An extension of geman and reynolds' approach to constrained restoration and the recovery of discontinuities

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Geman and Reynolds [7] present an approach to linear image restoration which provides for recovery of horizontal and vertical gray-level discontinuities from blurred and noisy observations. We extend their model and parameter selection method to include diagonal discontinuities. A hazard of this modeling approach is identified and addressed. We also comment on the truncated Gibbs sampler suggested in the paper [7].

Original languageEnglish
Pages (from-to)657-662
Number of pages6
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number6
Publication statusPublished - 1996


  • Discontinuity recovery
  • Gibbs sampler
  • Metropolis algorithm
  • Parameter selection
  • Simulated annealing
  • Statistical image reconstruction

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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