Hi Jony,
In MATLAB, the “histeq” function works only on grayscale images. There are three options available to you depending on what you want to do:
- You could convert the image to grayscale.
- You could histogram equalize each channel individually
- You could convert the image into the LAB or HSV colour space, histogram equalize the L or V component, then convert back into RGB. Applying histogram equalization to each RGB channel separately can distort colors because it processes each channel independently.I tend to prefer the last option for colour images because it enhances contrast while preserving colors. Therefore, one method will be an enhanced grayscale image, and the other two will be an enhanced colour image.
Convert to grayscale then equalize:
G = imread('image1.jpg');
G = histeq(rgb2gray(G));
figure; imshow(G);
Equalize each channel individually:
G = imread('image1.jpg');
for i = 1 : size(G, 3)
G(:,:,i) = histeq(G(:,:,i));
end
figure; imshow(G);
Convert to HSV, histogram equalize the V channel then convert back:
G = imread('image1.jpg');
Gh = rgb2hsv(G);
Gh(:,:,3) = histeq(Gh(:,:,3));
G = im2uint8(hsv2rgb(Gh));
figure; imshow(G);
The “rgb2hsv” function is used to convert a coloured image to HSV.
Note that the output of "hsv2rgb" will be a “double” type image and so assuming that the original input image was “uint8”, use the “im2uint8” function to convert from “double” back to “uint8”.
For more information on “rgb2grey”, “hsv2rgb”, “rgb2hsv”, “histeq” functions, please refer to the following documentation links:
I hope this helps you perform histogram equalization in your image.
