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Of all the tools and features available in digital photography, the histogram might just be the most useful one. Yes, even more than the preview button on your camera. Its job is to gather all the data stored by your camera’s software and put it into a nice, simple graph you can easily understand. Because all image software programs speak the same language, the photography histogram allows you to understand exactly how your images look from the moment you press the shutter until you publish them on your photography website.

But despite its clear importance across all the creative process, many beginner and self-taught photographers don’t take full advantage of all of the histogram’s capabilities. If you struggle with understanding what all those spikes mean, or don’t know how to actually use it, fear not. By the end of this article you’ll have learnt everything there is to know about how to read and use a camera histogram.

What is a histogram?

In photography, a histogram is a mathematical representation of the tonal range of a picture. In other words, it shows the distribution of the total number of tones in an image, from its darkest to its brightest area.

Without going too much into the technical details, here’s a brief breakdown of how the photography histogram works: There are 256 different values of brightness recorded in an image, ranging from absolute black (0) to pure white (255). Each pixel is assigned a value in this scale, and the results are displayed based on the proportion of pixels dedicated to each tone.

The primary use of the histogram is to make sure an image has been properly exposed. Knowing how to read it will help you make the most out of every scene, as well as bringing it as close to your vision as possible during post-processing. Essentially, it will help you become a better photographer both behind the camera and the computer screen. This is why it’s considered one of the main photography skills for any genre and style.

The histogram maps the brightness of every pixel in the image

How to read a histogram

The easiest way to understand how the histogram works is to see it as a bar chart. The horizontal axis has 256 labels, representing each of the brightness values of the image. The vertical axis determines how many pixels are found at each particular tone. From left to right, the chart is divided into five sections: blacks, shadows, midtones, highlights, and whites.

If you’re familiar with editing software, you’re probably used to these photography terms. Basically, the left side represents dark tones, the right side belongs to the bright areas, and there is a nice middle ground in between them for tones which are neither too dark nor too bright. The best way to get comfortable with what each of these labels represent is to open any editing software and see how modifying them affects the image.

The photography histogram is divided into five sections

Interpreting the image histogram

Maybe even more important than knowing how to read a histogram is being able to interpret what it means. This is essential to make sure the picture you capture is as close to your vision as possible, which will save you a lot of time and headaches during the rest of the creative process.

Here are the four main things you should always look for in an image histogram:

Exposure

The most important function of a histogram is assisting the photographer in finding the correct exposure for each picture. Some believe that you should always aim for a bell-shaped histogram: dominated by midtones, with some highlights and shadows. In fact, this is most likely the type of photography histogram you’d get if you shot all your images in automatic. But the truth is, the shape you get is completely dependent on your photography style and the scene you’re capturing.

The one thing you should always keep in mind is to stay away from both extremes of your image histogram. As you’ll learn about in a few lines, spikes on the far left or right are something you really should stay away from.

Take a look at this image, which has been properly exposed across all tonal range. Afterwards, scroll down to see how the histogram would look if the same scene had been over or under exposed.

A correct exposure records information from all areas of the image

On an overexposed photo, you’ll see a spike on the extreme right side of the histogram. This means that some areas of your image have a brightness level of 100%, and so there are just simply pure white pixels.

An overexposed photo shows a spike on the right side of the histogram

On the other hand, the histogram of an underexposed picture will have a level spike on the extreme left side. Part of the pixels have a brightness level of 0%, meaning they are pure black and show no details.

An underexposed photo shows a spike on the left side of the histogram

Clipping

When an image is over or underexposed, it suffers a loss of information in certain areas. This data damage is known as “clipping”. Needless to say, this is something you want to avoid at all times. Even if you decide to intentionally use clipping in your creative photography ideas, you should do so in post-processing rather than on camera.

The reason behind this is that there is no way to recover information that has not been captured in the first place. So even if you’re shooting in RAW, there will be part of your image you won’t be able to work with. This will significantly limit your creative options and might even put your final vision in jeopardy.

Clipping is displayed in the histogram as a spike on either side of the graph, at the absolute black or white position. Most editing software and cameras include the option to highlight the zones in which these spikes are recorded, allowing you to assess the damage and reduce the impact on the final image.

These two examples show how underexposed and overexposed histograms look in Photoshop:

It's important to avoid spikes on both let and right side of the histogram

Lighting

The style of lighting you choose for your photos will have a direct impact in how the histogram is distributed. This is especially important to take into account when you want to modify light to fit your concept, such as for fine art photography.

As you can see in the examples below, the histogram of a properly exposed image can actually be heavily focused towards one of the sides. In low-key lighting, most tones occur within the shadows area. While in high-key lighting, the majority of the information is found within the highlights area.

High-key lighting pictures contain mostly highlights

Low-key lighting pictures contain mostly shadows

Contrast

In addition to exposure and lighting style, the histogram also describes the contrast level of an image. Contrast is determined by the tonal difference between its light and dark areas, and is highly dependent on the lighting conditions of the scene. For example, a photo taken in a sunny afternoon will have a significantly higher contrast than one taken during the photography golden hour.

Take a look at the following images. High contrast images result in broad histograms, while low contrast ones produce a much narrower graph. The outcome you’re aiming for will completely depend on your artistic choice. However, it’s important to keep this in mind during your process, as low contrast pictures can be perceived as dull, while high contrast ones create noticeable textures.

An image with strong contrast results in a broad histogram

A narrow histogram represents low contrast

The color histogram

Also known as RGB histogram, this alternative view of the histogram displays the tonal values of the primary colors. In other words, it creates an individual histogram for each red, green, and blue. These graphs can either be seen individually or stacked in a single space. A single RGB histogram shows the values of each channel as well as a gray highlight for the values where all colors are present.

Many photographers consider the RGB histogram much more valuable than its luminosity counterpart. The most notable benefit is that it offers more information. Because the general histogram is generated based on the average levels of each tone, it’s possible to miss exposure issues on specific channels.

Imagine you are photographing the treetops of a forest in the middle of the afternoon. You set your exposure based on what the trees need, ignoring the brightness of the sky areas in the image. After checking the histogram, you see nothing seems out of place and continue with your photo adventure.

If only you had taken a moment to double check the RGB histogram, you’d have realized that the blue channel was completely overexposed and then had the opportunity to capture the same shot after modifying your settings accordingly.

Most cameras and editing programs allow users to see either version of the histogram. For example, Lightroom displays the RGB histogram as the main option and the average luminosity on its tone curve tool. In Photoshop, you can select your preferred version by going to Window > Histogram. As for free photo editing software options, the vast majority of them include at least one type of histogram among their tools.

This is how the RGB histogram looks in Photoshop

The camera histogram

One of the biggest advantages of digital photography is being able to see the results immediately after shooting an image. This is especially valuable for beginners who are still working on mastering their knowledge of the exposure triangle, but also for professionals shooting under tough conditions.

However, many photographers base their decisions on the field solely on the image preview the camera offers. While this is a great option to check your focus and composition, it should not be a deciding factor on your camera settings. After all, the results you see on the camera’s LCD screen are completely dependent on its brightness settings and the lighting conditions under which you’re looking at it.

In order to make sure you’re shooting with a correct exposure, use the histogram feature within the camera. Many brands offer the option to visualize both the luminosity and color histograms, as well as a clipping highlight that will let you know which areas of your image are not properly exposed.

Because an image histogram is purely a mathematical representation, its values will stay consistent across any device. This makes it an incredibly reliable tool across the entire photography creation process.

Let’s sum things up

• Right after the basic camera settings, how to read a histogram is one of the first things new photographers learn. Being able to do so will give you much more control over how your images look and allow you to take your editing skills to the next level.
  

• In a nutshell, the histogram maps the brightness of every pixel in an image and puts the data in a bar chart that goes from absolute black (0% brightness) on the left side, to pure white (100% brightness) on the bright side. The way in which the image histogram is shaped and distributed lets you know many things about a picture, such as its luminance, type of lighting, and contrast.
  

• The isn’t a ‘correct’ distribution you should aim for, other than avoiding spikes on the extreme left or right side of the histogram. This means that the image was either over or underexposed, and therefore some areas have no actual information about the scene.
  

• Above all, the most important thing to remember about the photography histogram, is that it’s meant to complement your skills, not limit them. Being able to read and comprehend the information it displays will improve your knowledge and understanding of how light behaves and how to mold it to your liking both in camera and in post-processing.
  

• The histogram should be seen as a guideline, rather than an actual rule. Use it to make sure you capture as much information as possible of every scene, but don’t be afraid to break some rules en route to your vision. After all, photography is meant to capture your unique vision of the world, not a mathematically correct visual description of it.

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