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Proceedings Paper

Tomographic reconstruction from partial angular views using Gibbsian models
Author(s): Giovanni Jacovitti; Alessandro Neri; Alberto Laurenti
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Paper Abstract

In some applications of tomographic reconstruction of 2D or 3D fields, the presence of physical constraints allows measurement of projections only within limited angular views; in these cases, a satisfactory resolution may be obtained only with the addition of a priori information about the structure to be estimated. Besides deterministic constraints, some form of probabilistic knowledge is often available, which could help to eliminate a large class of unlikely solutions in the inversion process. However, despite their elegant simplicity, some proposed Gaussian models have shown to be inadequate to satisfactory model objects in actual environments. For these reasons, the paper proposes a flexible probabilistic model based on Gibbs Random Field (GRF) which can be used for tomographic reconstruction. The theoretical framework of the method is described and the performance of the algorithm are illustrated through some simulated experiments.

Paper Details

Date Published: 29 December 1992
PDF: 10 pages
Proc. SPIE 1767, Inverse Problems in Scattering and Imaging, (29 December 1992); doi: 10.1117/12.139030
Show Author Affiliations
Giovanni Jacovitti, Univ. of Rome (Italy)
Alessandro Neri, Univ. of Rome (Italy)
Alberto Laurenti, Univ. of Rome (Italy)


Published in SPIE Proceedings Vol. 1767:
Inverse Problems in Scattering and Imaging
Michael A. Fiddy, Editor(s)

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