Histogram Equalisation by converting an RGB image into a GrayScale Image/ Histogram Equalisation of Grayscale Image

This opencv tutorial is about drawing histogram of a grayscale image.

What is a Image Histogram?

Histogram of an image represents the relative frequency of occurrence of various tonal values of an image. In other words it is a graphical representation of the intensity distribution of an image.

Simply said, it plots the number of times (frequency) each intensity values(pixel values) occurs in image.

E.g.: Consider the following matrix of an image :-

1	4	7	6	2	5
5	7	3	5	3	3
7	5	6	3	4	7
1	5	4	2	2	3

Here the depth of the image is 8.Since the highest value of pixel in this image is 7

Note:-Depth of n represents that the range of pixel values is from 0 to n-1

Histogram shows the pattern of distribution of pixel in an Image.

The above image contains 2 pixels of intensity 1, 3 pixels of intensity 2, 5 pixels of intensity 3 and so on.

This can be tabulated as:

Pixel Value	No. of Pixels
0	0
1	2
2	3
3	5
4	3
5	5
6	2
7	4

The following graph shows the histogram of the above image:-

What is histogram equalization?

Histogram equalization is defined as equalizing the intensity distribution of an image or flattening the intensity distribution. It helps in enhancing the contrast of the image.

The graph of the equalized histogram looks like this:

Here is the opencv histogram equalization code :

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>

using namespace cv;
using namespace std;

int mainundefined)
{
  //Declare the source and destination images as well as the windows names:
  Mat src, dst;
  char* source_window = "Source image";
  char* equalized_window = "Equalized Image";

  // Load image
  src = imreadundefined "C:\\Users\\arjun\\Desktop\\input.jpg", 1 );

  ifundefined !src.data )
    { 
     cout<<"No image Found "<<endl;
     return -1;
    }

  // Convert to grayscale
  cvtColorundefined src, src, CV_BGR2GRAY );

  // Apply Histogram Equalization
  equalizeHistundefined src, dst );

  // Display results
  namedWindowundefined source_window, CV_WINDOW_AUTOSIZE );
  namedWindowundefined equalized_window, CV_WINDOW_AUTOSIZE );

  imshowundefined source_window, src );
  imshowundefined equalized_window, dst );

  // Wait until user exits the program
  waitKeyundefined0);

  return 0;
}

Before Histogram Equalization Image:

After Histogram Equalization Image:

Frequency distribution table of before histogram equalisation image:

Frequency distribution table of histogram equalized image:

Note: The difference between two frequency distribution table and the corresponding image before histogram equalization to that after histogram equalization