@Article{bonmassar1999:real-time,
  author =       {Giorgio Bonmassar and Eric L. Schwartz},
  title =        {Real-time restoration of images degraded by uniform
                  motion blur in foveal active vision systems},
  journal =      {IEEE Transactions on Image Processing},
  year =         1999,
  volume =       8,
  pages =        {1838-1842},
  month =        Dec,
  datestr =      199912,
  INSPEC =       6458401,
  abstract =     {Foveated, log­polar, or space­variant image
                  architectures provide a high resolution and wide
                  field workspace, while providing a small pixel
                  computation load. These characteristics are ideal
                  for mobile robotic and active vision applications. A
                  common problem in these application areas is image
                  blur and motion artifact. Recently, there has been
                  described a generalization of the Fourier Transform
                  (the fast exponential chirp transform) which allows
                  frame­rate computation of full­field 2D frequency
                  transforms on a log­polar image format. In the
                  present work, we use Wiener filtering, performed
                  using the Exponential Chirp Transform, on log­polar
                  (foveated) image formats to de­blur images which
                  have been degraded by camera motion or other sources
                  of blur. Since the exponential chirp transform
                  provides size and rotation invariant properties, we
                  only need to pre­compute and store a single motion
                  vector template, exploiting the size and rotation
                  properties of the chirp transform. This provides
                  real­time performance without requiring a large
                  storage of pre­computed templates. Examples of this
                  processing on different samples from a data base of
                  images shows effective image restoration, with
                  frame­rate performance on modest hardware (e.g. a
                  Pentium or SHARC DSP processor). This work shows
                  that the fast exponential chirp transform provides a
                  simple algorithm with low spatial complexity for
                  full frame, real­time image restoration of foveal
                  imagery.},
  keywords =     {Logpolar Mapping, Motion Blur, Space-Variant Image
                  Processing, Image Restoration, Real-Time Imaging}
}