Abstract
Augmented reality (AR) microscopes assist users in analyzing microscopic specimens by overlaying virtual information onto the captured images. Typically, this approach requires continuous scene analysis and computational processing, which limits real-time performance and introduces significant computational overhead. We introduce an all-optical alternative by proposing a new phase optimization scheme integrated into AR microscopes. Our optimizations rely on creating a precomputed library of phase maps for a spatial light modulator (SLM). Each phase map is configured to selectively enhance a specific shape or size class in a scene, eliminating per-frame computational requirements. Furthermore, by leveraging the inherent shift-invariant property of Fourier optical systems, our phase masks maintain a selective augmentation of the target object during in-plane translations within the field of view (FoV) without explicit tracking algorithms. Our results demonstrate selective target highlighting based on object size or shape, enabling continuous real-time observation in microscopy systems.
Maha Sahloul
Graduate Research Assistant
My research interests include digital holography, quantitative phase imaging, and Spatial Light Modulators (SLMs)
M. Fatih Toy
Associate Professor of Electrical and Electronics Engineering
My research interests include digital holography, quantitative phase imaging, optical diffraction tomography and optical superresolution.