Understanding photography histograms
Histograms have made their place in every single image editing software these days and, to master photography, you need a thorough understanding of them.
They are a part of the majority of the present day digital cameras and also some of the compacts can display them. So the meaning of such persistent inclusion suggests that histograms are very important.
So if you are a beginner photographer and don’t understand what these graphs represent then you have come to the right place. Remember there is nothing to be ashamed of because after reading this article you will become proficient at them.
They might appear complex at first but to be honest, they are not. And hopefully you will agree with me by the end of this tutorial, as I will teach everything about the histogram in simple terms; from how to “read” them to how useful they are for photographic needs, everything will be covered.
So let us begin:
General Understanding of Histogram
A histogram graphically represents the tonal values of your photo. In simple word, it reflects the number of tones of particular brightness that are part of your photograph, which can range from 0% brightness(black) to 100% brightness (white).
In a typical histogram, the dark tones are displayed on the left side of and if you move toward the right, the tones get lighter. In the middle of the histogram are the mid-tones, which don’t fall in the dark nor light category.
The vertical axis in the histogram refers to the number of tones of that particular lightness and the histogram itself is exposure-dependent and is also influenced by other factors such as tone curve and other settings.
Shadow and Highlight Clipping
When a portion of the histogram “touches” either of the edges, it indicates loss of detail, which is also known as clipping.
So if the histogram is touching the right side it is Highlight clipping which means areas are completely white and if the histogram is touching the left side it is Shadow clipping which means areas that are completely black.
In both cases, you can fix it by altering exposure settings.
If you want to view the clipping in your photograph, then engage histogram in your camera when reviewing images.
Each camera has different reviewing option for example in Nikon cameras you have to press the navigator keys down or up a couple of times when in review modes so that the correct settings can come up.
Majority of current DSLR cameras come with live histograms which react with the scene in real time. So if you want live histogram, you have to make use of the LCD screen of your camera instead of optical viewfinder to photograph in Live View mode.
If you notice any shadow clipping or highlight then immediately alter your exposure accordingly.
If you want to save shadow detail, then make the photo bright by setting a positive exposure compensation value such as +0.3 or +0.7, on the other hand, if you want to save highlight detail, then make the photo darker by setting a negative exposure compensation value such as -0.3 or -0.7.
You can set this Exposure compensation in most cameras through “+/-” button. If you are shooting in manual mode then you will have to alter ISO, shutter speed, or aperture accordingly.
Most histograms only display information of 3 primary colors; green red, and blue. That is why they are called RGB histograms.
You must have noticed that histograms consist of several diagrams that are marked with different colors. So 3 of the diagrams in a histogram are there to represent green, red, and blue color channels.
The gray diagram is to represent the areas where the 3 channels overlap. The Yellow, magenta, and cyan represent the areas where 2 of the channels overlap.
Histogram and Exposure
Photographers can perceive histograms as graphical representations of exposure and many of them do use it to evaluate whether the exposure based on histograms alone is “good” or “bad”.
They do this by reading the histograms as a “good” histogram renders most tones in its middle portion, and only minimum tones are found at the edges.
While a “bad” histogram mostly have tones at the edge which basically means that either there is underexposure leading to shadow clipping or overexposure leading to highlight clipping. It can even lead to both in a single photo.
Here are some examples to further explain the link between histogram and exposure:
When you look at an underexposed image it is too dark and lacks any sort of bright detail.
This is also represented in the Histogram as it clearly shows a shift to the left side as most of the tones fall in the shadow range, and you will even find some clipped (completely black) areas.
When you look at an overexposed image it is too light. Most of the tones are very bright and you will normally find no darker tones.
Majority of the portion of the image is completely white and is blown-out bearing no detail at all. This is confirmed by the histogram as it clearly shows a strong shift to the right.
Correctly Exposed images
In a well-exposed image, the brightness is perfect and there are neither too dark not too light areas. So in a histogram, it is represented by a much broader tone distribution and most of these are found in the “midtone” section.
There will be barely any tones at the extreme right or left side of the histogram, which will mean that no detail is lost in shadows nor any is blown out.
Can you use histograms to Set Exposure?
Based on the above examples a “good” histogram will have tones stored in the middle portion and this will represent correct exposure.
But this doesn’t work every time that is why histogram can never be completely effective for judging exposure. A simple conclusion which we have reached is that for overexposure and underexposure histograms are good as they can discover whether the image is clipped or shadowed.
But for evaluating correct exposure they are not so good as well exposed image depends on too many factors, other than tones such as your vision as well as the scene you are capturing.
So as histogram can merely show the number of tones of various brightness levels, the verdict is that they are not sufficient for determining exposure. It can act as a guide to avoid loss of detail when capturing images, as it excels in it but nothing more.
Learning how to evaluate a histogram can be invaluable but this doesn’t mean that you have to make a habit of glancing at histogram after each shot.
It should only be used to check the under and overtones in. Hopefully, after reading this article you will be able to understand how to use them and can apply them in real life.
I am sure that with practice you will be able to read them without a hitch and with their help create some extraordinary images.