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.
|Publisher||Department of Computer Science, University of Copenhagen|
|Number of pages||8|
|Publication status||Published - 2011|
|Series||Koebenhavns Universitet. Datalogisk Institut. Rapport|