color image enhancement opencv python

Image enhancement is a crucial step in computer vision and image processing applications. In this tutorial, we will explore color image enhancement using the OpenCV library in Python. We will cover basic techniques to improve the visual quality of color images.
Before getting started, make sure you have the following installed:
You can install OpenCV using the following command:
Color image enhancement involves improving the visual appearance of an image by adjusting its colors and contrast. OpenCV provides various functions to achieve this, and in this tutorial, we'll focus on the following techniques:
Histogram Equalization: A method to adjust the distribution of pixel intensities, enhancing the overall contrast.
CLAHE (Contrast Limited Adaptive Histogram Equalization): An improvement over histogram equalization, which limits the contrast in local regions to avoid over-amplifying noise.
Let's dive into the Python code for color image enhancement using OpenCV:
Loading the Image:
Converting to RGB:
Displaying the Original Image:
Histogram Equalization:
Converting Equalized Image to RGB:
Displaying the Equalized Image:
Showing the Plot:
This tutorial covered basic color image enhancement techniques using OpenCV in Python. Experiment with different images and parameters to observe the effects of these techniques on various types of images.
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