Histogram Equalization in OpenCV

What is an Image Histogram

  • It is a graphical representation of the intensity distribution of an image.
  • It quantifies the number of pixels for each intensity value considered.

What is Histogram Equalization

It is a method that improves the contrast in an image, in order to stretch out the intensity range.

How does it work

  • Equalization implies mapping one distribution (the given histogram) to another distribution (a wider and more uniform distribution of intensity values) so the intensity values are spreaded over the whole range.
  • To accomplish the equalization effect, the remapping should be the cumulative distribution function (cdf). For the histogram img, its cumulative distribution img2 is:
    To use this as a remapping function, we have to normalize img2 such that the maximum value is 255 ( or the maximum value for the intensity of the image ).
  • Finally, we use a simple remapping procedure to obtain the intensity values of the equalized image:


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

using namespace cv;
using namespace std;

/**  @function main */
int main( int argc, char** argv )
	Mat src, dst;

	IplImage* newImg;
	/* load an image named "desert.jpg", 1 means
	this is a color image */
	newImg = cvLoadImage("Desert.jpg",1);

	char* source_window = "Source image";
	char* equalized_window = "Equalized Image";

	/// Load image
	src = cvarrToMat(newImg);

	/// Convert to grayscale
	cvtColor( src, src, CV_BGR2GRAY );

	/// Apply Histogram Equalization
	equalizeHist( src, dst );

	/// Display results
	namedWindow( source_window, CV_WINDOW_AUTOSIZE );
	namedWindow( equalized_window, CV_WINDOW_AUTOSIZE );

	imshow( source_window, src );
	imshow( equalized_window, dst );

	/// Wait until user exits the program

	return 0;




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