The Basics Behind Image Stabilization

We’ve all been witness to shaky video footage or blurred images captured by professional and beginner photographers alike. While image blur is often unavoidable, particularly under certain circumstances, it certainly detracts from the overall impact of the image and occasionally even renders the affected image unusable. In their attempts to increase the stability of images and video footage, camera manufacturers have been working with the concept of image stabilization (IS), a series of techniques that can allow a still image photographer to shoot 2-4 stops slower (handheld) than without the IS option.

This essentially translates into less blur on average for a variety of photo situations, since the image stabilizer will counteract slight movements of the photographer that would have otherwise created a shaky image. Before delving into the details behind how stabilizers work, it’s important to note that IS systems will not compensate for motion blur caused by a subject or from extreme camera movement.

While many companies have their own terminology and marketing behind their image stabilization techniques, all of the systems operate in much the same way. Without getting terribly technical, an image stabilizer uses a motion sensor to communicate to a microprocessor in the lens or digital camera body, depending on where the IS system is located. The microprocessor then takes the information and decides whether or not to activate a series of gyroscopic stabilizers that serve to counteract the movements that would have otherwise been responsible for creating a blurred image.

Although the entire process sounds rather complicated, it truly does work, particularly in low-light situations where the lens needs to stay open longer in order to capture the correct amount of light. Think of it this way – a certain amount of light must be captured through the lens before an image can be recorded on your memory card. In lower light situations the lens must stay open longer to capture enough data, which increases the likelihood of even the slightest movement causing motion blur. This is where the IS system can save the day, and often does to some extent.