Once the image histogram is calculated, it can be modelled so that the image is modified and the histogram has a different shape. This is useful to change the low-contrast levels of images with narrow histograms, since this will spread out the gray levels and thus enhance the contrast. Histogram modeling, also known as histogram transfer, is a powerful technique for image enhancement. In histogram equalization, the goal is to obtain a uniform histogram for the output image. That is, a flat histogram where each pixel value has the same probability. In OpenCV, histogram equalization is performed with the function void equalizeHist(InputArray src, OutputArray dst). The first parameter is the input image and the second one is the output image with the histogram equalized.

The following EqualizeHist_Demo example shows how to calculate and display the histogram equalized and the effect on the two-dimensional image:

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc...