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231223s2008 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2008.2001405
|2 doi
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|a pubmed24n0606.xml
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|a (NLM)18713673
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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 |
1 |
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|a Monaco, James Peter
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Nonlinearities in stereoscopic phase-differencing
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| 264 |
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|c 2008
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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| 500 |
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|a Date Completed 23.09.2008
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|a Date Revised 20.08.2008
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|a published: Print
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|a Citation Status MEDLINE
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| 520 |
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|a Exploiting the quasi-linear relationship between local phase and disparity, phase-differencing registration algorithms provide a fast, powerful means for disparity estimation. Unfortunately, these phase-differencing techniques suffer a significant impediment: phase nonlinearities. In regions of phase nonlinearity, the signals under consideration possess properties that invalidate the use of phase for disparity estimation. This paper uses the amenable properties of Gaussian white noise images to analytically quantify these properties. The improved understanding gained from this analysis enables us to better understand current methodologies for detecting regions of phase instability. Most importantly, we introduce a new, more effective means for identifying these regions based on the second derivative of phase
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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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| 700 |
1 |
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|a Bovik, Alan Conrad
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Cormack, Lawrence K
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 17(2008), 9 vom: 24. Sept., Seite 1672-84
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
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| 773 |
1 |
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|g volume:17
|g year:2008
|g number:9
|g day:24
|g month:09
|g pages:1672-84
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|u http://dx.doi.org/10.1109/TIP.2008.2001405
|3 Volltext
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|d 17
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|h 1672-84
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