Videos

Just about all cameras used for serious photography, and even many point-and-shoot models, enable users to choose how light in a scene is measured. The video below will help you understand the options available, and when one works better than the others.

In another clear and concise tutorial, photo instructor Radhakrishnan Chakyat explains the theory behind three in-camera light metering modes, commonly referred to as Center-Weighted, Spot, and Matrix, and he provides practical advice for choosing and using the best mode for the scene you’re shooting.

Chakyat explains that, unlike hand-held “incident” light meters that measure the amount of light falling on a subject, all three in-camera metering modes are designed to measure the light reflected by a scene. The catch, is that they do it differently.

With Matrix (also known as “Evaluative”) metering, which Chakyat says is “the most dependable and safest” approach, the camera divides the frame into multiple zones—analyzing each separately to arrive at a correct exposure. This complex measurement method even compensates for backlit scenes, and others that would be difficult to meter with simpler methods.

A Center-Weighted reading, on the other hand, only accounts for about 60-80% of the field (appearing in the center of the frame), while the Spot Metering mode enables you to precisely measure a tiny portion of a scene, typically between 3-5%. Here, you can associate that “spot” with the focus area you have chosen. The latter approach requires a bit more knowledge, but you’ll nail exposure every time once you know how to use it.

As you’ll see in the video, all three metering techniques can be used when shooting in Aperture Priority, Shutter Priority, or Program exposure modes. Watch the video, to see how it’s done.

There are more great tips on Chakyat’s YouTube channel, and in his earlier tutorial on using in-camera white balance settings. You may also want to look at yesterday’s story, demonstrating how to use Lightroom to refine the white balance of an image.