No, it is not normal. Depending what you understand under "image quality" but visually, equilized images look good, in some sense, better than the original. Check your algorithm implementation. Actually, it is a very simplistic quesiton for a scientific site. I answer it here only because I am new myself, and this is the very first time I have logged in to this site...

Dear Igor

i know that histogram equalization and its extension are used to improve the quality of image, but first this methods have the inconveninent to enhance the noise too in the image and produce unnatural image , i use this method in preprocessing step in biometrics , but the data base without using histogram equalization give more efficienty thant with HE, that is why i mentionned "is it normal"

PS: Igor a simplistic or not , we are here to lean from each other

Sorry, I was a little harsh, but there are other, probably better places to discuss implementations, like LinkedIn... Then filter noise ! Histrogram equalization greatly improves visible brightness "resolution" in the low contrast places. Try to limit the number of bins, say make 24 bins per 256-level gray image. It may decrease some noise and show "shapes of brightness" better at the expence of some resolution.

No, it only affects the image brightness and improve it. I have never read about the histogram equalization and adaptive histogram equalization gives bad effect

Histogram Equalization does improve contrast in some cases, but it may introduce noise and other undesired effect.

Image regions that are dark and not clearly visible become clearer but this may happen at the expense of other regions.

These undesired effect is a consequence of digitization. When digitize the continuous operations rounding leads to approximations.

Images for which different regions exhibit different brightness level, may benefit from applying HE on sub-blocks of the images.

The quality of well lit images after HE suffer more than expected.

applying HE on RGB introduce unexpected results, instead convert to HSV color system and do HE only on the V (illumination) part.

I hope this is helpful.

I agree with Ahmad. In general, HE increases the contrast of the image. As a result, it may increase the contrast of background noise, while decreases the contrast of foreground object.

Just in case, HE has nothing to do with the efficiency of the related system. It does not change the image resolution, and does not decrease the depth of the image (basically, it increases the depth).

Gamma correction is a better alternative of HE in practice. But unlike HE, gamma correction does not necessarily have a theoretical support.

In recent years, there has been many studies, which aim at improving HE such that its side effect can be avoided.

Whether HE can degrade an image? Yes!

HE could greatly improve level/window (= brightness/contrast) when you print the image. But when the image is still in computer memory, any good viewer will allow you to blow up contrast of regions of interest, without affecting the original data.

The danger of HE is that pixel-values that are just a little different in the original image, can wind up in the same bin after applying HE; thus leading to unrecoverable information loss.

So, while HE can improve superficial visual inspection, it can lead to information loss. Only when there are unused parts of the dynamic range, HE can preserve information. Besides that, proportionality of pixel-values to circumstances in the physical world and the acquisition-equipment is also lost.

Beware!