How to use histograms to take better pictures

When you take photos with a digital camera during daytime, it’s quite easy to estimate if you got your exposure right by taking a peek at the photo on the display on the back of the camera. You might think that the same it’s true for astro and night photography.

You take a photo, you have a look at it on the display, and you decide if you increase or decrease the exposure, ISO or aperture accordingly. But it’s not that easy for photographers out in the dark.

This article will look at how you can use you histogram to ensure you take better night photos with the correct exposure.

How to Use Histograms to Take Better Pictures

How to Use Histograms to Take Better Pictures

At night, your eyes adapt to the dark. Your pupils dilate and you actually perceive dim lights as being brighter than they are. That’s what happens when you look at your star photos on the display of your camera. You will have the tendency of misjudging their general appearance and you will perceive them as being brighter.

You go back home, download the photos to your computer, and suddenly they don’t appear as bright as they seemed the night before when you were reviewing them on location. They all look underexposed.

You adjust the exposure in your raw conversion software, and you do your best to recover some details in the shadows. Great, the photo looks as you intended. But now it’s a lot noisier, especially in the shadows. 

How to Use Histograms to Take Better Pictures

How can you get around this problem? It’s quite easy, actually. All you need to do is learn how to read your histogram properly, and you’ll find that it becomes very, very helpful for these kinds of scenarios.

What is a histogram in photography?

What’s a histogram? Technically speaking, a histogram is a graph that shows the distribution of some kind of numerical data. Imagine you have a wall divided into a certain number of squares and you repeatedly throw a ball at the wall. You count how many times the ball hit each square, and you graph those values.

Understanding Histograms in Photography

Histograms can be found in almost any modern image editing software. It is my guess that most current digital cameras, including some compacts, can display histograms as well – some even live as you shoot using your LCD screen. Such persistent inclusion would suggest that histograms are quite important.

Even so, many beginner photographers don’t seem to understand what they show. There is nothing wrong or shameful with that, as histograms may appear to be rather complex at first. Truthfully, they aren’t. In this article for beginners, I will try to teach you how to understand histogram.

Hopefully, by the end of this tutorial, you will learn to “read” them and see if they are useful to your photographic needs.

How to Use Histograms to Take Better Pictures

1) General Understanding

A histogram is a graphical representation of the tonal values of your image. In other words, it shows the amount of tones of particular brightness found in your photograph ranging from black (0% brightness) to white (100% brightness).

As shown in the image above, dark tones are displayed on the left side of the histogram. As you move rightward, tones get lighter. The middle portion of the histogram represents midtones, which are neither dark nor light. Vertical axis of a histogram displays the amount of tones of that particular lightness.

Histogram is exposure-dependent, but is also affected by tone curve and other settings.

2) Shadow and Highlight Clipping

How to Use Histograms to Take Better PicturesIf a certain portion of the histogram is “touching” either edge, it will indicate loss of detail, also called clipping. Highlight clipping (areas that are completely white and absent detail) occurs if the graph is touching the right side of histogram. Shadow clipping (areas that are completely black and absent detail) occurs if the graph is touching the left side of histogram. Either case can be often fixed by altering exposure settings. However, you must remember that it all depends on the scene. For example, if there’s sun in your image, it is only natural it will be so bright – completely white, in fact – that highlight clipping will occur.

Read our Mastering Lightroom series article “How to Use the Basic Panel” to learn how to fix exposure errors with RAW files. If you want to see whether there is any clipping as you photograph, engage histogram in your camera as you review images.

Each camera is different – Nikon cameras, for example, usually require you to press navigator keys up or down a couple of times in review mode before the correct settings come up. Many current DSLR cameras have live histograms that react to scene in real time.

To engage live histogram, you will need to use the LCD screen of your camera to photograph instead of optical viewfinder (Live View mode).

Should you notice any highlight or shadow clipping, alter your exposure accordingly: to save shadow detail, make images brighter by dialing in positive exposure compensation value (+0.3 or +0.

7, for example); to save highlight detail, make images darker by dialing negative exposure compensation value (-0.3 or -0.7, for example). Exposure compensation is usually set using “+/-” button on your camera.

If you prefer to shoot with manual settings, just change ISO, aperture or shutter speed accordingly. Read this article to learn about each of these three exposure settings.

3) Color Channels

Histograms usually display information for three primary colors – red, green and blue – and are known as RGB histograms. Such is the histogram shown above.

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You will notice that it consists of several diagrams marked with different colors. Three of these diagrams represent red, green and blue color channels accordingly. Gray diagram shows where all three channels overlap.

Yellow, cyan and magenta appear where two of the channels overlap.

4) Histogram and Exposure

What Is a Histogram, and How Can I Use It to Improve My Photos?

How to Use Histograms to Take Better Pictures

What’s with that weird graph with all the peaks and valleys? You’ve seen it when you open Photoshop or go to edit a camera raw file. But what is that weird thing called a histogram, and what does it mean?

The histogram is one of the most important and powerful tools for the digital imagemaker. And with a few moments reading, you’ll understand a few simple rules can make you a much more powerful image editor, as well as helping you shoot better photographs in the first place. So what are you waiting for? Read on!

What Do I Need to Know About Histograms?

How to Use Histograms to Take Better Pictures

While it may be intimidating looking, histograms are nothing really all that complex. What they represent are the distribution of tones throughout the image—a simple algebraic graph, when it all comes down to it.

The horizontal line represents the various values in your image. The leftmost side stands for pure blacks and dark shadows. The right side are your highlights, and pure whites. The values between the two fall much the way you might imagine them, with dark tones transitioning to midtones, then on unto brighter and brighter highlights.

The vertical axis represents how much of any corresponding value, whether light or dark, appears in the image. Higher peaks represent high concentrations of that particular value. In our example, we can see that the image this histogram came from has a high concentration of brightest highlights, with the concentration falling sharply, as we look to the slightly dimmer highlights.

Digital images don’t have unlimited tones. They only have 256  (that’s 8-bits of information). On a Histogram, black is 0 and white is 255. The dark tones all have low values and the bright tones have high values.

Okay, But What Do I Use It For?

How to use histograms to improve your photography

The histogram can be a big help in capturing great images. Here's a look at how and when you can reference it to make your photos better.

How to Use Histograms to Take Better Pictures


Ever watched a program on photography and heard commentators say a shot is “overexposed”? In a lot of instances, this assumption comes from just glancing at the image or the image's histogram. Here's the thing. The histogram in photography isn't quite the same as the one you use in your day-to-day marketing or forecasting presentation.

What is a histogram?

In photography, the histogram is used as a reference to help you understand the levels of light and color in a particular image. Analyzing image exposure is usually the primary reason for referencing a histogram.

The way a photograph's histogram is laid out, you can quickly grasp what's going on with the image's levels of black, shadows, midtones, general exposure, highlights, and white. If you look at the graph in Figure A, you'll see vertical lines that delineate these levels of a particular image.

As the white bar flows horizontally across the histogram, it lets you know that the image hits the marks for all the levels previously mentioned. The higher the peak, the more intense the particular level is in the image.

Figure A

What your cameras histogram means and how to use it

How to Use Histograms to Take Better Pictures

Have you ever wondered what that moving graph on your camera screen means? In the world of passionate photography full manual mode is the norm. As you move away from the “auto” mode in your camera the histogram is an important concept to familiarize yourself with, this article explains the histogram and how it can be used to improve your picture taking skills.

Histogram basics

A Histogram reveals the degree of image exposure showing proper exposure, it also shows if the lighting is flat or harsh and possible adjustments that will work best. Mastering the art of histogram photography greatly improves your skill not only as a photographer but also on the computer editing.

The histogram shows what the sensor is capable of detecting in the shot.

Histogram Geek Talk

A Histogram is a guide graph counting pixel distribution between black(located on the left end) and white(located on the right end). Darker images move an image to the leftwhile lighter images move it to the right.

 The height distribution of a graph depends on the number of bright pixels at a point. Color histograms for color photography have three separate (RGB channels) histograms which aid in determining correct exposure instantaneously.

For most shooting modes, the combined histogram is more than enough.

3 Seperate RGB histograms are great for advanced users but most situations the combined white graph is enough.

The horizontal axis

Represents images maximum potential tonal range (the region where most brightness values are present) or contrast (the measure of the difference in brightness between dark and light scenes).

A pixel in an image can be set from pure black (0) to pure white (255) depending on the level of brightness. The histogram horizontal axis documents levels of brightness and their distribution.

The vertical axis

Represents the number of pixels with each of the 255 values of brightness. The higher the line from the horizontal axis, the higher the number of pixels at that level of brightness.

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How to use a histogram to take a better photo
Look at the distribution of the histogram pixels though your eyes are the final determinant.

  • Use exposure compensation if most pixels are towards the left(darker) to increase exposure.
  • In an event of many pixels towards the right (lighter) use exposure compensation to reduce exposure.

Photos look best when the images are using the entire tonal range.
Pixels collected in one area in the histogram lack contrast between the darkest and brightest areas this can be edited in photo-editing software using commands that spread pixels to the entire tonal range.


A clipped pixel is a pixel showing at the extreme ends with levels beyond 0 and 255 hence tones are lost or “clipped” in the image. This means some parts of the photo are either too bright or too dark for the camera sensor to record any detail and would appear as a black or white area in the photo.

Avoid clipping by using the highlight warning setting during image composing. Check your camera setting for this warning function.

An example of clipping, in this photo the sky and some stones are too bright and can not be detected by the sensor so are just totally white and have no detail. The red indicates the areas that are clipped.

Adjust exposure to reduce clipping

The easy way to remove clipping is to adjust the exposure,

  • UNDEREXPOSURE Black Clipping – By increasing exposure, you shift the histogram to the right.
  • OVEREXPOSURE White Clipping – Decreasing exposure moves the histogram to the left.

Histogram: Discover How To Take Better Photos By Exposing To The Right

One of the tools most frequently overlooked by beginner and improving photographers is the histogram. The histogram is full of information that you can use to make your photographs more interesting to the viewer. In this article, you’ll discover how to make sense of your camera’s histogram and learn a great technique to take advantage of that information.

What Is A Histogram?

In photography, a histogram is a graph showing the distribution of light in an image. Most cameras are capable of displaying a histogram for each image stored on the camera’s memory card.

Some cameras even allow you to see a live histogram before you take the shot. The features vary from camera to camera, so consult your camera manual to find out how to display the histogram on your camera.

Your image is made up of millions of pixels, and every pixel has a value representing its color. The pixel’s brightness is derived from this value. A histogram shows you the number of pixels of each brightness in your image.

The scale along the bottom of the histogram goes from left to right, from 0% brightness (black) to 100% brightness (white). The taller the peak, the more pixels of that brightness there are in the image.

In the example histogram above, you can see that most of the pixels have a medium brightness (the mountain peak in the “Midtones” region). There are quite a lot of darker pixels (in the “Shadows” region), and very few brighter pixels in the “Highlights” region.

The image below has a histogram showing that most of the pixels are of medium brightness. There are two spikes in the histogram – the leftmost spike representing the darker regions of the image, and the rightmost spike representing the lighter regions – mainly the light-colored block pillars framing the shot.

The photo below has a histogram which shows how most of the image’s pixels are dark or pure black. There’s a tiny little spike to the extreme right, which relates to the bright white highlights at the top of the brightly lit windows on the top floor of the building.

Understand What Your Histogram Is Telling You

Now that you understand the basics of reading a histogram, let’s look at what it’s telling you about your image.

Most shots will contain a high number of pixels in the mid-tones.  These will cluster around the central area of the graph.  The higher the level of contrast in the image, the fewer pixels will appear in the middle.

  • In the example below, most of the pixels are at the dark end of the scale, with few bright pixels.
  • One of the most common uses of a histogram is to check for clipping.
  • Clipping is where a region of your photo is too dark (under-exposed) or too light (over-exposed) for the sensor to capture any detail in that region.
  • When clipping occurs at the right-hand side of the histogram, it’s called blowing out the highlights.

Clipping is difficult to spot without a histogram, but with a histogram, it’s very easy. You’ll see a large spike on the histogram graph right up against the left or right side of the graph.

No detail about your photo is captured beyond these extremes. Therefore, clipping is undesirable, and no amount of post-editing can recover detail that simply wasn’t captured by the camera.

Change How You Think About Exposure

An exposure is the combination of several camera settings found in the exposure triangle, but in simplistic terms, it’s how bright or dark the captured image is.

There is no single correct exposure for a scene but most photographers aim to capture the scene as they see it in front of them. While this seems sensible, it won’t always give you the best exposure if you want to achieve the best possible end result.

This naturalistic approach is great for snapshots and will work fine for photographers who don’t intend to post-process their images. But if you are willing to spend a little time working with the image in post-edit, using Lightroom or Photoshop, for example, then the technique you’re about to discover you can bring far better results.

So, let’s look at that technique now. It’s called Expose To The Right.

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What Is Exposing To The Right?

Photographers normally aim for a reasonably balanced histogram with the traditional bell-shaped curve, as shown below.

Expose to the right means exposing your image to push the peaks of the histogram as near to the right side of the graph as possible without clipping the highlights. Then, in your favorite photo editing suite, the shot is then processed to reduce the brightness and bring the final image back to your desired exposure.

The Benefits Of Exposing To The Right

Exposing to the right is beneficial because the further to the right you go, the more distinct tonal values there are. This produces a wider dynamic range. Dynamic range is the camera’s ability to capture both dark and light regions of the scene and everything in between.

You can easily check the claim that images exposed to the right contain more detail than those exposed to the left. Simply take two identical photos of the same scene, but, using your camera’s exposure compensation dial, drastically under-expose one of them.

Now, check the file sizes of both images. The properly exposed image will have a larger file size than the under-exposed image. This demonstrates how much more data your image holds when exposing to the right, rather than the left.

Bright light has more energy than low light, making it easier for the sensor to capture it. This results in a higher signal-to-noise ratio. This is because bright light generates a strong electrical signal in the camera’s sensor. This overpowers the relatively weak electrical signals created by random electronic interference found in all electronic devices.

Exposing to the right, but being sure not to clip the highlights, results in images which are less noisy, have greater dynamic range, a higher signal-to-noise ratio, and better colors.

Choose The Right File Format

When your camera takes a photo, it saves it as a file on your camera’s memory card. The two most common image file formats are JPEG and RAW.

RAW is a lossless file format which keeps all of the information captured by your sensor. It’s an exact copy of what the sensor captured, without any image adjustments or enhancements.

By comparison, the JPEG format compresses the sensor information, throwing away detail which you can never get back. This keeps the image file size small but at the expense of image quality.

As the price of memory and storage falls constantly, image file sizes are less important. So, always shoot RAW if your camera allows it.

Brighten Your Image The Right Way

Exposing to the right involves making the image brighter. There are several ways to do this in-camera. Refer to the exposure triangle to discover how to adjust aperture, shutter speed, and ISO for a brighter image. Avoid increasing the ISO value, as the increased grain will counteract any benefits you’ll get from exposing to the right.

Keep the ISO as low as it will go. Only make changes to aperture or shutter speed. Be aware that changes to shutter speed might introduce camera shake. If you choose to use a slower shutter speed, consider using a tripod and timer for best results.

A quick way to brighten the image is to use your camera’s exposure compensation dial. This allows you to increase or decrease the exposure in small increments.

Turn the dial to a positive number (e.g. +1/3, +1/5, +1 or +2) and take a test shot. Then check the histogram for the photo you just took. If the histogram is stacked hard up against the right-hand side of the graph, reduce the exposure compensation, and take another test shot.

Use Bracketing To Speed Up Your Workflow

In-camera histograms use a JPEG version of the image, even if you’re shooting in RAW only. Sometimes this results in the histogram incorrectly warning you about clipping. Despite this, the information lost in the JPEG version is potentially still available in the RAW file. It’s a small point, but a reminder that the histogram isn’t the whole story.

Exposure bracketing can help with this problem. It allows you to take multiple photos at different exposures. One normally exposed photo, one over-exposed photo, and one underexposed.

The three photos below were created automatically with exposure bracketing. They include a normally exposed image, an over-exposed image, and an under-exposed image.

Using exposure bracketing increases the chances of getting the best exposure, even if the histogram is slightly misleading.


A histogram is a useful tool for understanding and accurately exposing your images.  Correctly reading the histogram lets you make informed decisions about adjusting the exposure while you’re still out in the field. Once you get home, it’s too late!

Exposing to the right, but being sure not to clip the highlights, results in better quality images. Your images will be less “noisy”, have greater dynamic range, a higher signal-to-noise ratio, and better colors.

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