COLOR HISTOGRAM EQUALIZATION - MATLAB CODE

                          Histogram Equalization can be considered as redistribution of the intensity of the image. Color histogram equalization can be achieved by converting a color image into HSV/HSI image and enhancing the Intensity while preserving hue and saturation components. 

                          However, performing histogram equalization on components of R,G and B independently will not  enhance the image. At the end of this post, check the histogram of before and after histogram equalization of an image which is obtained by performing histogram equalization on the components(R,G and B) independently.

Steps to be performed:

1.      Convert RGB image into HSI Image.
http://angeljohnsy.blogspot.com/2013/05/converting-rgb-image-to-hsi.html

2.      Obtain the ‘Intensity Matrix’ from the HSI Image matrix

3.      Perform Histogram Equalization on the intensity Matrix
http://angeljohnsy.blogspot.com/2011/04/matlab-code-histogram-equalization.html

4.      Update the Intensity Matrix from the HSI Image matrix with the histogram equalized Intensity matrix

5.      Convert HSI Image back to RGB Image
http://angeljohnsy.blogspot.com/2013/06/convert-hsi-image-to-rgb-image.html

        

MATLAB CODE:

%COLOR HISTOGRAM EQUALIZATION

%READ THE INPUT IMAGE

I = imread('football.jpg');

%CONVERT THE RGB IMAGE INTO HSV IMAGE FORMAT

HSV = rgb2hsv(I);

%http://angeljohnsy.blogspot.com/2013/05/converting-rgb-image-to-hsi.html

%PERFORM HISTOGRAM EQUALIZATION ON INTENSITY COMPONENT

Heq = histeq(HSV(:,:,3));

%http://angeljohnsy.blogspot.com/2011/04/matlab-code-histogram-equalization.html

HSV_mod = HSV;

HSV_mod(:,:,3) = Heq;

RGB = hsv2rgb(HSV_mod);

%http://angeljohnsy.blogspot.com/2013/06/convert-hsi-image-to-rgb-image.html

figure,subplot(1,2,1),imshow(I);title('Before Histogram Equalization');

       subplot(1,2,2),imshow(RGB);title('After Histogram Equalization');

EXPLANATION:

RGB image matrix is converted into HSI(Hue ,Saturation and Intensity) format and histogram equalization is applied only on the Intensity matrix . The Hue and Saturation matrix remains the same. The updated HSI image matrix is converted back to RGB image matrix.

%DISPLAY THE HISTOGRAM OF THE ORIGINAL AND THE EQUALIZED IMAGE

HIST_IN = zeros([256 3]);

HIST_OUT = zeros([256 3]);

%http://angeljohnsy.blogspot.com/2011/06/histogram-of-image.html

%HISTOGRAM OF THE RED,GREEN AND BLUE COMPONENTS

HIST_IN(:,1) = imhist(I(:,:,1),256); %RED

HIST_IN(:,2) = imhist(I(:,:,2),256); %GREEN

HIST_IN(:,3) = imhist(I(:,:,3),256); %BLUE

HIST_OUT(:,1) = imhist(RGB(:,:,1),256); %RED

HIST_OUT(:,2) = imhist(RGB(:,:,2),256); %GREEN

HIST_OUT(:,3) = imhist(RGB(:,:,3),256); %BLUE

mymap=[1 0 0; 0.2 1 0; 0 0.2 1];

figure,subplot(1,2,1),bar(HIST_IN);colormap(mymap);legend('RED CHANNEL','GREEN CHANNEL','BLUE CHANNEL');title('Before Applying Histogram Equalization');

       subplot(1,2,2),bar(HIST_OUT);colormap(mymap);legend('RED CHANNEL','GREEN CHANNEL','BLUE CHANNEL');title('After Applying Histogram Equalization');

EXPLANATION:

Obtain the histogram of each component (Red,Green and Blue) independently.

Define the colormap ‘mymap’ with three colors namely Red, Green and Blue.

Display the histograms of the components before and after histogram equalization.

 NOTE:

Histogram of the above image by processing the components independently gives bad result.

 

Histogram Equalization applied on individual components