Effect of image restoration on acquisition of moving objects from thermal video sequences degraded by the atmosphere
By: Oren Haik and Yitzhak Yitzhaky
Remotely sensed videos captured by high-resolution imagers, are likely to be degraded by the atmosphere. The degradation sources that include turbulence and aerosols cause mainly image blur in still images. In video sequences however, spatiotemporal-varying distortions caused by turbulence become also meaningful. These atmospheric degradations reduce image quality, and therefore, the ability of target acquisition by the observers. The effects of image quality and image restoration (de-blurring) 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 effects 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 non-restored video sequences captured by a remote-sensing thermal imaging system. Results show that image restoration may 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.
Recorded versus restored videos:
Contrast and brightness in the media player may be adjusted to better view the videos.
Experiment 1: Detection and recognition of moving objects in the six video clips shown below -
Video_1 (Construction workers)
Video_2 (Walking person, two dogs)
Video_3 (Two trucks, car)
Video_4 (Walking person, dog, bird)
Video_5 (Forklift, truck)
Video_6 (Bicycle rider)
Experiment 2: Determination whether a moving person carries a thin pole (a rifle-resembled object) in the three video clips shown below -
Video_7 (Walking with a pole)
Video_8 (Walking without a pole)
Video_9 (Walking with a pole)