# HISTOGRAM EQUALISATION PDF

Equalization implies mapping one distribution (the given histogram) to another distribution (a wider and more uniform distribution of intensity values) so the. Histogram equalization is a technique for adjusting image intensities to enhance contrast. normalized histogram of f with a bin for each possible intensity. So. Histogram is a graphical representation of the intensity distribution of an image. In simple terms, it represents the number of pixels for each.

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We have already seen that contrast can be increased using histogram stretching.

In this tutorial we will see that how histogram equalization can be used to enhance contrast. Before performing histogram equalization, you must eqkalisation two important concepts used in equalizing histograms. Please visit them in order to successfully grasp the concept of histogram equalization.

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Histogram equalization is used to enhance contrast. It is not necessary that contrast will always be increase in this.

### Point Operations – Histogram Equalization

There may be some cases were histogram equalization can be worse. In that cases the contrast is decreased. First we have to calculate the PMF probability mass function of all the pixels in this image.

Our next step involves calculation of CDF cumulative distributive function. Considering we have an 3 bpp image. Then number of levels we have are 8. And 1 subtracts 8 is 7.

So we multiply CDF by 7. Here what we got after multiplying. Now we have is the last step, in which we have to map the new gray level values into number of pixels.

## Histogram equalization

Now map these new values you are onto histogram, and you are done. Lets apply this technique to our original image.

After applying we got the following image and its following histogram. As you can clearly see from the images that the new image contrast has been enhanced and its histogram has also been equalized.