Flaw Detection Using a Priori Knowledge with Limited View Aperture System

dc.contributor.author Safaeinili, Ali
dc.contributor.author Basart, John
dc.date 2018-02-14T03:31:21.000
dc.date.accessioned 2020-06-30T06:37:44Z
dc.date.available 2020-06-30T06:37:44Z
dc.date.copyright Mon Jan 01 00:00:00 UTC 1990
dc.date.issued 1990
dc.description.abstract <p>In CT imaging with limited view-angle data, the image of the object’s slice is usually distorted such that it is difficult to interpret the image. Usually in industrial applications. one deals with quality testing of products which are built from on an original blueprint or model. The objective of this paper is to use the knowledge about the model and try to establish whether there is any significant difference between the object under test and the model object. We will first formulate the problem as a deconvolution problem. Then we will use the CLEAN deconvolution algorithm to restore the image.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/qnde/1990/allcontent/92/
dc.identifier.articleid 1566
dc.identifier.contextkey 5777087
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath qnde/1990/allcontent/92
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/59736
dc.language.iso en
dc.relation.ispartofseries Review of Progress in Quantitative Nondestructive Evaluation
dc.source.bitstream archive/lib.dr.iastate.edu/qnde/1990/allcontent/92/1990_SafaeiniliA_FlawDetectionPriori.pdf|||Sat Jan 15 02:29:37 UTC 2022
dc.source.uri 10.1007/978-1-4684-5772-8_92
dc.subject.disciplines Electromagnetics and Photonics
dc.subject.disciplines Signal Processing
dc.subject.keywords Electrical and Computer Engineering
dc.subject.keywords CNDE
dc.title Flaw Detection Using a Priori Knowledge with Limited View Aperture System
dc.type event
dc.type.genre article
dspace.entity.type Publication
relation.isSeriesOfPublication 289a28b5-887e-4ddb-8c51-a88d07ebc3f3
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