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|a (DE-627)NLM161105904
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|a (NLM)16519347
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
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|a Nagy, James G
|e verfasserin
|4 aut
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|a Kronecker product approximation for preconditioning in three-dimensional imaging applications
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|c 2006
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|a Text
|b txt
|2 rdacontent
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 30.03.2006
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|a Date Revised 10.12.2019
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|a published: Print
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|a Citation Status MEDLINE
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|a We derive Kronecker product approximations, with the help of tensor decompositions, to construct approximations of severely ill-conditioned matrices that arise in three-dimensional (3-D) image processing applications. We use the Kronecker product approximations to derive preconditioners for iterative regularization techniques; the resulting preconditioned algorithms allow us to restore 3-D images in a computationally efficient manner. Through examples in microscopy and medical imaging, we show that the Kronecker approximation preconditioners provide a powerful tool that can be used to improve efficiency of iterative image restoration algorithms
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|a Evaluation Study
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|a Journal Article
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|a Research Support, U.S. Gov't, Non-P.H.S.
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|a Kilmer, Misha E
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 15(2006), 3 vom: 07. März, Seite 604-13
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
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| 773 |
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|g volume:15
|g year:2006
|g number:3
|g day:07
|g month:03
|g pages:604-13
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|d 15
|j 2006
|e 3
|b 07
|c 03
|h 604-13
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