The histogram is a tool that many beginning photographers fear to learn. At first it looks confusing and probably makes little sense, resulting in many photographers avoiding it. However, you need to understand the histogram in order to take your photography to the next level – that’s what you want, right?

I also avoided the histogram for a long time in the beginning. But then I learned how powerful it is and that it would improve my understanding of photography.

Before we start, I want to point out that a good photo doesn’t need to have a perfect histogram. This might sound a little confusing but by the end of the article, you’ll understand why.

What is a histogram?

So, what IS a histogram?

The easiest way to explain the histogram is to say it’s a graphical representation of an image’s light levels. The shadows (blacks) are represented on the left side of the graph – pixels leaning all the way to the left are equal to 0% brightness. Highlights (whites) are represented on the right side. Pixels leaning all the way to the right are 100% bright. In between these two you have the midtones, which are neither completely black or white.

The vertical axis of the histogram represents the number of pixels that are in that particular tone.

Histogram in Photography

The histogram is different for every picture but when you know how to read it, you’re able to recognize if an image is too bright or too dark or have areas that are 100% black or white (called clipping).

More detailed…

If you found the description above confusing, skip this part and continue reading from the next heading but I know that many of you are interested in a more detailed and tech-savvy explanation of how a histogram work:

Let’s use the histogram on the back of your camera as an example. As you remember from above, the histogram on the back of your camera is a representation of the light levels in the image you’re viewing. The camera creates this graph by converting the image to greyscale and divides it into 256 levels of brightness: starting at 0 (representing pure black) and up to 256 (representing pure white). The camera then analyzes each pixel of the image and plots its brightness information into what becomes the histogram chart.

The height of the histogram tells how many pixels there are of that specific tone.

Clipping shadows or highlights

When the histogram chart is leaning all the way to the left or right, it means that you have tones that are completely white or black. This is referred to as clipping. The more pixels leaning to the furthest side, the more of the image is over- or underexposed.

Let’s look closer at what that means:

Underexposing & clipping shadows

The image below is what we define as underexposed. In other words, it is darker than it should be, resulting in lots of lost details in the shadows.

When this is the case, you need to either lengthen your shutter speed, increase the ISO or use a wider aperture.

Understanding the Histogram

Looking at the histogram above, you’ll see that the majority of the pixels are leaning towards the furthest left. This means that the majority of the image is underexposed (too dark) and parts of the image are pure black.

Notice that there aren’t many pixels towards the right side. This means there are few bright pixels in the image.

Now, look at the image itself. Are you able to see how the chart represents the image? The majority of the image is near black while only the sky and some details in the landscape are represented as highlights or midtones.

The peak all the way to the left in the histogram represents the area which has 0% brightness, pure black. As I’ve mentioned, when pixels touch the sides of the histogram, it means that part of the image is clipped.

Let’s quickly jump into Lightroom to see what this means:

Lightroom Histogram

By clicking the arrow in the upper left corner of the Histogram (Show Shadow Clipping), places that are pure black are revealed with a bright blue color. In general, you want to avoid having any areas like this but, depending on your camera and if you’re photographing in RAW, you might be able to bring back some detail in Lightroom or another RAW processing software.

The best way to avoid clipping is by increasing your exposure in-camera before taking the next shot. Do this by either increasing the shutter speed, ISO or opening your aperture. You can learn more about setting the correct camera settings in our Fundamental Series.

Overexposing & clipping highlights

The opposite of an underexposed image and clipping shadows is an overexposed image that’s clipping the highlights. As you might understand by now, that means there are areas in the image which are pure white (100% bright).

Below is another shot from the same location as the previous but this one is too bright, i.e. overexposed.

Understanding the Histogram
Overexposed Histogram

Unlike the histogram from the underexposed image, the histogram representing the image above is leaning towards the right. According to the histogram, the image contains only highlights and some midtones but no true blacks, which is accurate if we compare with the actual photograph.

So, how do we know by looking at the histogram that the image is overall too bright? Because the pixels are mostly on the right side of the chart.

Notice that there’s a “tower” at the right edge of the chart. This represents the sky which is clipped and overexposed.

Let’s jump back to Lightroom to see which parts are pure white:

Overexposed in Lightroom

Clicking on the arrow in the upper right of the histogram reveals the pure white areas of your image. In this example, it’s more or less the entire sky. Notice that the sky in the left corner isn’t marked red, though, which means that area is not pure white. Even though it might look like it is pure white, it isn’t bright enough to be considered 100% bright.

What’s the perfect histogram?

Achieving the “perfect histogram” is something photographers often work towards. What the “perfect histogram” looks like depends on the image you wish to capture but an ideal histogram has pixels that are spread throughout the axes with a lot of midtones. This is considered to be an ideal histogram:

The Ideal Histogram
The Ideal Histogram

Most of the information in the histogram above is gathered in the mid-range. Notice that there are no pixels touching either side. Do you remember what that means? Yes, that means there are no clipped highlights or shadows.

A histogram such as the one above allows you to be more flexible when processing the image. Since you have so much information captured in the image file, you can increase/decrease shadows and highlights a lot before seeing a decrease in the quality.

The main issue with underexposing an image (when it’s too dark and the histogram is leaning towards the left) is that fewer details are stored in the darker areas. This means that increasing the shadows’ exposure will decrease the image quality faster.

How to use the histogram

Most DSLRs have an option that shows you the histogram of an image after you’ve captured it. Use this to your advantage. Look at the histogram after each shot to see exactly how the image looks in terms of luminosity.

Be aware that the camera’s LDC doesn’t always accurately represent the image; the histogram might tell a different story. Adjust your settings according to the histogram rather than the image preview.

More expensive DSLRs have the option to view the histogram live. This is a function I rely heavily on and even though using Live View and live histogram drains the battery, I rarely photograph without using it. I would rather bring extra batteries than not knowing whether the image is properly exposed.

It took me a long time to grasp the importance of understanding the histogram but once I learned how to read it, I realized how useful it is.

Why understanding the histogram is important

By now you’ve hopefully got a better understanding of how the histogram works but why is it so important to understand? Why do I believe that understanding the histogram will take your photography to the next level?

Most of these questions have been answered throughout the article but let me summarise for you:

  • The histogram is an accurate representation of an images luminosity/brightness
  • It tells you if an image is too dark or too bright
  • Understanding the histogram will help you capture more balanced images

I briefly mentioned this before but the image preview on the back of your camera’s LCD isn’t always accurate. Sometimes the image looks good on the camera but once you import it to a computer, you learn that it’s too dark or too bright. This can be because the brightness of the screen is wrong or maybe the sun was reflecting on the screen making it hard to see. Had you instead taken 10 seconds to view the histogram as well, you would have quickly learned that the image wasn’t of the same brightness as the preview suggested.

I challenge you to actively use the histogram during the next few days and adjust the shutter speed, ISO or aperture to see how it changes as the image gets brighter or darker.

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