Abstract: Existing single image defogging techniques can restore contrast loss and yield a rough estimate of the depth map of a scene. The ubiquity of hand-held imaging devices has attracted considerable attention to motion blur but this has not been addressed in the context of images captured under foggy conditions. In this paper, we show how to restore foggy motion-blurred images using depth cues derived from fog itself. Initially, we address restoration of images blurred primarily due to in-plane translational camera motion. This is followed by a scheme for handling general camera motion blur with a projective blur model. We demonstrate that foggy road scene images can be segmented into road, left, right and sky planes, and that each of these planes can be deblurred individually.
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