Optical scanning cryptography (OSC) is an optical image encryption method encrypting information incoherently based on two-pupil heterodyne scanning optical system. But numerical reconstruction of a 3-D volumetric image from an optical scanned hologram is a difficult task. The main problems are the intensive computational load, and the heavy blurring of each reconstructed section with the defocused noise from other sections.In this talk, we propose a deep-learning based reconstruction algorithm in optical scanning holography, which can generate reconstruction images in high quality. DNNs are created based on the U-net structure to learn the mapping between holograms and reconstruction images. Simulation and experimental results showed that the deep-learning based method is able to reconstruct the optical scanning hologram in real time for the removal of defocus noise.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.