Two keys open up the understanding of how exposure metering works and why photos turn out as bright or dark as you see them. It's background knowledge – but with practical benefits, because with these two simple keys you can recognize and decide for yourself for many situations whether and how you intervene in the exposure.
The first key to understanding exposure metering is:
You can try out what this means with simple equipment: a white and a black piece of cardboard will do. Any similar objects, e.g. a white and a black T-shirt are just as suitable. I put the two glass balls on the cardboard to distinguish them and so that the camera has a help to focus.
Next you see one shot each where the white and black cardboard boxes fill the entire image. They are taken with the same fully automatic exposure metering, without any change in camera settings, I just held the camera over the individual boxes after the overview photo.
The black and white cardboard boxes appear equally bright because the exposure meter can only measure an quantity of incoming light. It does not know whether it comes from a brightly lit dark surface or a white one in dim light.
If an image section consists of a good mix of bright and dark areas, the camera electronics can easily find an exposure that reproduces bright and dark areas as we see them.
However, if there is little contrast in the image and light or dark tonal values dominate, any exposure metering will render your photo a medium grey. A black cat in front of a pile of coal will be just as grey as a snowman in front of a white wall.
This behavior of exposure metering is timeless; it was already true in decades of analog photography just as it is today in digital. And it affects expensive professional cameras just as much as simple compact cameras.
Different types of exposure metering, no matter how sophisticated and elaborate they have become today, then have no chance to play out their advantages. They can prove their worth when a subject has different brightness distributions. Decisions are then necessary as to which parts of the image are to be taken into account in the exposure measurement and to what extent, or can be neglected.
The second key to understanding exposure metering is:
To illustrate the second key, I took a high-contrast subject with two different exposures.
It has very high contrasts because differences in brightness from the lighting and the subject colour come together: The white cloud, illuminated by the sun and the much darker green, lying in the shade. If the tree is sufficiently bright, the cloud is completely overexposed and washed out. Conversely, a darker exposure that shows all the details of the cloud results in a much too dark, barely discernible foreground.
With very high-contrast subjects, there is no exposure that renders all parts of the image well. The camera electronics or you as the photographer who intervenes in the exposure must decide which parts of the picture you sacrifice as overexposed or underexposed.
This is where modern automatic systems have advantages and differ in how they analyse the brightness distribution in the subject. Then, for example, it can make sure that the part of the picture on which it has focused is still recognisable. Scene recognition before the picture is taken goes even further, especially with smartphones; it can, for example, ensure that a face is easily recognisable even in backlight.
Cameras differ somewhat in the range of brightness they can reproduce. However, none of them comes close to the human eye, and this challenge exists for all cameras.
This second rule is also timeless – applicable in digital photography as it was in previous decades.
What is new, however, is that there are technical tricks to better deal with it: So-called HDR shots combine several differently exposed individual images – the clouds from one photo, the tree from the other. With smartphones, this sometimes happens automatically and so quickly that you don't even notice it.
There are a few simple, ageless rules for exposure. For very low contrast subjects:
The white orchids against a white background, with light from behind are one such example. The left of the three photos is taken with automatic exposure metering – Nikon's cutting-edge matrix metering delivers an image that is too dark, just as any other camera would do and did already decades ago. Additional exposure compensation produces the desired result on the right.
And for very high-contrast subjects: