Abstract
A large-scale, nonlinear image registration problem can be partitioned into smaller independent subproblems by adding a global, coarsely discretized distance measure. The remaining inconsistencies between subdomains are smaller than without the coarse distance term and can be incorporated into the global solution by a blending method. Reaching a similar accuracy, the new method enables the registration of large-scale images that could otherwise not be computed.
Original language | English |
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Qualification | Doctorate / Phd |
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Award date | 30.04.2020 |
Publication status | Published - 05.05.2020 |