Effects of de-blurring on background modeling used for surveillance in long-distance horizontal imaging

Long-distance imaging through atmospheric turbulent medium is affected mainly by blur and spatio-temporal movements in the recorded video, which have contradicting effects on the temporal intensity distribution, mainly at edge locations. For automatic surveillance, a correct model of the background can contribute to a successful background subtraction often applied for the extraction of the moving targets. Following a recent study of modeling the background due to atmospheric effects, we further examine here experimentally the effect of image de-blurring on the model using an automatic image restoration method implemented to real video signals recorded from a variety of imaging distances.

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