An Image Reconstruction Algorithm Based on Regularization Optimization for Process Tomography

Author

Ding, Yong-wei ; Dong, Feng

Author_Institution

Tianjin Univ., Tianjin

Volume

3

fYear

2007

fDate

19-22 Aug. 2007

Firstpage

1717

Lastpage

1722

Abstract

An image reconstruction algorithm based on regularization optimization for process tomography is proposed in this paper. Through the comparison of the images reconstructed by linear back projection algorithm, sensitivity coefficient algorithm, singular value decomposition algorithm and the regularization optimization algorithm proposed in this paper, it is apparent that images can be reconstructed clearly and quickly by the regularization optimization algorithm. The regularization optimization algorithm is a very good image reconstruction algorithm both in image quality and the reconstruction speed.

Keywords

computerised tomography; image reconstruction; image quality; image reconstruction; linear back projection; process tomography; regularization optimization; sensitivity coefficient; singular value decomposition; Conductivity; Fluid flow measurement; Image reconstruction; Phase measurement; Projection algorithms; Reconstruction algorithms; Singular value decomposition; Tomography; Velocity measurement; Voltage measurement; Image reconstruction; Linear back projection algorithm; Regularization optimization; Sensitivity coefficient algorithm; Singular value decomposition algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2007 International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-0973-0

Electronic_ISBN

978-1-4244-0973-0

Type

conf

DOI

10.1109/ICMLC.2007.4370424

Filename

4370424