Bite Size Tips: How to Get the Perfect Exposure with a Histogram

The histogram is one of the most useful tools in the camera that helps to evaluate proper exposure and is also one of the least understood and used tools. If you want to become a better photographer, you need to understand how the histogram works and use it to nail exposures. It is the best way to make sure that you are properly exposing the frame you are photographing.

Note to remember: Nothing can evaluate exposure better than your eyes, but then there are situations when the light is harsh or very limited, that you need some help evaluating exposure and you can use the histogram as a guide.

So, what is a histogram? A  histogram is a graphical representation of the tonal values in a photograph (between 0 and 255) and is an accurate guide to exposure.

And what does it represent? It is a curve that represents tones and pixels in the image. The x-axis represents the tonal variations from black to white; that is, blacks, shadows, midtones, highlights and whites. The y-axis represents the amount of pixels for a given tonal value or range.

Here is a representation of the information you find on the histogram. Included here is only the luminosity histogram, but it is good to look at the RGB colours which we will look at in a different article.

Histogram Illustration created for Light Stalking

In order to have a good variation of all the tones, the histogram needs to be a curve (almost bell-shaped, depending or an even spread of medium humps) touching almost all areas but not the very ends (which are the blacks and whites). The ends would mean a loss of pixel information, like complete darkness or completely blown out highlights and this is called clipping.

Here are some examples to see how the histogram looks when there are whites and blacks in the frame:

Since there are blown out highlights in this image, you can see that there is a peak in the histogram towards the right end, which indicates highlights clipping

Image by Erik Scheel

As you can see in this image, there are some areas that are dark (completely black), as a result of which, the histogram shows peaks at the far left. In this image, this is how the photographer wanted it, as it is a silhouette. There is nothing to worry too much about.

Image by Pete Linforth

Note: If your scene has predominantly a lot of black areas, then you should not worry about the histogram hitting the left end of the graph and similarly if there are a lot of whites in the frame, the histogram may hit the right end of the graph.

Also, for clarification and ease of understanding, included here is another example, where you can see how the histogram varies when the image is correctly exposed, underexposed and overexposed. Using a single image for comparison while demonstration always helps!

The image is correctly exposed. You can see that the tonal values vary from shadows to a bit in the white region because there are some white clouds and snow.


Underexposed image – You can see that the histogram has shifted heavily towards the darker (shadows) end.


Overexposed image – The histogram has shifted towards the whiter end with a lot of highlights clipping

Image by Ambir Tolang

So how do you go about getting the exposure right?

  • Keep the histogram active on the LCD screen when composing the image and that way you can watch in real time how changes in aperture, shutter speed, and iso affect your exposure (check the camera settings or camera's user manual on how to get the histogram on screen).
  • If you are not using live view, keep it on when reviewing images to get an idea of the exposure, so you can correct it (do not always rely on what you see on the LCD screen while reviewing).
  • Use the correct metering mode depending on the scene you are photographing.
  • Always shoot raw, that way you get to pull out a little bit of the lost details (both in darks and whites) while post-processing, but, it is always good to get the exposure right in camera.
  • Do not worry if the histogram hits the ends when you have blacks and whites in the scene. Also note that a little bit of clipping is ok and there are times when that is unavoidable in scenes that have strong reflections from water, glass, etc.

That's about it. It is really that simple and not complicated at all like many would think or refrain from using. If you have any other tips on using the histogram to get the exposure right, please share your thoughts in the comments section below.


About the author

Dahlia Ambrose

Dahlia is a physicist and self taught photographer with a passion for travel, photography and technology. She can sometimes get obsessed trying new photography techniques and post processing styles using Lightroom or Plugins in Photoshop. She occasionally writes articles on topics that interest or provoke her. You can check out her photography on Instagram, 500px and Flickr

  • Kent DuFault says:

    Nice Article, Dahlia.

  • Lakshmi mn says:

    Good and educative

  • Graham Hart says:

    Very clear explanation Dahlia. The examples are great and its good to know that the numbers 0 and 255 aren’t quite as nasty as first thought.

    Report user
    • Thank you very much Graham. Glad that you found them useful 🙂

      • Graham Hart says:

        Hi again Dahlia. Question: what does it mean when a histogram is perfectly centred (no clipping at the edges) and dome shaped but the amplitude is quite shallow? I know the overall height of the histogram relates to the number of pixels but what does this mean in real terms? Low exposure? The reason I ask is because I recently took a photo which turned out looking fine to my eyes (exposure-wise) but the histogram was only half the height of the usual histograms I see?

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        • Hi Graham, sorry, not sure how I missed this question. The x-axis represents the tonal variations from black to white and the y-axis represents the amount of pixels for a given tonal value or range.

          If the histogram is flat, then it means that for that particular tonal range the number of pixels is less. This could be because the lighting in the scene was even without much contrast – which means the light was flat. Did you try increasing the contrast to see if there was a change in the histogram?

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