Optimization Methods for In-Line Holography
We present a procedure to reconstruct objects from holograms recorded in in-line holography settings. Working with one beam of polarized light, the topological derivatives and energies of functionals quantifying hologram deviations yield predictions of the number, location, shape and size of objects...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/13415 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/13415 |
| Access Level: | acceso abierto |
| Palabra clave: | 517.9 Holography Light imaging Inverse scattering Topological energy Topological derivative Cellular structures Soft matter Microscale Nanoscale Óptica (Física) Análisis funcional y teoría de operadores Análisis numérico Ecuaciones diferenciales 2209.19 Óptica Física 1206 Análisis Numérico 1202.07 Ecuaciones en Diferencias |
| Sumario: | We present a procedure to reconstruct objects from holograms recorded in in-line holography settings. Working with one beam of polarized light, the topological derivatives and energies of functionals quantifying hologram deviations yield predictions of the number, location, shape and size of objects with nanometer resolution. When the permittivity of the objects is unknown, we approximate it by parameter optimization techniques. Iterative procedures combining topological field based geometry corrections and parameter optimization sharpen the initial predictions. Additionally, we devise a strategy which exploits the measured holograms to produce numerical approximations of the full electric field (amplitude and phase) at the screen where the hologram is recorded. Shape and parameter optimization of functionals employing such approximations of the electric field also yield images of the holographied objects. |
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