A histogram is an incredibly powerful tool for taking better photos. And, although it may appear confusing and intimidating at first, it is much simpler than you imagine.
Most of us get scared when we see a histogram for the first time. What does such a complex graph mean? Well, believe it or not, it is pretty helpful and easy to understand, even for beginner photographers— and no, you don’t have to know anything fancy to use it to your advantage. What’s more, you can learn a lot just by looking at it.
That is why, in this article, we will talk about the histogram and how you can use it to become a better photographer. Consider this as a comprehensive guide to understanding histograms (with a few extra tips to get the best out of them!).
Let’s start with a quick definition:
What is a histogram in photography?
A histogram is a graphical representation of the distribution of brightness levels within a photo. In simple words, it displays how many pixels are in the dark and bright areas of an image, so it gives you an accurate overview of the exposure.
On its X-axis, the histogram shows the luminance range from left to right. The left side represents the shadows and blacks, while the right side depicts the highlights and whites. And, of course, in the middle section, you will find the mid-tones.
On the other hand, the Y-axis indicates the amount of data collected in each tone. For example, a high spike to the right of the graph means plenty of light and bright tones in an image.
So far it sounds easy, no?
Histograms can be found in most digital cameras and editing programs— for instance, if you edit in Lightroom, you have probably seen them in the upper right corner. They are almost everywhere, and that is because they can really help you improve your workflow as a photographer.
Not sure how that works? Let’s get into more details:
How to use the histogram in digital photography
Up to this point, we know histograms provide valuable information about your images. But how should we use that information?
Okay, let’s assume you just shot a beautiful scene. You checked the image, and you’re pretty happy with the result. Yet, when you open the file in Lightroom, you realize it doesn’t look much like what you saw on your camera. Sound familiar?
If the answer is yes, relax, we all have been there.
The truth is that no matter what camera you use, the results you will see on the screen are usually not accurate. That can be due to several factors, like screen brightness or excessive ambient light, for example.
On top of that, sometimes your camera might get confused when metering exposure, especially in high dynamic range scenes. All that leads to over-or underexposed images (along with countless deceptions).
Here is when a histogram comes in handy.
Remember that each side of the histogram represents different tone values. So, the shape of the histogram will tell you how much data is in the shadows, highlights, and mid-tones without looking at the image. Thus, you can detect and override any exposure mistakes you may have made.
In short, looking at the histogram is the easiest way to ensure you get the correct exposure. It takes only a few seconds and can help you avoid unnecessary headaches in post-processing.
Besides all that, the best use you can make of the histogram is to identify any loss of detail in the bright or dark tones, also known as clipping.
This brings us to the following point:
Shadow and highlight clipping
Clipping can occur in heavily overexposed or underexposed images. In simple terms, it indicates a loss of data when the sensor is unable to capture textures in the highlights or shadows.
It is pretty easy to spot clipping in the histogram. If you notice pixels touching either edge of the graph, it means there are clipped areas in your image. Of course, if it is to the left side, there is shadow clipping, but if it is to the right, it is highlight clipping. Unfortunately, in either case, it is not possible to recover details.
The best you can do to avoid completely white or black pixels is to check the histogram while you are shooting. By doing so, you can identify clipping very quickly and adjust your camera settings (shutter speed, ISO, and aperture) to get a new, well-exposed image. Some photographers even recommend using exposure compensation to lighten or darken your photos.
Besides the data displayed on the histogram, most digital cameras have a highlight alert that uses blinking spots to reveal blown-out areas. It is extremely useful to be more aware of which areas of the scene are compromised.
What to keep in mind
- Most cameras have an option to show the histogram alongside an image you have already captured. However, some models go further and feature a live histogram for shooting in Live View mode. Consult your camera manual to learn how to access the histogram and other functions.
- Always shoot RAW so you can recover more details later.
- Use manual mode to have absolute control over the exposure.
- High contrast scenes are challenging, and sometimes, depending on what you want to photograph, it may not be possible to get a correctly exposed image in a single take. You will have to do bracketing.
- If you want more detailed information, you can check the color histograms. They work just like a traditional histogram but are separated by RGB color channels. They are helpful to determine if you need to make any color adjustments.
Using the histogram in post-processing
In general, the histogram works as a guide to understand what you need to do to enhance your images in post-processing. Plus, it helps you keep track of the impact of your changes on the final result. For example, if you reduce the exposure in an overexposed image, you will notice that the right side of the histogram begins to fall and gather more data towards the center.
In other words, as you make any adjustments, the graph will change shape. This is quite useful to see how much information you can recover. But also (and most importantly), it allows you to avoid clipping.
To ensure you don’t have clipped areas, Lightroom has two arrows in the upper corners of the histogram that indicate areas of the image with texture loss. The left arrow shows shadow clipping in blue, and the right arrow shows highlight clipping in red.
Note that you can bring back some details in highlights and shadows to reduce the colored areas— especially if you are processing a RAW file. Yet, remember that you can’t retrieve data from pure white or black.
Now you see why the histogram is important, huh?
What should a perfect histogram look like?
There is no such thing as a perfect histogram. The appearance of the histogram will depend on the light and color properties of each scene. It is as if every image has its own DNA. However, an ideal histogram should have a balanced distribution of pixels across all areas of the graph, always without touching the extremes.
Some photographers might say that a proper histogram should be very rich in mid-tones. But, to be honest, in some cases, you will need more information towards a specific side of the graph to get the most out of a photo or to achieve a specific look. In the end, the only “rule” you should follow is to try to avoid clipping. That way, you will have more data to get creative in editing.
Histogram shapes and exposure
As we mentioned earlier, the shape of the histogram says a lot about how an image looks. So, here are some tips to help you read (and distinguish) some common histogram shapes:
Balanced exposure
This histogram contains the most information in the central area and few pixels towards the edges. As there is no clipping, you get enough textures in all tones.
Low key photography
Low key images are quite dark, so the histogram is oriented to the left side. It shows almost no information in the bright tones, and there may be some clipping towards the blacks.
High key photography
As you might expect, in this case, the histogram slants to the right side. It focuses on light tones and highlights and shows few dark tones. In this type of photography, you might have completely white pixels in bright areas like the sky, for example.
High contrast photos
In this case, you get plenty of information in the shadows and highlights but not in the mid-tones. The histogram usually has a U-shape, and there can be clipping at each edge.
Final words
To summarize, the histogram is a fundamental tool in digital photography, and it is much simpler than it first appears. Besides, you can save yourself a lot of trouble if you start shooting with it.
However, don’t forget that it is only a guide, not an unbreakable rule. Sometimes the shape of the histogram may indicate an excess of pixels to either side, but that doesn’t mean that the image is badly exposed. Every situation has different requirements, so don’t try to find the “perfect” histogram.
If you found this post helpful, feel free to share it! And, for more articles on photography and post-processing, check out our blog and our Photo Editing section.
