Coarse grid correction by aggregation / disaggregation with application in image reconstruction | Zendy

Popa Constantin | Zendy; Nicola Aurelian | Zendy; Rüde Ulrich | Zendy

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Coarse grid correction by aggregation / disaggregation with application in image reconstruction

Author(s) -

Popa Constantin,

Nicola Aurelian,

Rüde Ulrich

Publication year - 2010

Publication title -

pamm

Language(s) - English

Resource type - Journals

ISSN - 1617-7061

DOI - 10.1002/pamm.201010357

Subject(s) - grid , relaxation (psychology) , pixel , projection (relational algebra) , minification , computer science , iterative reconstruction , algorithm , algebraic reconstruction technique , algebraic number , image (mathematics) , mathematical optimization , computer vision , artificial intelligence , mathematics , geometry , mathematical analysis , psychology , social psychology

In algebraic reconstruction of images in computerized tomography we are dealing with rectangular, large, sparse and ill‐conditioned linear systems of equations. In this paper we describe a two‐grid algorithm for solving such kind of linear systems, which uses Kaczmarz's projection method as relaxation. The correction step is performed with a special “local” aggregation / disaggregation type procedure. In this respect, we have to solve a small sized minimization problem associated to each coarse grid pixel. The information so obtained is then “distributed” to the neighbour fine grid pixels. Some image reconstruction experiments are also presented. (© 2010 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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