Abstract
Even for reasonably sized three-dimensional (3D) images, image registration becomes a computationally intensive task. Here, we introduce and explore the concept of octrees for registration which drastically reduces the amount of processed data and thus the computational costs. We show how to map the registration problem onto an octree and present a suitable optimization technique. Furthermore, we demonstrate the performance of the new approach by academic (twodimensional) as well as real life (3D) examples. These examples indicate that the computational time can be reduced by a factor of 3-4 compared with standard approaches.
| Originalsprache | Englisch |
|---|---|
| Zeitschrift | SIAM Journal on Scientific Computing |
| Jahrgang | 29 |
| Ausgabenummer | 5 |
| Seiten (von - bis) | 2008-2023 |
| Seitenumfang | 16 |
| ISSN | 1064-8275 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 01.12.2007 |
UN SDGs
Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung
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SDG 9 – Industrie, Innovation und Infrastruktur
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