Shooting videos with a hand-held camera introduces shaking, which incontrovertibly reduces video quality. Digital video stabilization is a process to compensate for camera motion by means of image processing. In the best case, it not only removes the image motion, but also reduces image distortion caused by unintentional camera motion. In practice, removing solely unwanted jitter cannot be achieved precisely. Furthermore, the stabilization process itself often introduces some additional distortion in images instead of removing it. In this paper, various means to automatically evaluate the performance of the video stabilization process are proposed, based on measuring the divergence and jitter of the remaining unintentional motion and blurring using point spread function (PSF). This helps, for example, in tuning the system parameters for better quality.