Here's How Your Histograms Should Look

One question I often get from my photography students is: "What the heck is that graph?" I often enjoy teaching photography even more than creating it, but explaining concepts like the histogram is one of the tougher parts of teaching photography.

Perhaps this little graph has been haunting you for some time, popping up here and there in your camera or sitting quietly in the corner of your Lightroom workspace. Or you might already be familiar with the histogram, but would like to learn more. In any case, let's first look at Webster's definition of a histogram: "a representation of a frequency distribution by means of rectangles whose widths represent class intervals and whose areas are proportional to the corresponding frequencies."

That definition couldn't be more obscure and technical-sounding (but that’s why we have photography teachers). To put it in simple terms, a histogram is a visual representation of an image's luminance content, shown as graphical data.

The luminance range of such data lies in its placement on the graph, left to right, or on its X axis. The left end of the histogram represents darker (shadow) data, and the right end represents the brighter (highlight) data. Naturally, the middle of the graph displays mid-tones. The amount of any specific luminance value is represented by the Y axis (up and down).

To make this abstract description more palpable, let's begin with an example. If you create a photo that's technically underexposed, the histogram might appear this way:

If you were to look at the above image's histogram on its own, you might think the image it represents is underexposed and lacking overall data. Actually, there’s nothing technically wrong with it. Photographic art is not always accurately represented by technical data, and sometimes, technical rules are purposefully broken for dramatic effect.

Clipping

Clipping on the histogram is seen as data touching the very end of either side of the X axis: the left (shadows) or right (highlights) end. This indicates a loss of data on either end of the luminance spectrum. Sometimes, clipping is less obvious, showing up as a thin sliver on the very end of a graph.

The good news is that with editing software like Lightroom, you can easily turn clipping indicators on, alerting you to any loss of data within a tonal range. The bad news is that, as I mentioned earlier, you can't recover this data.

You can also use "highlight previews" found in your camera's playback menu, which will actively alert you (via blinking warning spots) to any highlight clipping while you're shooting.

The above image seemed to present a nice moment, and received a "pass" in my image culling process. However, we do observe highlight clipping here. 

Example

As you edit, specifically, as you make global exposure adjustments (exposure, highlights, shadows, etc.), you will notice your histogram changing. These changes can be seen in real-time in the upper right-hand corner of Lightroom's Develop module.

Notice how this image appears dull and muddy. Most of our data is centered around the left side of the histogram, representing the shadows. The clipping on the left means that we've lost data in the image's deep shadows, seen in the background behind the archer. Some of the shadow data that wasn't lost (example: the archer's tunic) can be recovered with post-processing software, but keep in mind you might bring digital noise out from the shadows when brightening them. For this reason and many others, it's crucial to shoot in raw, which preserves the maximum amount of image data.

Notice how much of the data in the above overexposed version is allocated to the right (highlight) portion of the histogram. We also see some clipping on the right end of the graph, indicating blown-out data in the highlights. The highlight clipping comes from the man wearing a white shirt in the background and the archer's arms. Such overexposure should be avoided in shooting. Just like shadow clipping, completely blown-out highlights cannot be recovered in post-processing.

An Ideal Histogram

While there is no "ideal" histogram for all situations, you ideally have most data centered in the mid-tones and not too much in the shadows or highlights or slightly skewed to the right. So, a healthy histogram will show up as a strong graph which shouldn't appear too "thin" or lacking in data, ideally centered around the middle with no data running off either end of the graph. Then again, rules can and will often be broken.

But unlike like the earlier example of the underexposed archer image, you could have an image that is intentionally dark or "low key." The histogram for this image might not look evenly distributed at all. A similarly uneven distribution is could be produced by bright, "high key" images. Such image production reflects legitimate stylistic preferences.

Color Histograms

Color histograms work similarly to an exposure (standard) histogram, but they show you where the data is in each color channel of R, G, and B. For a properly color-balanced photo, you'll want a mostly consistent peak in each color channel. Lightroom integrates the color histogram in the same dialogue as the the exposure histogram. All are shown together as one graph in the upper right corner of the Develop module.

In Photoshop, each of the three RGB channels can be manipulated separately. To do this, use the keyboard shortcut Command + M to bring up your Curves adjustments. Under "Channel" on the Curves adjustments box, select any of the three color channels to view each channel's histogram, and then, manipulate each separate channel to achieve color balance.

If one of the color channels looks different from the rest, it's possible you need an adjustment. I use the Color Curves technique described above fairly often as a shortcut in my color editing, especially when I've identified a single layer that needs color adjustment. Instead of going into the raw slider module to change the white balance, I simply use the Command + M keyboard shortcut and drag the color channels around until they're where I need them.

Summary

Even if you can judge an exposure with your bare eyes, histograms can still be a valuable tool in identifying your exposure and even color data. Histograms can help you to detect data-clipping or peaking. If you're all about maximizing tonal ranges, it would benefit you to attention to your histograms, at least when the occasion calls for it. You can also utilize the Highlight Preview function on your camera and the other built-in Adobe features to make sure you're maximizing your images.

Do you utilize histograms? If so, in what ways have they helped you? Please share your comments below.

If you're passionate about taking your photography to the next level but aren't sure where to dive in, check out the Well-Rounded Photographer tutorial where you can learn eight different genres of photography in one place. If you purchase it now, or any of our other tutorials, you can save a 15% by using "ARTICLE" at checkout.