## Histogram in digital photography

What is a histogram?
As defined in dictionaries, it’s called histogram a bar graph of a frequency distribution in which the widths of the bars are proportional to the classes into which the variable has been divided and the heights of the bars are proportional to the class frequencies, in the case of photography a histogram is a graphical representation of the pixels exposed in your image.
The left side of the graph represents the blacks or shadows, the right side represents the highlights or bright areas and the middle section is mid-tones (middle or 18% gray).
The height of the peaks represent the number of pixels in that particular tone, on a scale from 0-255 (0 - pure black, 255 - pure white) as shown in the picture below:

Before the histogram, photography enthusiasts had to go through a lot more effort to get good exposures, especially in analog photography.
While the histogram is one of the most useful tools on your camera, it’s also one of the least understood or often misunderstood.
Understanding the histogram in photography and how it helps you get the correct exposure on your images is one of the key steps in learning how to improve your photography skills and technique.

In this article, I’ll show you exactly how to interpret your camera’s histogram and use it to your advantage for better photography results.
Getting the best exposure in camera should be your goal every time you click the shutter, judging whether you have taken a decent exposure is simple with a DSLR after reviewing a preview of your picture on the LCD.
You can instantly see if your shot is too bright, or too dark and adapt your aperture and times for the next shot, it is apparently so easy and immediate that it seems unnecessary to have a second, more scientific, way of judging the suitability of your exposure settings.

How can histogram be useful in photography?
First, and foremost, displaying the camera’s histogram is not a replacement for looking at the image itself when you review a picture. This mathematical graph simply gives you some additional, but invaluable, information.
As colorful as your photo is, it is actually made up of Black, White and each shade of gray in between.
The histogram graphs out all of the pixels to show you how many of each shade of gray you have, giving you a quick overview of the pixel distribution useful to avoid pure black and pure white pixels high concentration that respectively represents under and over exposed pictures.

Another point to consider is that the histogram is based on a JPEG image of the shot that you are taking.
If you shoot in RAW, the camera will capture more tonal detail (as it is captured in a 12-bit or 14-bit form, rather than the 8-bit limit used by JPEGs); this is one of the reasons why RAW format is more flexible and allow you to recover highlights that appear blown out in the graph using RAW conversion software.
It’s also worth pointing out that parts of some images should be clipped, simply because they should be shown as pure white or pure black.

Recent DSLRs also give the option to show a color histogram, in addition to the black-and-white luminosity version. This RGB histogram shows three separate graphs, corresponding to the red, green and blue channels that the picture is made up of.
If you see a marked difference in the three graphs, it can give you an indication of a white balance problem (though this may simply show that one particular color dominates the composition).

With some subjects, clipped detail in the channels can also help you to ensure you get maximum detail in a particular subject (eg: a bright green leave).
However, for most purposes, the simple black-and-white graph is all you need to avoid exposure pitfalls.

Now that you've learned the theory, take your camera and practice!