Evaluating and predicting human detection performance of targets embedded in distorted and restored infrared images

Aviram, Guy; Rotman, Stanley R.; Succary, Roni

doi:10.1016/s1350-4495(01)00121-9

Cited by 2 publications

(2 citation statements)

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“…25 The experimental results indicate that image restoration can significantly improve the ability of observers to acquire moving objects ͑averages of 20-percentage-point improvement in detection, and 24percentage-point improvement in recognition͒. The detection improvement results here agree with results obtained in a previous study, 16 which demonstrated that restoration of ͑synthetically͒ degraded static thermal images improves the detection probability by an average of 22 percentage points.…”

Section: Discussionsupporting

confidence: 80%

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Effects of image restoration on acquisition of moving objects from thermal video sequences degraded by the atmosphere

et al. 2006

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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 ͑deblurring͒ 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 targets͒, 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 vehicles͒ in video sequences. This is done through perception experiments that compare acquisition probabilities in both restored and nonrestored video sequences captured by a remotesensing 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. © 2006 Society of Photo-Optical Instrumentation Engineers.

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Section: Discussionsupporting

confidence: 80%

“…14 The effect of image restoration on target acquisition performance by observers was analyzed for still images only. [15][16][17] In these studies, different amounts of atmospheric blur and Gaussian noise were added synthetically to the images. The images were then restored using Wiener filtering.…”

Section: Introductionmentioning

confidence: 99%