Histogram equalization skimage

1. What does histogram equalization do?
2. Where does histogram equalization fail?
3. What are the disadvantages of histogram equalization?

What does histogram equalization do?

Histogram equalization is a method to process images in order to adjust the contrast of an image by modifying the intensity distribution of the histogram. The objective of this technique is to give a linear trend to the cumulative probability function associated to the image.

Where does histogram equalization fail?

Histogram equalization fails when the input image (a) has a large area low-intensity background. In this case, the histogram (d) has a spike component corresponding to the background graylevel.

What are the disadvantages of histogram equalization?

So in theory, if the histogram equalization function is known, then the original histogram can be recovered. The calculation is not computationally intensive. A disadvantage of the method is that it is indiscriminate. It may increase the contrast of background noise, while decreasing the usable signal.