The resolution of videos can be computationally enhanced by moving the camera and applying super-resolution algorithms. However, a moving camera introduces motion blur, which limits the quality of super-resolution. We analyze this phenomenon and derive a theoretical result showing that motion blur severely degrades the performance of super-resolution. The conclusion is that in order to achieve any reasonable enhancement in resolution by using super-resolution, motion blur should be avoided.

To this end, we have developed a novel camera called the "jitter camera". The jitter camera produces shifts between consecutive video frames without introducing any motion blur. This is done by shifting the video detector instantaneously and timing the shifts to occur between pixel integration periods. The videos captured by the jitter camera are processed by an adaptive super-resolution algorithm that handles complex dynamic scenes in a robust manner. We show that the video resolution is significantly enhanced for stationary or slowly moving objects, while it is improved slightly or left unchanged for objects with fast and complex motions. The end result is a video that has a higher resolution than the captured one.