The histogram in photography is a fundamental tool for understanding whether you’re capturing a photo with the correct exposure or editing an image properly. Checking the histogram is crucial both during the shooting phase on your camera and during the editing phase on your monitor.
During my Photography Tours around the World, I’ve noticed that many students don’t check their histogram, and some don’t even know how to read it. Ignoring the histogram is a big mistake.
Learning to read and adjust histograms allows you to improve your photography skills, capture more details, and achieve better results during editing. By balancing exposure and avoiding clipping, you can create stunning, high-quality images that stand out!
With that said, welcome to this guide on how to read a histogram, which will help make you a better photographer! In this article, we’ll explore how to understand a histogram to achieve proper photographic exposure. We’ll look at how to use a histogram in the most common photography scenarios and examine some examples of photos with histograms to show how reading the histogram relates to the final image!
What is a histogram in photography?
The histogram is simply a two-dimensional representation of a photograph in the form of a graph. You can see the color channel histograms, which we’ll cover later in this guide, but the most important histogram for evaluating proper exposure is the brightness histogram.
A histogram is a graphical representation of the tonal values in an image. The purpose of a histogram is to give photographers a more accurate representation of brightness values than even a trained eye can perceive just by looking at the image.
The sections of a histogram along the X-axis represent the range of values from pure black to pure white. On the vertical Y-axis, we see the number of pixels that recorded each tonal value. Together, these elements create the graphical representation of the histogram!
How to Read a Histogram in Photography
Mastering histogram reading is a crucial skill for achieving perfect exposure in photography!
The graph represents the range of tones the sensor can capture, from the brightest whites to the darkest blacks. The left side represents black (shadows), the right side represents white (highlights), and the center shows midtones.
The peaks in the graph indicate the number of pixels at each brightness level. For example, a high peak in the center of the graph means the image contains a large number of pixels with medium brightness (midtones). If the peak is on the left side of the histogram, it indicates a lot of information in the dark tones of the image. Conversely, if the peak is on the right side, it means there’s a lot of information in the light tones of the image.
When looking at a photograph, it’s hard to determine exactly where all the variations of light and dark areas are and how much space each one takes up. By observing the histogram, these aspects become much clearer.
Here’s a simplified explanation: the pixels on the left side of the graph correspond to 0% brightness, while those on the right side represent 100% brightness. In the middle, you’ll find the midtones. So, moving from left to right, we have the shadows (blacks), midtones, and highlights (whites).
Let’s apply the histogram to a photo:
- A dark (underexposed) photo will have a histogram shifted to the left, indicating more information in the blacks and shadows.
- A bright (overexposed) photo will have a histogram shifted to the right, showing more information in the whites and highlights
This information is extremely important for photographers because it allows them to immediately determine if the photo is properly exposed or if adjustments are needed by balancing the exposure triangle.
What is the Perfect Histogram in Photography?
There’s no perfect histogram, it really depends on your creative style. For example, if you want a dark image, it’s normal for the histogram to be pushed to the left, with very little information in the white areas.
However, an “ideal histogram” usually shows a good balance of pixels across the graph, with a peak in the middle (the midtones). The edges should not touch the far left (pure black) or far right (pure white), meaning no details are lost in the darkest or brightest parts of the image.
Here’s an example of an ideal histogram in photography:
Translating this graph means that the photo has a correct exposure, with a good amount of information spread across all tones and no clipped shadows or highlights.
Remember, a photo with an ideal histogram like this gives you more flexibility during post-processing, as it has more information to adjust without losing quality.
How to use the Histogram in Camera
Don’t trust the LCD screen on your camera to judge exposure, because it can be misleading.
Your eyes can easily be tricked, and the screen’s brightness setting affects what you see. This is especially true at night, when the image on the screen can look much brighter than it really is because it’s much lighter than the dark surroundings.
Make sure not to make this mistake but always check your photos by looking at the histogram!
You can see the histogram in two ways on your camera: the live histogram, which is available on most modern cameras, or the post-shot histogram in the image preview.
By reading the histogram, you can quickly tell if your camera settings are right and if your exposure triangle is balanced, or if you need to adjust it to get the right exposure with good detail in all areas, without losing detail in the shadows or highlights.
Photography Tip 1: Turn on the histogram display on your LCD screen so you can quickly check if your image is properly exposed right after you take the shot. On mirrorless cameras, it’s even easier because you can see the histogram in the electronic viewfinder before you even take the picture!
Photography Tip 2: In night photography, when shooting things like the Milky Way or the Northern Lights, you might use techniques like double exposure (taking two photos with different exposures, one for the landscape and one for the sky, to get the right exposure for both). It’s normal for the histogram to shift left, touching the blacks (on the left side of the graph) for the sky photo, and shift right, touching the whites (on the right side of the graph) for the landscape photo. Don’t worry, though! When you blend the two exposures during editing, you’ll get a perfect histogram.
What is Histogram Clipping?
With an ideal histogram, the photo won’t have any lost details in the shadows or highlights.
If the photo is too dark, the graph will shift too far to the left and touch the left side of the histogram. This is called “clipping.” The same thing happens if the image is too bright and the graph touches the right side.
Here’s what clipping means:
Clipping happens when an image is either too bright or too dark, causing parts of the photo to be completely black or completely white. Pure black is 0% brightness, and pure white is 100%. In simple terms, clipping occurs when the graph hits one of the extremes of the histogram, leading to shadows that are too dark or highlights that are too bright. If you see clipping, you should fix the exposure while shooting, or the image might not be fixable later in editing.
How to spot clipping on the histogram?
Clipping Shadows (Underexposure Histogram)
Clipping shadows means the image is too dark.
You’ll see the graph shift to the left, with a high peak on the left side, and some of the image’s details touching the left edge of the histogram. This shows that we’ve lost details in the dark areas (shadows). Even if you try to brighten the shadows in Lightroom or Camera Raw, you’ll just get noise without recovering any real detail because the camera didn’t capture it during the shot due to underexposure.
- The image is too dark
- Loss of detail in the shadows
- More digital and color noise in post-processing when trying to fix the exposure
- The photo lacks midtones and highlights
Let’s see what shadow clipping means on the histogram in Lightroom
By clicking on the top-left corner of the histogram, you can spot areas in the image that are too dark. The blue areas show parts of the image with no detail because the shadows are too dark, and there’s no information in those areas. Looking at the histogram, the blue parts of the photo are where the graph touches the left edge.
You can try to fix this by increasing the exposure, lifting the shadows, and bringing back details in post-processing. But depending on your camera and file type, this might cause a lot of digital and color noise.
Photography Tips and Tricks: If this happens, in post-processing, slightly increase the exposure and blacks first, then adjust the shadows. You’ll notice less digital noise will appear.
In general, it’s best to avoid clipping. The best way to prevent it is to get the exposure right when taking the photo, using a balanced exposure triangle.
Clipping Highlights (Overexposure Histogram)
Clipping highlights means the image is too bright.
You’ll see the graph shift to the right (with a high peak on the right side), and some details in the image touch the right edge of the histogram. This means we’ve lost information in the bright areas. (Even if you try to reduce the brightness in Lightroom or Camera Raw, you won’t recover the burned-out highlights because the camera didn’t capture them due to overexposure).
- The image is too bright
- Loss of detail in the highlights
- Burned-out areas in the bright spots
- The photo lacks midtones and shadows
Let’s see what clipping highlights mean on the histogram in Camera Raw
By clicking on the top-right corner of the histogram, you can find areas in the image that are too bright. The red areas show parts where there are no details because the highlights are too bright. Looking at the histogram, the red parts of the image show where the graph touches the right side.
You can try reducing the exposure and lowering the brightness in post-processing, but if the image is too bright, you won’t be able to recover the lost details because the highlights are “burned out” and have no information.
Photography tips and tricks: If you’re shooting a scene with a big contrast between the landscape and the sky (like dark mountains in shadow and a bright sky), and you want to take just one shot without using HDR (multiple exposures), try to balance the exposure triangle to get the best histogram. However, the camera will likely struggle to capture the perfect exposure. My advice is to slightly underexpose, which will make the histogram lean a bit to the left. It’s better to lose some details in the shadows than to have burned highlights, which can’t be fixed in post-processing.
The best way to get an ideal histogram and a balanced exposure in high contrast situations is to take at least two different exposures: one for the sky and one for the landscape. This way, you can combine them later for a perfect result. This is called exposure bracketing.
Color Channels in the Histogram
Until now, we’ve talked about the brightness histogram, which shows the distribution of light and dark tones in an image.
Now let’s look at another important aspect of the histogram in photography: the graph for each of the three primary color channels: Red, Green, and Blue.
What is the RGB Histogram?
The RGB histogram shows the range of tones for each of the three RGB channels and represents the distribution of tones within a single color. Checking this histogram is essential to understand if the colors are properly exposed or if they are underexposed or overexposed.
Checking the RGB histogram is especially useful when photographing a subject with a dominant color. Since the luminosity histogram shows the overall values across all three channels, it might not highlight that your monochrome subject has clipping, meaning some subtle color variations are lost.
To simplify, if you’re photographing a night sky during strong Northern Lights activity, checking the luminosity histogram might show that your image is properly exposed overall, with good detail in both shadows and highlights. However, since green is the dominant color in the scene, you might be losing some green color information. This is why it’s important to also check the RGB histogram, specifically the green channel.
For example, if the Northern Lights are strong, you might see a peak in the green channel of the RGB histogram. This indicates overexposure, meaning you’ve lost some detail in the brighter areas of the Aurora.
We wouldn’t have noticed this if we were only looking at the luminosity histogram. But by also referring to the RGB histogram, we can quickly identify and correct these issues.
If you’re still feeling a bit confused about how to adjust the shape of an histogram, my “Exposure Triangle in Photography – A Beginner’s Guide” explains every aspect of controlling light exposure!
How to use Histogram in Lightroom and Camera Raw
Welcome to the second stage of using the histogram: post-processing.
Reading a histogram in Lightroom, Camera Raw, or Photoshop serves as a valuable guide during the editing process. It provides a clear overview of the adjustments that can and should be made to enhance the image effectively.
Before you start editing, make sure to check the histogram and keep an eye on it as you make changes. This helps you stay on the right track and avoid accidentally damaging the image, like causing clipping in the shadows or highlights. The histogram you see after editing will be different from the original, but it should still be a balanced one.
Using software like Lightroom and Camera Raw, you can fix the histogram if the one from your initial shot wasn’t ideal, and improve it as much as you can.
How to correct the histogram?
For example, if your histogram has a peak too far to the left, you can correct it by increasing the exposure, blacks, and shadows. On the other hand, if the peak is too far to the right, you can reduce the highlights and exposure. Also, by checking the RGB histogram, if you notice a color is too bright, you can go to that color’s brightness and decrease it.
Photography Tip 1: If you need to correct the histogram during post-processing, remember to do it before starting your workflow. When your histogram is closer to an ideal histogram, that’s when you can fully unleash your creativity.
Photography Tip 2: Remember, it’s always better to get an ideal histogram while shooting so you don’t risk degrading the image’s pixels in post-processing (for example, by excessively brightening shadows because the photo is underexposed). So, do your best to get an ideal histogram while shooting.
Benefits of Understanding Photography Histogram
Master the Art of Reading Histograms: Essential Tips for Photographers
Learning to read and use histograms is a must-have skill for photographers because this simple graph contains crucial information that influences how you capture and edit every scene.
What Information Does a Histogram Provide?
- Understand the Exposure-Image Relationship: Histograms help you see how exposure impacts your final image.
- Spot Clipping Easily: Histograms reveal tonal clipping in shadows or highlights that may not be visible on your camera’s LCD, which can sometimes deceive your eyes.
- Tonal Value Accuracy: Histograms accurately represent an image’s tonal range, showing what the naked eye might miss.
- Achieve Perfect Exposure In-Camera: Analyzing the histogram helps you set the correct exposure while shooting.
- Guide Post-Processing Adjustments: Using the histogram during post-processing helps guide the adjustments needed to improve your image.
- Better File Quality: Capturing images with a balanced histogram improves file quality and gives you more flexibility in editing.
- Create Balanced Images: Understanding the histogram helps you improve image quality and achieve more flexible post-production.
Histogram examples in Photography
Understanding Histograms: Examples for Better Photography
Here are some examples of histograms side by side to help you better understand how to read and interpret them!
Underexposed Histogram Example
This histogram shows completely clipped blacks, resulting in lost details. Attempting to fix this in post-processing would introduce significant digital noise and degrade image quality.
Example of a Left-exposed Histogram
The histogram is shifted to the left, meaning the image is slightly underexposed, but it still has recoverable shadow details. It’s easier to edit than a fully underexposed image.
Properly Exposed Histogram Example
A perfectly balanced histogram displays a full range of midtones without any clipping in the highlights or shadows. This represents an ideally exposed image with all details intact.
Example of a Right-exposed Histogram
This is a typical result when using “ETTR” (Expose to the Right). By carefully recovering highlights in post-processing, you can achieve a final image with an excellent dynamic range, depending on your camera’s capabilities.
Overexposed Histogram Example
An overexposed histogram shows clipped highlights, where certain pixels reach 100% brightness. This results in irreversible loss of detail in the brightest areas of the image.
RGB Histogram Example
Unlike a standard histogram that represents all colors combined, an RGB histogram separates exposure data for individual color channels: Red, Green, and Blue. This is useful for analyzing and correcting color clipping in images with dominant hues.
Conclusion
If you’ve made it this far, you now have a solid understanding of what a histogram is and how to use it effectively in photography.
As we’ve learned, it’s important to check the histogram in two stages: when you’re shooting and during post-processing.
Your camera has two types of histograms that are key to review during shooting. They help you see if your image is properly exposed or if you need to make adjustments for a balanced exposure. These are the luminance histogram and the RGB histogram.
- Luminance Histogram: This shows the brightness levels in your image.
- RGB Histogram: This shows how the primary colors (Red, Green, and Blue) are distributed in your image.
By checking these two histograms, you can adjust your camera settings to get the best results. By learning how to read and use histograms, you’ll create better images, improve photo quality, and enjoy greater flexibility during editing.
If you’re still wondering why histograms are useful, try taking a few test shots with obvious exposure problems. Then compare the histogram readings in your camera or Lightroom with the tips shared here. It’s a great way to get a better understanding of how histograms work!
I invite you to join one of our Photography Tours around the world, take your photography skills to the next level, and capture memories that will last a lifetime!
