Computer-free, all-optical reconstruction of holograms using diffractive networks
Md Sadman Sakib Rahman, Aydogan Ozcan

TL;DR
This paper introduces a novel all-optical method for reconstructing holograms that eliminates twin-image artifacts instantly, using trained transmissive diffractive layers, enabling high-speed, computer-free hologram processing.
Contribution
It presents the first all-optical hologram reconstruction technique using diffractive layers trained via deep learning, removing the need for digital processing.
Findings
Successfully reconstructs unknown holograms without digital computation.
Eliminates twin-image artifacts in real-time optical processing.
Improves diffraction efficiency and depth-of-field in holography.
Abstract
Reconstruction of in-line holograms of unknown objects in general suffers from twin-image artifacts due to the appearance of an out-of-focus image overlapping with the desired image to be reconstructed. Computer-based iterative phase retrieval algorithms and learning-based methods have been used for the suppression of such image artifacts in digital holography. Here we report an all-optical hologram reconstruction method that can instantly retrieve the image of an unknown object from its in-line hologram and eliminate twin-image artifacts without using a digital processor or a computer. Multiple transmissive diffractive layers are trained using deep learning so that the diffracted light from an arbitrary input hologram is processed all-optically, through light-matter interaction, to reconstruct the image of an unknown object at the speed of light propagation and without the need for any…
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