In this section, we will learn how to equalize a color image. Image equalization and histogram equalization try to obtain a histogram with a uniform distribution of values. The result of equalization is an increase in the contrast of an image. The equalization allows lower local contrast areas to gain higher contrast, spreading out the most frequent intensities.
This method is very useful when the image is almost dark or completely bright and there are very small differences between the background and foreground. Using histogram equalization, we increase the contrast and the details that are over- or under-exposed. This technique is very useful in medical images, such as X-rays.
However, there are two main disadvantages to this method: it increases the background noise and decreases useful signals.
We can see the effect of equalization in the following image and see how the histogram changes and spreads on increasing the image contrast:
Let's try to implement our histogram...
