Image interpolation methods in Matplotlib - Mini Project: Build & Apply

Image interpolation methods

📖 Scenario: You have a small image represented as a 2D array of pixel values. You want to see how different interpolation methods affect the image when it is enlarged.

🎯 Goal: Learn to use matplotlib to display the same image enlarged using different interpolation methods.

📋 What You'll Learn

Create a small 2D numpy array representing an image

Set a variable for the interpolation method

Use matplotlib's imshow with the chosen interpolation method

Display the image with a title showing the interpolation method

💡 Why This Matters

🌍 Real World

Image interpolation is used when resizing images in photography, computer graphics, and medical imaging to keep images clear and smooth.

💼 Career

Understanding interpolation helps data scientists and engineers improve image processing tasks, computer vision models, and visualization quality.

1

Create a small image array

Import numpy as np and create a 5x5 numpy array called image with these exact values: [[0, 50, 100, 150, 200], [50, 100, 150, 200, 250], [100, 150, 200, 250, 255], [150, 200, 250, 255, 255], [200, 250, 255, 255, 255]]

Matplotlib

# Import numpy as np
# Create the 5x5 numpy array called image with the given values
# Your code here

Need a hint?

Use np.array([...]) to create the 2D array with the exact values.

2

Set the interpolation method

Create a variable called interp_method and set it to the string 'nearest' to choose the nearest neighbor interpolation.

Matplotlib

import numpy as np
image = np.array([[0, 50, 100, 150, 200],
                  [50, 100, 150, 200, 250],
                  [100, 150, 200, 250, 255],
                  [150, 200, 250, 255, 255],
                  [200, 250, 255, 255, 255]])
# Set interp_method to 'nearest'
# Your code here

Need a hint?

Just assign the string 'nearest' to the variable interp_method.

3

Display the image with interpolation

Import matplotlib.pyplot as plt. Use plt.imshow to display image with the interpolation set to interp_method. Add a title showing the interpolation method using plt.title. Use plt.show() to display the plot.

Matplotlib

import numpy as np
image = np.array([[0, 50, 100, 150, 200],
                  [50, 100, 150, 200, 250],
                  [100, 150, 200, 250, 255],
                  [150, 200, 250, 255, 255],
                  [200, 250, 255, 255, 255]])
interp_method = 'nearest'
# Import matplotlib.pyplot as plt
# Use plt.imshow with interpolation=interp_method
# Add a title with plt.title showing interp_method
# Show the plot with plt.show()
# Your code here

Need a hint?

Use plt.imshow(image, interpolation=interp_method, cmap='gray') to show the image in grayscale.

4

Change interpolation and display again

Change the value of interp_method to 'bilinear'. Then run the same plt.imshow, plt.title, and plt.show() commands again to see the image with bilinear interpolation.

Matplotlib

import numpy as np
image = np.array([[0, 50, 100, 150, 200],
                  [50, 100, 150, 200, 250],
                  [100, 150, 200, 250, 255],
                  [150, 200, 250, 255, 255],
                  [200, 250, 255, 255, 255]])
interp_method = 'nearest'
import matplotlib.pyplot as plt
plt.imshow(image, interpolation=interp_method, cmap='gray')
plt.title(f"Interpolation: {interp_method}")
plt.show()
# Change interp_method to 'bilinear'
# Display the image again with plt.imshow, plt.title, and plt.show
# Your code here

Need a hint?

Just assign 'bilinear' to interp_method and repeat the plotting commands.