Abstract
Platform motion blur is a common problem for airborne and space-based imagers. Photographs taken by hand or from moving vehicles in low-light conditions are also typically blurred. Correcting image motion blur poses a formidable problem since it requires a description of the blur in the form of the point spread function (PSF), which in general is dependent on spatial location within the image. Here we introduce a computational imaging system that incorporates optical position sensing detectors (PSDs), a conventional camera, and a method to reconstruct images degraded by spatially variant platform motion blur. A PSD tracks the movement of light distributions on its surface. It leverages more energy collection than a single pixel since it has a larger area making it proportionally faster. This affords it high temporal resolution as it measures the PSF at a specific location in the image field. Using multiple PSDs, a spatially variant PSF is generated and used to reconstruct images.
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