NDLI: Secondary image reconstruction based on Associative Markov Networks for electrical resistance tomography

Content Provider	IEEE Xplore Digital Library
Author	Jiamin Ye Hoyle, B.S.
Copyright Year	2012
Description	Author affiliation: School of Process, Environmental and Materials Eng., University of Leeds, UK (Jiamin Ye; Hoyle, B.S.)
Abstract	The images reconstructed by electrical resistance tomography for two-phase flow with distinctive phase origins are usually blurred at the phase interface. To improve the image quality, secondary image reconstruction with Associative Markov Networks (AMNs) is presented. The initial images are reconstructed by the Landweber iteration algorithm. The obtained images are then processed using AMNs. The weights of AMNs are learned by a quadratic program and then a min-cut is used for the maximum a posteriori inference to obtain the optimal images. Simulation results from both noise-free and noisy data show significant improvement in the phase interface of images. For some conductivity distributions, the image errors can be reduced to a fifth of the initial values.
Starting Page	482
Ending Page	487
File Size	920697
Page Count	6
File Format	PDF
ISBN	9781457717765
e-ISBN	9781457717758
DOI	10.1109/IST.2012.6295495
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-16
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image reconstruction Markov random fields Conductivity Vectors Imaging phantoms Electrodes Phantoms regularization associative Markov networks electrical resistance tomography secondary imaging
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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