In the last instalment of this series we looked at light meters and used the histogram to discuss exposure. In this part of the series we’re going to take a closer look at histograms and explain a little more what information they convey and what information they don’t convey.
What is the histogram? Simply put it’s a distribution of the pixels in an image from black (on the left) to white (on the right).
What isn’t the histogram? As strange as it may sound, and perhaps a bit contrary to what we were talking about in the light meter article, the histogram is not a substitute for a light meter.
It’s not? No, it’s not. Everything we see in the histogram and any assumptions or information it may convey about whether an image is under- or overexposed is based on the context of the image itself.
A histogram that’s skewed to the left doesn’t absolutely mean the image is underexposed. Conversely, a histogram that’s skewed to the right doesn’t necessarily mean the image is overexposed. The information in the histogram has to be viewed in the context of the image. In the examples in the last article, the histogram did show an underexposed flower in the context of the image. Let’s look at some examples to see how the context of the image is important.
The histogram of the image below is skewed to the right. But this is what’s called a ‘high key’ image. A high key image is one with a majority of light tones and very minimal dark tones. In the context of this type of image, the histogram is fine.
The opposite of a high key image is a low key image. In a low key image, the majority of the tones are darker with a minimal amount of light toned area. The histogram for this type of image is skewed to the left as shown below.
In the context of this image, the histogram is correct. In another context it might show underexposure. But not the spike at the right end showing some pure white. In a truly underexposed image this would not be the case unless the dynamic range of the image were wider than our sensor could capture.
The image below looks flat and lacking in contrast. This is confirmed by the histogram. The graph is pulled in from both ends indicating there are no true whites and no true blacks. This is a low contrast image.
Many people feel this shape of histogram indiates a ‘good’ image. It may, but not necessarily. What it shows is that the majority of the tones in the image are middle tones. This may be fine. It depends, again, on the context of the image. The histogram that approximates what, in math terms, is referred to as a ‘normal distribution’ isn’t good or bad by default. It depends on the image. It’s rare; however, that we’ll want an image that has a histogram showing gaps at either, or both, ends.
The last one we’ll look at is a high contrast image. In this type of image, the histogram fills the entire graph and there may be peaks at both ends with a trough in the middle. This tells us that there are true blacks and lots of other darker tones along with true whites and plenty of other light tones.
That’s exactly what the graph for this image shows. And in the context of the image, it’s correct. At least it’s correct for me. Your vision for this image may be different and that’s fine.
So, in closing, the histogram in and of itself doesn’t tell us whether our image is properly exposed or not and we shouldn’t use the histogram as a proxy for a light meter. Context tells the tale. What may be an incorrect exposure in one image will be correct in another. Keep this in mind when you’re viewing your images in the field and when you’re working with them in the digital darkroom.
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