How can I do the histogram equalization?

Hello
I think that the histogram equalization on the 3 components of a color image has the effect of increasing the contrast in order to facilitate the detection of the region of interest that is darker than the other part of the image. How can I do this using matlab? thanks

Risposte (2)

Aneesh Balaji
Aneesh Balaji il 14 Nov 2012
Hey For a color image split into 3 components and perform histeq on each of them and then recombine them.

1 Commento

Tomas
Tomas il 14 Nov 2012
Modificato: Tomas il 14 Nov 2012
I used these lines but i got this result
r=im(:,:,1);
v=im(:,:,2);
b=im(:,:,3);
r1 = histeq(r);
v1 = histeq(v);
b1 = histeq(b);
img = cat(3,r1,v1,b1);

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Image Analyst
Image Analyst il 14 Nov 2012
Using histeq() on individual color channels is not a good method. You will introduce color artifacts which may be severe. You're best off converting to hsv color space, then using histeq() or adapthisteq() on only the v channel, then recombine and transform back to rgb color space.

4 Commenti

I tried this but I got also a bad result
im=rgb2hsv(im);
h=im(:,:,1);
s=im(:,:,2);
v=im(:,:,3);
v1 = histeq(v);
img = cat(3,h,s,v1);
img2=hsv2rgb(img);
Looks like it should be right. Maybe it's some kind of uint8/double conflict. Can you post your image somewhere?
I'm working on a large number of images. I just need to equalize the histogram to facilitate detection of the dark object. this is an example http://s13.postimage.org/99yr0g2p3/image.jpg
Histogram equalization is not necessary for that purpose. In fact, it's rarely necessary for anything. And it looks like you'd do best with a texture filter, like entropyfilt() or stdfilt(), at least for the one image you posted.

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il 10 Nov 2012

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