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13 March 2024 Transferring optical information through random unknown diffusers using a diffractive decoder with electronic encoding
Bijie Bai, Heming Wei, Xilin Yang, Tianyi Gan, Deniz Mengu, Mona Jarrahi, Aydogan Ozcan, Yuhang Li
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Proceedings Volume PC12903, AI and Optical Data Sciences V; PC129030V (2024) https://doi.org/10.1117/12.3000579
Event: SPIE OPTO, 2024, San Francisco, California, United States
Abstract
We present a diffractive network (D2NN) design to all-optically perform distinct transformations for different input data classes. This class-specific transformation D2NN processes the input optical field, generating the output optical field whose amplitude or intensity closely approximates the transformed/encrypted version of the input using a transformation matrix specific to the corresponding data class. The original information can be recovered only by applying the class-specific decryption keys to the corresponding class at the diffractive network's output field-of-view. The efficacy of the presented class-specific image encryption framework was validated both numerically and experimentally, tested at 1550 nm and 0.75 mm wavelengths.
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Bijie Bai, Heming Wei, Xilin Yang, Tianyi Gan, Deniz Mengu, Mona Jarrahi, Aydogan Ozcan, and Yuhang Li "Transferring optical information through random unknown diffusers using a diffractive decoder with electronic encoding", Proc. SPIE PC12903, AI and Optical Data Sciences V, PC129030V (13 March 2024); https://doi.org/10.1117/12.3000579
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KEYWORDS
Optical networks
Image encryption
Information visualization
Visual optics
Channel projecting optics
Design and modelling
Optical computing
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