Many digital cameras provide a histogram feature whereby you can see a digital analysis of your photo immediately post-shoot and determine whether it was underexposed or overexposed. But how do you look at the histogram graph and figure out what’s wrong with the image and how to correct it?

Analyzing the Histogram

A histogram on a digital camera is simply a graphical representation of all the pixels in a particular photo, where the vertical axis represents the number of pixels, and the horizontal axis represents the brightness value – the left-most part of the horizontal axis is pure black (0 brightness) with the far right part being pure white (255 brightness). You may be more familiar with the histogram if you have used the “Levels” editing option in some of the Adobe software applications.

It is important to note that the entire horizontal axis represents only 5 f/stops worth of brightness, which explains why cameras cannot expose scenes with high contrast the same way we humans can see it. Thus, the importance of using the histogram: it is a tool that warns you whether you’ve over or underexposed a photo.

It is also important to note that if you divide the horizontal axis into 5 zones – one for each f/stop represented, that the number of tonal values available in each f/stop zone of the histogram is not equal. In fact, the zone to the farthest right that represents the brightest tonal values captures the same number of tonal values as that of the other four zones put together!

The Ideal Histogram

In order to have detail show up in dark and light areas in a photo, and to have a photo with depth, you want to expose to the right of the histogram as far as possible without clipping highlights (as shown with a right bar on the right margin of the histogram). Otherwise, your photo’s tones will be represented by fewer levels, which negatively impacts tonal smoothness and adds noise, especially in dark areas.

Underexposed Histogram

An underexposed image shows the left-most part of the histogram vertical against the upper left edge of the histogram boundary (or even left-dominated, touching the left boundary at anywhere but 0). We say that the dark end of the histogram is “clipped” because the graph is cut off prematurely on the left edge. Remember that very few tonal values are captured towards the left end of the histogram, so very little detail will be visible in the dark areas of the photo.

In general, to correct an underexposed image, you can make one or more of the following changes to your camera settings and retake the shot:

1) decrease your shutter speed to let in more light (e.g. change 1/8th second to 1/4th second)

2) decrease your aperture (e.g. change f/8 to f/5.6)

3) increase your ISO (e.g. change ISO 200 to ISO 400)

Overexposed Histogram

An overexposed image shows the right-most part of the histogram vertical against the upper right edge of the histogram boundary. We say that the light end of the histogram is “clipped” because the graph is cut off prematurely on the right edge. Such a histogram maps to a photo that is overexposed, and has lost detail in the lightest areas of the image.

In general, to correct an overexposed image, you can make one or more of the following changes to your camera settings and retake the shot:

1) increase your shutter speed to let in more light (e.g. change 1/250th second to 1/500th second)

2) increase your aperture (i.e. change f/5.6 to f/8)

3) decrease your ISO (i.e. change ISO 400 to ISO 200)

Properly Exposed Histogram for a low-key photo (i.e. mostly dark – perhaps the moon at night)

When a photo is composed of things that are mostly very dark in shade, then we call it a low-key photo. Such photos will have a histogram with the left end dominated. It can be challenging to capture such an image with low contrast and without underexposing – the histogram would show it’s left edge being clipped if the photo is underexposed. An example of a low-key image would be the proverbial black cat at night.

Properly Exposed Histogram for a high-key photo (i.e. mostly light – perhaps a snow scene)

When a photo is composed of things that are mostly very light in shade, then we call it a high-key photo. These photos will have a histogram with the right end dominated. It can be challenging to capture such an image with low contrast and without overexposing – the histogram would show it’s right edge being clipped if the photo is overexposed. An example of a high-key image would be a snowman in the snow.

By: Jennifer Clarkson

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