MATLAB: Reason for Histogram Equalisation for having “stacked” effects

histeqhistogramhistogram equalizationImage Processing Toolbox

I read in an image, run histeq on the it and store it as Img2. Then I run histeq again on Img2 and store it as Img3.

It turns out that when I compare the histograms of Img2 and Img3, the histogram of Img3 looks more equalised and uniform. Both Img2 and Img3, however, look almost identical with naked eyes.

This is a screenshot of their histograms. The one on the left is the histogram for Img2, while the right one is for Img3:

So it looks like the histogram equalisation can be "stacked" and by running many times can make the image even more uniform? Is there a reason for this?

Best Answer

What was your second input argument to histeq()?

Related Solutions

MATLAB: How to equalize histogram of two images

You could try imhistmatch(), but as you can see below, it doesn't do such a great job:

testImage = imread('moon.tif');
subplot(2, 3, 1);
imshow(testImage);
refImage = imread('cameraman.tif');
subplot(2, 3, 2);
imshow(refImage);
matchedImage = imhistmatch(testImage, refImage); 
subplot(2, 3, 3);
imshow(matchedImage);
% Plot histograms
subplot(2, 3, 4);
imhist(testImage);
subplot(2, 3, 5);
imhist(refImage);
subplot(2, 3, 6);
imhist(matchedImage);

If you really want to do it right, you have to employ a few tricks (adding noise, sorting, randomly picking, etc.). I employ these tricks in my File Exchange submission which will match any histogram to any other histogram regardless of the shape.

Click for Image Analyst's program

MATLAB: Image with uniform histogram

http://www.mathworks.com/matlabcentral/answers/23228-i-want-to-know-if-we-can-implement-histogram-equalization-without-the-histeq-function

Best Answer

Related Solutions

MATLAB: How to equalize histogram of two images

MATLAB: Image with uniform histogram

Related Question