Semiconvergence and Relaxation Parameters for Projected SIRT Algorithms

Tommy Elfving; Per Christian Hansen; Touraj Nikazad

doi:10.1137/110834640

Semiconvergence and Relaxation Parameters for Projected SIRT Algorithms

Tommy Elfving, Per Christian Hansen, Touraj Nikazad

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Abstract

We give a detailed study of the semiconverg ence behavior of projected nonstationary simultaneous iterative reconstruction technique (SIRT) algorithms, including the projected Landweber algorithm. We also consider the use of a relaxation parameter strategy, proposed recently for the standard algorithms, for controlling the semiconvergence of the projected algorithms. We demonstrate the semiconvergence and the performance of our strategies by examples taken from tomographic imaging. © 2012 Society for Industrial and Applied Mathematics.

Original language	English
Journal	S I A M Journal on Scientific Computing
Volume	34
Issue number	4
Pages (from-to)	A2000-A2017
ISSN	1064-8275
DOIs	https://doi.org/10.1137/110834640
Publication status	Published - 2012

Bibliographical note

Keywords

Algorithms
Parameter estimation
Tomography
Iterative methods
Projected Landweber iteration
Simultaneous iterative reconstruction technique
Relaxation parameters
Semiconvergence
Nonnegativity constraints
Tomographic imaging

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abstract = "We give a detailed study of the semiconverg ence behavior of projected nonstationary simultaneous iterative reconstruction technique (SIRT) algorithms, including the projected Landweber algorithm. We also consider the use of a relaxation parameter strategy, proposed recently for the standard algorithms, for controlling the semiconvergence of the projected algorithms. We demonstrate the semiconvergence and the performance of our strategies by examples taken from tomographic imaging. {\textcopyright} 2012 Society for Industrial and Applied Mathematics.",

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AU - Hansen, Per Christian

AU - Nikazad, Touraj

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AB - We give a detailed study of the semiconverg ence behavior of projected nonstationary simultaneous iterative reconstruction technique (SIRT) algorithms, including the projected Landweber algorithm. We also consider the use of a relaxation parameter strategy, proposed recently for the standard algorithms, for controlling the semiconvergence of the projected algorithms. We demonstrate the semiconvergence and the performance of our strategies by examples taken from tomographic imaging. © 2012 Society for Industrial and Applied Mathematics.

KW - Algorithms

KW - Parameter estimation

KW - Tomography

KW - Iterative methods

KW - Projected Landweber iteration

KW - Simultaneous iterative reconstruction technique

KW - Relaxation parameters

KW - Semiconvergence

KW - Nonnegativity constraints

KW - Tomographic imaging

U2 - 10.1137/110834640

DO - 10.1137/110834640

M3 - Journal article

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SP - A2000-A2017

JO - S I A M Journal on Scientific Computing

JF - S I A M Journal on Scientific Computing

IS - 4

ER -

Semiconvergence and Relaxation Parameters for Projected SIRT Algorithms

Abstract

Bibliographical note

Keywords

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