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231223s1992 xx ||||| 00| ||eng c |
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|a pubmed25n0593.xml
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|a (NLM)18296166
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|a DE-627
|b ger
|c DE-627
|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Galatsanos, N P
|e verfasserin
|4 aut
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| 245 |
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|a Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation
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|c 1992
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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| 338 |
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 02.10.2012
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| 500 |
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|a Date Revised 25.02.2008
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| 500 |
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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|a The application of regularization to ill-conditioned problems necessitates the choice of a regularization parameter which trades fidelity to the data with smoothness of the solution. The value of the regularization parameter depends on the variance of the noise in the data. The problem of choosing the regularization parameter and estimating the noise variance in image restoration is examined. An error analysis based on an objective mean-square-error (MSE) criterion is used to motivate regularization. Two approaches for choosing the regularization parameter and estimating the noise variance are proposed. The proposed and existing methods are compared and their relationship to linear minimum-mean-square-error filtering is examined. Experiments are presented that verify the theoretical results
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|a Journal Article
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|a Katsaggelos, A K
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 1(1992), 3 vom: 15., Seite 322-36
|w (DE-627)NLM09821456X
|x 1057-7149
|7 nnns
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| 773 |
1 |
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|g volume:1
|g year:1992
|g number:3
|g day:15
|g pages:322-36
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|d 1
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|h 322-36
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