Introduction to the Intensity Histogram in Image Processing

A histogram is a graphical representation of a set of data (continuous) that lets you discover, and show, the underlying frequency distribution (shape) of the data.

In Image Processing, we use Intensity Histograms to describe the tonal distribution in a digital image. By looking at the histogram for a specific image a viewer will be able to judge the entire tonal distribution at a glance. The horizontal axis of the graph represents the tonal variations, while the vertical axis represents the number of pixels in that particular tone.

In 8 bits representation, there are 2⁸ gray levels, that is, 256 gray levels (0,1,….255). We use gray level 0 to represent Black and gray level 255 to represent White.

We are moving to each and every pixel in a digital image to find the gray levels and then we increment the appropriate frequency to create the histogram.

The following picture describes how a grayscale image is transformed into a histogram.

What about recreating an image from the histogram? Is it possible?

The answer is definitely ‘NO’, here is why,

All those three pictures have similar histograms. The recreation is not possible and it is also in the definition of the histogram too. That is, it only describes the tonal distribution of an image. But if we have the location details (information about the spatial arrangement) of all levels, we can recreate the image but unfortunately in the intensity histogram, we have only the levels and their occurrences in the picture.