# Increase Contrast with Histogram Equalization

Contents Original Image by Dan Fador from Pixabay (Top left image is the main image, and the bottom left image is the grayscale version of the image. The right-side images are the result of Histogram Equalization)

## Motivation

Histogram is the process of visual representation of frequency distribution with a bar plot. In computer vision, an image histogram is the process of representation of the frequency of intensity values with a bar plot. With image histogram equalization, we can easily adjust the distribution of frequency values of the image intensities. Generally, the process helps us to increase the contrast and brightness of an image. The process is simple and easy to implement. This article will discuss the full process of histogram equalization along with coding examples.

1. `Image Histogram`
2. `Full process of histogram equalization`
3. `Step-by-step, hands-on implementation`

## Image Histogram

Image histogram is the representation of the frequency of image intensity values with a bar plot. In Fig -1, I have shown a sample image with its intensity values in a 2D space.

The values range from 0 to 7. Let’s calculate the frequency of the values.

An image histogram is a simple representation of the frequency against the intensity value with a bar plot, as shown in Fig-3.

• CDF holds the probability of a probability distribution less than or equal to a particular value. For example, PDF of the intensity value `0 → 0.12, 1 → 0.24, 2 → 0.12, etc. So, CDF for 1 is 0.12+0.24 = 0.36, 2 is 0.36+ 0.12=0.48, and so on.` The entire result is…