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Reading Histograms

When I bought my first SLR (a Canon Digital Rebel XTi), I really didn’t understand anything about exposure. I simply took photos of things that I thought would look cool, I’d check the image on the LCD screen and, if it looked good, I moved on to my next shot. I knew enough to know that if the photo looked too bright, I needed less exposure (a smaller aperture, a faster shutter speed, or a lower ISO) or if the photo looked too dark I needed more exposure (a wider aperture, slower shutter speed, or higher ISO). But if the image on the LCD screen looked “good”, I figured there was nothing else I could do. Of course, this was a lot harder on very bright days. I would find myself trying to shade the screen as best as I could with my body or my hand, while squinting my eyes to look, ultimately getting frustrated at not being able to tell whether my shot had turned out like I had hoped. Finally, I’d get home, view the images on my computer and find out that part of the “good” image I thought I took was too underexposed or overexposed in one particular area that I didn’t notice when viewing it on the back of the camera. Now what?

I only had one of two options: Go back and re-shoot or try to fix the under/overexposure with software. It wasn’t often that I’d go and re-shoot because of one bad image (I tend to be lazy) so I’d start editing the photo. Often, this would work out OK but it bothered me that, as a new photographer, I was relying heavily on post-processing and not getting the image I wanted from the camera. What could I do?

This is where histograms come in.

What is a histogram?

A histogram is a graph showing the distribution of colors or shades of a color in an image. Most often, in a single histogram, this color is gray. Below is a simple graphical illustration of how the shades of gray are measured across a histogram:

From the sample histogram above, we see that a spike in our histogram on the left side indicates a large number of pixels that are dark or black (a possibly underexposed photo), while a spike on the right side indicates a large number of pixels are light or white (a possibly overexposed photo). By this reasoning, a histogram that appears to be somewhat evenly distributed across all shades is likely to be properly exposed.

In Practice

How does this translate to actual photos? Let’s take a look below…

Our dog, Hunter, was taking a nap behind my chair so I decided to use him as a model. I set the Automatic Exposure Bracketing on my 5D to +/-2ev and took three shots. The first one, below, is at -2.0ev and, thus, underexposed:

Obviously, you don’t need a histogram to tell you this photo is a little underexposed but bear with me. Let’s look at the histogram from the camera:

You can immediately tell from the histogram above that there are a huge number of dark or black pixels in the image. This tells us immediately that the image is probably underexposed (and we didn’t even have to shield the LCD with our hand!).

Now, let’s look at the photo taken at +2.0ev:

Too bright, right? Let’s look at the histogram to confirm:

Above, we see a pronounced spike on the right side of the histogram which tells us this photo is definitely overexposed. Look at the small bump, though, on the left/dark side. What’s that from? You’re right! It’s mostly from the chair behind Hunter. It’s one of the only dark things in the photo.

Finally, let’s take a look at a properly exposed photo… Properly exposed, according to the camera’s evaluative metering anyway. See my post on light metering for more info on how the camera isn’t always right.

That looks a lot better than the previous two, doesn’t it? Now, how about that histogram?

You can see from the histogram that we might still be a little too white, but the distribution is much wider than in the previous two histograms and the spikes that we do see aren’t nearly as pronounced or severe. This lets me know that my exposure is just about right… or at least as good as it’s going to get without some change in lighting, metering, or post-processing.

So how does this help?

You can just look at the images and tell they’re over- or underexposed, right? Well, in most cases, yes. But, if you recall from a few days ago when PopPhoto reviewed one of my photos, they only gave me three stars out of five. Why? Well, let’s regurgitate a small block:

“To improve on this shot a shorter exposure should be used to prevent the highlights from blowing out. The LCD can be misleading so next time take a few shots with different exposure times or try bracketing your exposures giving you an option to merge them.” (link)

As a reminder, the shot is below:

Overall, on the LCD screen, I thought the shot looked pretty darn good. Seeing that the bridge structure was blown out on a tiny 2.5-inch LCD isn’t easy, especially when the bridge is that shade of yellow. Of course, at the time, I had only had my first DSLR for about a week or two and, consequently, I knew nothing about histograms. If you look at the histogram to the right, though, you will see a pretty even distribution except for the spikes at the left (too dark) and right (too bright). It’s not extremely obvious but, had I known how to read a histogram, I might have tried another shot with a little shorter exposure.

A few more examples

Here we have a very colorful photo of the National Mall:

With this much color and no obvious bright or dark spots, we might expect a histogram with a wider distribution of shades:

One more image-histogram pair:

Conclusion

Now you know how to read your camera’s histogram. No more will you have to worry about missing something in the image preview on your camera’s LCD, you can just read the histogram. Of course, it must be said that, just like any “rule” of photography, you don’t have to have proper exposure every time. You’re the photographer, so you decide. For example, if you’re doing a black and white portrait, you may want to blow out the white background. Or, if you’re spot metering on one particular object, the rest of the photo might be either underexposed or overexposed. Either way, as long as you know you got the shot you wanted, that’s all that matters.

Feel free to leave comments and suggestions in the comments below… But be gentle.

UPDATE: Be sure to see Niels Henriksen’s comment below for some more information on color histograms and digital cameras. Great stuff! Also, please check out Niels’ blog! It has some really great info!

Other Histogram Resources

• Understanding Histograms from DPS
• Histogram Guide from PhotographyReview.com
• Histograms for Photography from Ken Rockwell
• Histogram from Herb Segars Photography
• Your Friend, the Histogram from Earthbound Light

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