Jacobians for Lebesgue registration for a range of similarity measures
Research output: Book/Report › Report › Research
In [Darkner and Sporring, 2011] was presented a framework based on locally orderless images and Lebesgue integration resulting in a fast algorithm for registration using normalized mutual information as dissimilarity measure. This report extends the algorithm to arbitrary complex similarity measures and supplies the full derivatives of a range of common dissimilarity measures as well as their obvious extensions.
Original language | English |
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Publisher | Department of Computer Science, University of Copenhagen |
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Number of pages | 8 |
Publication status | Published - 2011 |
Series | Koebenhavns Universitet. Datalogisk Institut. Rapport |
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Number | 04/2011 |
ISSN | 0107-8283 |
ID: 45953557