How to read a Histogram

Man I hated Histograms. Back when I was in school, they seemed stupid and pretty useless and I loathed making them in a class. Now fast forward almost 15 years and now I am a changed person. I love Histograms and use them extensively while shooting photographs. Surprised? Well read on..

If by any chance, you have missed your school (or slept through the periods) and do not know what a histogram is, here is your chance to learn it again. A histogram is a display of statistical information that uses rectangles to show the frequency of data items in successive numerical intervals of equal size. In the most common form of histogram, the independent variable is plotted along the horizontal axis and the dependent variable is plotted along the vertical axis. 

Still not clear? Well a histogram in a digital camera is exactly the same thing as explained above. It shows the distribution of tonal range of a particular digital image. Histogram is one of the most important advantages of a modern digital camera as we can manage our exposure very easily by reading the histogram. Actually, in modern image processing softwares, there are separate histograms available for each individual colour channels (Red, Green and Blue), but we shall not be looking in to that aspect in this post and will be looking only at the unified histogram. So without further ado, lets get into decoding Histogram.

In order to understand things better, lets first understand that we can divide the whole tonal range of a Photo in three distinct divisions. 1. Shadows 2.Midtones and 3. Highlights. The left side of a histogram denotes shadows, the middle represents mid tones and the right represents the high lights in a photo. The length of the bars in a histogram denotes how many pixels are there in a particular tonal range. The extreme left end of the histogram denote a ‘0’ while the extreme right denote ‘255’. All histogram have the same range of 0-255. Now these are not some random numbers but a combination of tones. A zero meanes absolutely no light or perfect black whereas 255 denotes perfect white. A random histogram shown below for illustrative purpose-

So, in order to clarify things further, lets take a look at an image with its histogram-

As you can see, the picture is mostly dark with some of the places dimly lit. So, most of the pixels of this image are either completely black or very dark shades. Hence the histogram of this photo shows a big spike on the left side, with very little data on the mid tones and highlights sections (because there are not much details in the photo itself ). Lets take a look at another example-

This was a day time image, taken on a cloudy day. See how the histogram shows a balanced spread of pixels. It means that no single tone dominates the image and the lighting is pretty flat and even.

So, now we can see that how the peaks & dips in a histogram tell us how dominant a particular shade is in the image. So, if on a normal lighting condition, the histogram shows a heavy spike towards the left (which means a lot of pixels are dark), we can safely assume that the image is under-exposed and in case of the opposite, its over-exposed.  While this statement is generally true, there is a big catch involved in this.

What is a "perfect" Histogram

Anyone after reading and understanding the above, will straightway come to the conclusion that a histogram where there is an average distribution of tones with no pixels completely white or black is a "perfect" histogram. But in normal shooting circumstances, it is rarely so. Just like there can't be a perfect exposure, there can't be a perfect histogram and that's because every image is unique. For example,if we take a photo of a person wearing black cloths with a dark background , it will show a left-heavy histogram, even if it is properly exposed. On the other hand, if you photograph a child wearing bright clothes on a snowy environment, the histogram will show most pixels on the righter side, but the photo will not be over-exposed. 

That's all fine, but what do I take from all this boring lecture

For the real lazy bums out there (in other words, people like me) let me summarize all the discussions in some bullet points for reference-

• Keep an eye out on the histogram while shooting. If you notice that some pixels are touching the extreme ends, it means some area of the image is getting completely over-exposed or under exposed. In such cases, try to adjust the exposure and shoot again. Because in any photo, an unintentional over/under exposed part looks bad and draws the viewers attention to that point only. 
• If you post process your images a lot, its always advisable to take a look at the histogram all the time to make sure that you are not creating any gaps in the histogram. Such gaps can occur due to heavy and careless editing. These gaps means you have completely uprooted the particular pixels and they are irrecoverable. Avoid this.
• With time, it will just become a second practice to check the histogram after every shoot. It really gives a correct idea regarding the exposure of a particular image, provided you know beforehand how your ideal histogram should look like. Thats not easy, but with some practice, its definitely doable. 

So, there you have it. I have tried my best to explain this concept but I know that there will be doubts. If you have any such doubts, please leave a comment below and I will try my best to break it down for you. Do give this a try. You will be amazed how using this tool, you can manage to get proper exposure for each and every of your photo.