Jerry L. Prince, Alan S. Willsky

Research output: Contribution to journalConference articlepeer-review


A method is presented for reconstructing images from finite sets of noisy projections which are available only over limited or sparse angles. The method solves a constrained optimization problem to find a maximum a posteriori estimate of the full 2-D Radon transform of the object, using prior knowledge of object mass, center of mass, and convex support, and information about fundamental constraints and smoothness of the Radon transform. This efficient primal-dual algorithm consists of an iterative local relaxation stage which solves a partial differential equation in Radon space, followed by a simple Lagrange multiplier update stage. The object is reconstructed using convolution backprojection applied to the Radon transform estimate.

Original languageEnglish (US)
Pages (from-to)1268-1271
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - Jan 1 1988
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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