Remotely sensed videos, captured by high-resolution imagers, are likely to be degraded by the atmosphere. In still images, the degradation sources, which include turbulence and aerosols, mainly cause blur. In video sequences, however, spatiotemporally varying distortions caused by turbulence also become important. These atmospheric degradations reduce image quality and therefore the ability of target acquisition by the observers. The effects of image quality and image restoration (deblurring) on target acquisition in still images were examined previously in several studies. Nevertheless, results obtained in static situations may not be appropriate for dynamic situations (with moving targets), which are frequently more realistic. This work examines the effect of image restoration on the ability of observers to acquire moving objects (such as humans and vehicles) in video sequences. This is done through perception experiments that compare acquisition probabilities in both restored and nonrestored video sequences captured by a remote-sensing thermal imaging system. Results show that image restoration can significantly improve the acquisition probability. These results correspond to the static case. However, unlike the static case, considerably smaller differences were obtained here between the probabilities of target detection and target recognition.