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Understanding Histogram: The Easiest Way To Achieve Proper Exposure

Understanding Histogram: The Easiest Way to Achieve Proper Exposure

Histogram simply is a graphical representation of the distribution of light or color components in a photograph. It is the easiest way to achieve proper exposure. Just by checking the histogram, you can make out if the image is underexposed or overexposed. Understanding histograms will be very handy in the field, as you can correct any exposure mistakes immediately.

In digital world, an image is made up of collection of pixels and a pixel is made up of Red, Green, and Blue (RGB) color components. Pixel is the smallest display area of illumination in a photograph. However, in digital world, it is just an array element which is represented in 24-bits in RAW format. Pixel is generally 8-bits in JPEG format and 8-bit, 10-bit, 12-bit, 14-bit or 16-bit variations using TIFF format.

A RAW pixel can be represented as: 1 Pixel (24-bits) = Red (8-bits) + Green (8-bits) + Blue (8-bits)

You will find two types of histograms in modern DSLRs. One which is represented in all black (which is basically the light distribution), and Three histograms representing Red, Green, and Blue color components distribution.

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We understand Red, Green and Blue color components, since a pixel is made up of these…but where is the light distribution coming into picture?

Light distribution is calculated using the three color components Red, Green and Blue!

Light (8-bit) =  Equation [Red (8-bits), Green (8-bits), Blue (8-bits)]

Let us not get into equations and the conversions that are done internally. Let us just understand that each of the histogram is represented with a 8-bit value.

8-bits, in binary world, yields total of 256 values (2^8) ranging from 0 to 255. A histogram plots each of these 256 values (referred to as levels) in x-axis and their number of occurrences in a photograph in the y-axis of the graph.

Check the histogram plot for Luminosity (Light), RGB (composite Light), Red, Green, and Blue components.

Histogram representing RGB, luminosity, Red, Green and Blue colors

All 5 types of Histograms. Namely, RGB composite, Luminosity, Red, Green, and Blue

Out of 5 histograms (luminosity, RGB, Red, Green, Blue), we are generally interested in light distribution which is either Luminosity or RGB composite histograms.

That is because, the light is the most important factor to produce an image and our eye is most sensitive to the light than the color. You are already aware of this, aren’t you?

Just, turn off the light. You cannot see any colors…neither bright nor dark! On the contrary, if the light is just too bright, then you won’t see any colors again…everything will look white!

Understanding Histogram Values

We understand that histogram is a graph with 256 values plotted against the number of occurrences of each of these values. Let us understand about these 256 values.

256 values or levels = 256 shades of grey

Understanding Black Histogram (Light)

Shades of grey ranges from pitch black (represented by value 0) to pure white (represented by value 255). All the values in between 0 and 255 represents the shades of grey from black to white.

Understanding Color Histogram (RGB)

In case of color histograms, you will get the shades of that particular color ranging from 0 (lowest saturated color) to 255 (highest saturated color).

Reading the Exposure based on Distribution of Light

If the distribution in the histogram is towards the left hand side of the graph, then the image is mostly having black shades of grey or the image is underexposed.

Understanding Histogram. Great Egret with underexposed histogram.

Photograph of a Great Egret shows that the overall image is dark or underexposed. The histogram indicates the same in a graphical way.

On the other hand, if the distribution in the histogram is towards the right hand side of the graph, then the image is mostly having white shades of grey or the image is overexposed.

Understanding Histogram. Chipmunk on a tree branch showing overexposed histogram.

Histogram of an image of Chipmunk, shows that the image is severely overexposed. The portion of the background in this image is completely white or overexposed. You can also observe that there is some portion of image which is underexposed, which is not easy to identify in the image, but histogram shows it clearly!

With above two examples, you can infer what a properly exposed image looks like in the histogram. The histogram should have grey values well distributed in the middle.

Understanding Histogram. Belted Kingfisher in flight. Proper distribution of histogram showing perfect exposure.

In this image of a Belted Kingfisher, the histogram clearly shows a perfect distribution indicating nearly a perfect exposure

Bottom line is to avoid the extreme left and the extreme right side of the histogram.

Well Distributed Histogram?

Is it always necessary to get a well distributed histogram for a proper exposure? No, not really. It always depends on the scene.

If the scene contains only few shades of grey, then the histogram may have only few grey shades that accumulate only towards one portion of the graph. Which is perfectly fine.

Understanding Histogram. An image of a frog showing underexposed histogram.

An image of a frog showing underexposed histogram. But the image demands such exposure and there is no need to push the histogram to the right in this case

Expose it to the Right

Consider the below histograms:

Understanding Histogram. A composite image of an American Goldfinch perched on a plant. Histograms show the light distribution in each case.

The middle image indicates that the exposure is fine, there is no hard clipping. But the image looks dark and if you try to bring the exposure up in the post, then the colors look muddy and the textures and features will be gone.
The top image make it clear that it is always good to expose to the right since we do not loose any data.
If you push it too much to the right, then you will overexpose the image

Just by looking at the Histogram, you can say that you got the right exposure. However, when you have the image exposed towards the left of the histogram or underexposed, you will most likely loose the subtle textures and features in the darker areas of the image.

If there is enough space onto the right of the histogram, then it is always good to push the histogram to the right to get all the subtle textures and features on the subject(s).

However, care should be taken, not to go too far by pushing it to the right edge, since you will run into overexposed image.

How do you Avoid it?

Go for positive exposure compensation. Try with +0.3 to +3.0 and lock on the exposure when you get the histogram to the right hand side without overexposing any details.

On the contrary, if the histogram is skewed towards the right with highlights clipped, then you will run into overexposure. You can avoid it using negative exposure compensation.

What if the histogram overshoots the Full Dynamic Range?

When the histogram shows the grey values less than 0 (clipped to the left) all the way beyond 255 (clipped to the right also), then you might have to go for 2 or more exposures. One or more for the darker regions and one or more for the brighter regions.

Later you can combine them in the post by using exposure blending options to get what is widely known as an HDR (High Dynamic Range) image.

HDR is mostly misunderstood by many photographers around the world. I will cover HDR in an in-depth article sometime in the future. Don’t forget to subscribe!

As of now, remember that, HDR is just a High Dynamic Range image which allows you to capture more than 256 levels. It is a way of increasing the dynamic range from 0 to 255 to something higher. By doing this you can accommodate avoid clipping of darker regions and brighter regions.

But, at the end of the day, you have to bring the dynamic range back to 0 to 255 since the final JPEG image will be using 8-bits per pixel by blending the exposures in post-processing software.

Understanding Histogram. Three exposures of the Lake of Clouds showcasing exposure blending technique to create HDR image

The top two images make it clear that the scene is of very high dynamic range.
The top image is exposed to the shadow region or the foreground and the middleground in this case.
The middle image is exposed for the background.
The final image is a composite of the first two images made by blending the two exposures to create a HDR (High Dynamic Range) image


Always remember to check the histogram right after you take an image to make sure you have the proper exposure. If not, then use exposure compensation and take more pictures until you get the properly distributed histogram.

Histogram makes our life so easy in the digital world, that we don’t have to assume about whether the image is properly exposed or not. Because, we know it by looking at the graph! Don’t we?

That’s all from me for now. I would like to listen to you now. Feel free to write about your take on histogram.

Let me know if you have any doubts about the concept. I will be happy to help you.

Want to read more simple photography tips like this? [thrive_2step id=’2953′]Download Beginner’s Guide to Photography.Beginners Guide to Photography. Free eBook on Photography for Beginners. Best Photography Free eBook. Written by Prathap[/thrive_2step]

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Prathap is a professional nature photographer and founder of Nature Photography Simplified blog. He aims to simplify every photography concept to help beginners and amateur photographers.

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This Post Has 19 Comments
      1. Thanks Prathap

        i hv read your article on histogram
        can i see the histogram after an exposure
        I hv D3200 nikon
        pls suggest


        1. Hi Pramod, Thanks. I don’t have my camera with me now, but I vaguely remember the option names.To display the Histogram on the LCD monitor, you’d have to go to Menu. Then to Playback Display Options. In the Playback Display Options, you’d have to turn on Histogram.

  1. Prathap,

    Excellent article! I am a coordinator for a seniors Meetups Photography Group in Greenville, SC. (no commercial sponsors) We look at web sites constantly to discuss topics such as these. Would it be possible for us to use some of your graphics/illustrations in a simple PowerPoint discussion set? We have a public library provided projector with awful image definition, 40+ members and need to boil down topics to 10 minutes or less. We would introduce/discuss the topic in 5 or so summary slides, and then refer all to your site and specific article. It’s proven very difficult to try to walk through these topics as a group on the original site, the lettering is too small from afar, etc.

    I look forward to your response. Once again, excellent material! Thank You


  2. Didn`t understand histogram initially. Thanks to you for a simple and lucid explanation.
    Following your tutorials regularly. I am A beginner and thanks to you once again, i am evolving into a better one.

  3. Hi Prathap,

    I am a great fan of you and the way you write articles.
    You make topics to understand with simplicity, which otherwise sounds too technical.
    I am a software professional, have keen interest in photography and started taking it seriously 3 years ago and your blog helping me a lot.


  4. Thanks Prathap, i have used histograms for a long time now as a means of defining a good or bad photograph. The naked eye can deceive when trying to determine whether or not a photograph is under or over exposed. The histogram is a fool proof way in determining a correct exposure. I enjoy your articles very much. Thankyou

  5. I thought just take a shot is all about photography but you made me understood that i was wrong.
    thank you very much
    please can i get your email

  6. Hi Prathap

    I would like to buy the Kick Ass Guides to Exposure and other Kick ass guides to settings , DOG etc please send me an email alert – when they are on promotion.

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