Adaptive Gaussian Points for Faster and Better Computer-Generated Holograms

To achieve better quality and generation speed, we generate holograms from adaptively sized and placed points, modeled as 2D Gaussians. We compute them with a Rayleigh-Sommerfeld convolution directly in a compact, radially symmetric look-up table.
Author(s): | Sascha Fricke, Reinhard Caspary, Susana Castillo, Marcus Magnor |
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Published: | August 2022 |
Type: | Article in conference proceedings |
Book: | Digital Holography and Three-Dimensional Imaging (Optica Publishing Group) |
Presented at: | Digital Holography and 3-D Imaging (DH) 2022 |
Project(s): | Wave Optics Rendering |
@inproceedings{fricke2022adaptive, title = {Adaptive Gaussian Points for Faster and Better Computer-Generated Holograms}, author = {Fricke, Sascha and Caspary, Reinhard and Castillo, Susana and Magnor, Marcus}, booktitle = {Digital Holography and Three-Dimensional Imaging}, organization = {Optica Publishing Group}, pages = {W3A.4 ff.}, month = {Aug}, year = {2022} }
Authors
Sascha Fricke
ResearcherReinhard Caspary
ExternalSusana Castillo
Senior ResearcherMarcus Magnor
Director, Chair