Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?

  title={Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?},
  author={Lyndsey C. Pickup and David P. Capel and Stephen J. Roberts and Andrew Zisserman},
  journal={EURASIP J. Adv. Sig. Proc.},
In multiple-image super-resolution, a high-resolution image is estimated from a number of lower-resolution images. This usually involves computing the parameters of a generative imaging model (such as geometric and photometric registration, and blur) and obtaining a MAP estimate by minimizing a cost function including an appropriate prior. Two alternative approaches are examined. First, both registrations and the super-resolution image are found simultaneously using a joint MAP optimization… CONTINUE READING
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NETLAB: Algorithms for Pattern

  • I. Nabney
  • 2002
Highly Influential
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A practical approach to super-resolution

  • S. Farsiu, M. Elad, P. Milanfar
  • Visual Communications and Image Processing, vol…
  • 2006
1 Excerpt

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