Abstract
In this work, we investigate the relation between the edge
profiles present in a motion blurred image and the underlying camera motion responsible for causing the motion blur.
While related works on camera motion estimation (CME)
rely on the strong assumption of space-invariant blur, we
handle the challenging case of general camera motion. We
first show how edge profiles ‘alone’ can be harnessed to
perform direct CME from a single observation. While it is
routine for conventional methods to jointly estimate the latent image too through alternating minimization, our above
scheme is best-suited when such a pursuit is either impractical or inefficacious. For applications that actually favor
an alternating minimization strategy, the edge profiles can
serve as a valuable cue. We incorporate a suitably derived constraint from edge profiles into an existing blind deblurring framework and demonstrate improved restoration
performance. Experiments reveal that this approach yields
state-of-the-art results for the blind deblurring problem