Introduction:

Image enhancement is a fundamental step in image processing, aimed at improving the quality of an image to enhance its visual appeal, remove noise, or prepare it for further analysis. This module explores various techniques to enhance image quality, covering contrast adjustment, noise reduction, sharpening, and more.

What you'll learn:

•  Techniques for adjusting image contrast, brightness, and gamma
•  Noise reduction methods using filters (Gaussian, Median, Bilateral, etc.)
•  Image sharpening and smoothing techniques
•  Dehazing, deraining, and fog removal methods
•  Color correction and local tone mapping
•  Advanced techniques: deep learning-based denoising, Wiener filter, Kalman filter, and Savitzky-Golay filter

Objectives

•  Understand the importance of image enhancement in image processing
•  Learn to apply various image enhancement techniques using Python and OpenCV
•  Analyze and compare different techniques for specific use cases
•  Develop skills to implement image enhancement algorithms for real-world applications

Topics Covered:

Prerequisites:

•  Basic understanding of image processing concepts
•  Familiarity with Python and OpenCV

The future of computer vision is not just about recognizing images, but understanding their meaning. - Fei-Fei Li

Do continue your computer vision journey today with next module below.

#!/usr/bin/en
# -*- coding: utf-8 -*-

"""
	A Hello World kind of Demo code for Image Enhancement.
"""

import cv2
import numpy as np

# Load the image
img = cv2.imread('input_image.jpg')

# Display original image
cv2.imshow('Original Image', img)

# Apply basic image enhancements
enhanced_img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
enhanced_img[:, :, 2] = cv2.equalizeHist(enhanced_img[:, :, 2])
enhanced_img = cv2.cvtColor(enhanced_img, cv2.COLOR_HSV2BGR)

# Display enhanced image
cv2.imshow('Enhanced Image', enhanced_img)

# Save enhanced image
cv2.imwrite('output_image.jpg', enhanced_img)

# Wait for key press
cv2.waitKey(0)
cv2.destroyAllWindows()

# Requirements:
#   OpenCV (pip install opencv-python)
#   NumPy (pip install numpy)
#   Input image (input_image.jpg)

# Run the script:
#   Save the script as image_enhancement_hello_world.py
#   Replace input_image.jpg with your desired input image
#   Run the script using Python (python image_enhancement_hello_world.py)