You might have seen some articles here on Digital Photography School about using the histogram when editing pictures in Lightroom and Photoshop, but it can also be a very handy tool when you are out shooting images as well. Most cameras have the ability to show you the histogram when you review your photos on the rear LCD screen, and some even allow you to see a real-time histogram in Live View. While this might seem a bit intimidating at first, learning to use the histogram when out shooting pictures can have a dramatic impact on your photography and help you understand how to get the right exposure for the photos you are taking.
Sorority Bid Day brought to you by the magical properties of the histogram.
In a nutshell, the histogram shows how much data is recorded for various Red, Green, and Blue color values in a picture. While you can usually see data for all three colors separated into discrete graphs, the one I find most useful for general shooting is the histogram that combines all three RGB values into one visual representation. A histogram shows how much data has been recorded across the tonal range of a photograph from very dark to very light. A spike in the graph means a lot more data has been recorded for those particular values of darkness or lightness, and a dip means that not much data has been saved. In general, a properly-exposed picture should have a histogram that looks something like this:
An example of a hypothetical histogram for a properly exposed photo.
A histogram similar to this example would mean that most of the color data is concentrated in the middle: the greatest quantity of pixels is neither too dark nor too light. Most photos will have some darker pixels and some brighter pixels, but in general all the information captured by a camera’s image sensor should fall somewhere between the darkest of darks (i.e. very black) and the lightest of lights (i.e. very white). A histogram that is skewed to the right would indicate a picture that is a bit overexposed because most of the color data is on the lighter side, while a histogram with the curve on the left shows a picture that is underexposed. This is good information to have when using post-processing software because it shows you not only where the color data exists for a given picture, but also where any data has been clipped: that is, it does not exist and, therefore, cannot be edited. It’s also good information to have out in the field, such as in the following example:
Most cameras allow you to overlay the histogram on top of a given photo during playback, or as you shoot the photo when using Live View.
I could tell right away that this picture of some college students playing Quidditch was a little overexposed, but looking at the histogram data right on my camera gave me additional information that helped me adjust my shooting on the spot. The large curve on the right-hand side tells me that most of the color information is concentrated on the lighter side, which is actually a good thing because more data is actually collected in the highlight portions of the image which can then be brought down later in a program like Lightroom. (This is a technique called expose to the right, which is a fantastic way to get a little more out of your photography if you are willing to put in a bit of time editing pictures on your computer.)
The problem with this image, as you can see in the above histogram, is that the graph literally goes off the chart on the right-hand side. This means that some of the highlights have been clipped: there is no longer any data that can be recovered, and no matter what I do in Photoshop or Lightroom there are some portions of my image that show up as pure white and can’t be edited. An example histogram from a photo that is clipped on both the darkest and lightest areas would look like this:
After taking the first photo and realizing that some of the data would be lost due to clipping, I was able to adjust my exposure settings and get a much better image:
Quidditch isn’t only played at Hogwarts.
The histogram for this picture was also concentrated a bit more to the right-hand side, but right after I shot it I was able to see that no data had been lost due to clipping. This didn’t help much in the immediate moment, but it meant that I had plenty of information to work with later when editing the picture in Lightroom. As another example, here’s a picture of a unique building on the Oklahoma State University campus:
The Noble Research Center on the campus of Oklahoma State University.
When I looked at the back of my camera it seemed as though the photo was pretty good. The sky was a bit bright, but I thought everything would be just fine overall. This is similar to many situations I have been in when I thought I could tell simply by looking at the photo on my camera’s LCD screen if it was exposed properly, but a quick check of the histogram can yield much more information. Even though the above image seemed decent at first, the camera histogram told another story:
The histogram for the above photo indicated severe clipping on the highlights, meaning some parts of the photo were so bright that I wouldn’t be able to fix it in Lightroom.
Had I not looked at the histogram I would have never seen that a good chunk of the sky was clipped which meant there was no color data at all for the brightest portions of the photo. This would be a serious problem for my post-processing when I bring my pictures into Lightroom and adjust various parameters to get the image to look like I want. After looking at the histogram I re-adjusted my exposure settings and took another photo which had an improved balance of color data across the spectrum:
The same composition, but with different exposure settings that resulted in a better exposure with no clipped data.
One curious aspect of this image is that while the sky is now properly exposed, the glass panels on the building appear to be too dark. Looking at the histogram you can see that while there is certainly a lot of data on the darker portions of the image (hence the spike on the left-hand side of the graph), no data has been lost due to clipping. This means I had a lot of flexibility to improve the image in Lightroom, which resulted in the following finished photograph:
One nice thing about most mirrorless cameras, as well as some DSLRs when shooting in Live View, is their ability to give you a real-time indication of any areas of the image that will be over – or under – exposed. This is normally referred to as a zebra pattern and it essentially overlays a series of stripes over any portion of your image where data is going to be clipped. And remember, as I stated earlier, many cameras today have the ability to show you a live histogram that updates in real-time so you can see not only where the color data on your image is concentrated across the light/dark spectrum, but also alert you to any clipping that will happen when you take the photo.
These are just a few examples of how the histogram can be useful when you’re out shooting photos, not just when you’re editing them on your computer. How do you use the histogram, and what other tips and tricks do you have to share about using it to enhance your photography? Leave your thoughts in the comments below.
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