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231223s2010 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2009.2030955
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|a eng
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|a Kybic, Jan
|e verfasserin
|4 aut
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|a Bootstrap resampling for image registration uncertainty estimation without ground truth
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|c 2010
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|a Text
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|a ƒaComputermedien
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|a Date Completed 18.02.2010
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|a Date Revised 16.12.2009
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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|a We address the problem of estimating the uncertainty of pixel based image registration algorithms, given just the two images to be registered, for cases when no ground truth data is available. Our novel method uses bootstrap resampling. It is very general, applicable to almost any registration method based on minimizing a pixel-based similarity criterion; we demonstrate it using the SSD, SAD, correlation, and mutual information criteria. We show experimentally that the bootstrap method provides better estimates of the registration accuracy than the state-of-the-art CramEr-Rao bound method. Additionally, we evaluate also a fast registration accuracy estimation (FRAE) method which is based on quadratic sensitivity analysis ideas and has a negligible computational overhead. FRAE mostly works better than the CramEr-Rao bound method but is outperformed by the bootstrap method
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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|g 19(2010), 1 vom: 15. Jan., Seite 64-73
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