How to Read a Histogram and Why It’s Vital to Good Photography

In digital photography there are these things called histograms. They look a little bit like this:

As you can see, it’s a kind of graph with lots of peaks and troughs.

Most cameras have an option to display these when you review the image. On some, you can see a live histogram that changes as you point the camera at different things.

Unfortunately though, it is completely baffling as to what it actually means. So we usually just ignore it and turn it off. That’s a real shame, because they are actually really simple and incredibly useful.

So what is it?

The histogram is a graph that tells you about the image you’ve just made. It doesn’t tell you anything about the subject or artistry of the photo, but it tells you an awful lot about the light that makes it up.

Let’s break it down.

The scale across the bottom corresponds to brightness. The further right you go, the brighter it gets.

The vertical axis corresponds to the number of pixels at that particular value.

The whole thing tells you the overall distribution of light in the photo. How many pixels are dark, middle, or really bright.

In photography we call these different areas the Shadows, Mid-Tones, and Highlights.

Let’s look at a few examples:

I have no idea what would be in this photo – histograms don’t tell you that. But it does say that the photo is very dark, because there are lots of dark pixels, a few middle ones, but no bright ones. Any image with this histogram is probably either taken at night or somewhere extremely dark. It’s probably underexposed, in fact.

Here’s an example of what a perfectly normal image might look like taken during the day. As you can see it’s got a wide range of tones from dark to bright, with some peaks and troughs.

Finally, here’s an example of a histogram for an image that is almost certainly too bright. The fact that it is all piled up on the right hand side of the graph indicates that a lot of the image is overexposed. In other words, the highlights are blown out. They will just appear as flat white in the image.

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How do we use it?

Well, hopefully that should already be kind of obvious at this point.

The histogram gives you an absolutely clear picture of the exposure you have just made. It can tell you at a glance if your image is under or over-exposed. For instance, you might have a really bright sky in your image that you want to prevent blowing out. By looking at the histogram, you can see how far you need to adjust your settings.

Here’s this histogram again. See how it has a big peak on the right? That’s exactly what you’re looking to avoid. You want your highlights to be bright, but not so bright they are burnt out. If this was your histogram you’d need to reduce the exposure a bit, until it looked more like this:

See how the whole thing has shifted over to the left? And, crucially, the big spike on the right has now moved off the wall. It’s about as far right as it can go without actually touching it. We call this exposing to the right. It’s a technique that helps you get the exposure right every time.

This is actually a really good result if your histogram looks like this. The line meets the edges at the corners, so the dark bits are dark without being black, and the white bits are white without being blown out. Good job.

Quite often though, you’ll get a result that looks more like this:

A big spike of shadows and dark mid-tones, not much in the middle, and then a big spike of highlights. This is what can happen when you have a sky that is much brighter than the foreground.

In this case, though, you’re still good to go – as the right peak is not ‘climbing the wall’. The sky will look ok. The rest of the image might be a bit dark, but it’s probably better to work with it rather than increasing the exposure and blowing out the highlights. That’s because you can use software to brighten up the dark parts, but it’s much more of a problem to bring overexposed highlights down. Remember – you want to keep it off the right hand wall.

Above: When you edit you’d probably be looking to move the bit on the left further right (raising the shadows).

Above: How it might look after editing. This would now look more balanced, with more midtones.

Some finer detail:

Histograms usually have a series of dotted vertical lines in between the ends of the graph. Those lines aren’t arbitrary – they correspond to exposure stops.

That comes in super darn useful, because it let’s you see approximately how much you need to adjust the exposure to create the necessary correction for your next shot.

Above: Oops! We’ve overexposed again. Looks like we need to move about 1 stop to the left (darker) for the shadows to be dark and the highlights not to be blown out. I could double the shutter speed or increase the aperture by 1 f-number. Or I could reduce the ISO one value.

Perfect! All hail the histogram!

Histograms are especially useful in landscape photography because they are unequivocal. When we’re shooting outdoors there might be bright sun shining on the screen of our camera. That can make it hard to see the result clearly in image review, and it can mess with the brightness and contrast of the image on the screen. Just eyeballing the result is never the best option. If you can see the histogram then you can see definitively whether the exposure was right or not.

Here is another nuance. Because the camera sensor is divided into Red, Green and Blue pixels, the final image is made of three separate ‘channels’ – one for each colour. Each one has its own histogram, with the overall histogram being a combination of all three. It is possible for one channel to overexpose independently of the others. Let’s say there’s a very bright blue sky, for example. That might cause the histogram above, where the blue is a bit too bright. This can mess with the colour in the final image.

Being able to see the separate channels can be useful, because it can open up other editing options. Not something we’ll go into now, but something to be aware of!

Hopefully this helps you understand how histograms work and why they are so useful. If you have any questions then leave a comment below and I’ll get back to you!

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