 2D numpy array called image with exact values

Create a variable called norm_mode to configure normalization

Use scipy.fft.fft2 with image and norm=norm_mode

Print the resulting 2D FFT array

💡 Why This Matters

🌍 Real World

2D FFT is used in image processing to analyze patterns, compress images, and filter noise.

💼 Career

Understanding 2D FFT helps in roles like data analyst, image processing engineer, and machine learning specialist working with visual data.

1

Create the 2D image array

Create a 2D numpy array called image with these exact values: [[1, 2, 3], [4, 5, 6], [7, 8, 9]].

SciPy

import numpy as np
# Create the 2D numpy array called image with the specified values
# Your code here

Need a hint?

Use np.array to create a 2D array with the exact nested list values.

2

Set the normalization mode for FFT

Create a variable called norm_mode and set it to the string 'ortho' to normalize the FFT output.

SciPy

import numpy as np
image = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
# Create the variable norm_mode and set it to 'ortho'
# Your code here

Need a hint?

Assign the string 'ortho' to the variable norm_mode.

3

Apply the 2D FFT to the image

Import fft2 from scipy.fft and create a variable called fft_result by applying fft2 to image with norm=norm_mode.

SciPy

import numpy as np
image = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
norm_mode = 'ortho'
# Import fft2 and apply it to image with norm=norm_mode, store in fft_result
# Your code here

Need a hint?

Use from scipy.fft import fft2 and call fft2(image, norm=norm_mode).

4

Print the 2D FFT result

Print the variable fft_result to display the 2D FFT output.

SciPy

import numpy as np
image = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
norm_mode = 'ortho'
from scipy.fft import fft2
fft_result = fft2(image, norm=norm_mode)
# Print the fft_result variable
# Your code here

Need a hint?

Use print(fft_result) to show the FFT output.