Multiple-image encryption and hiding with an optical diffractive neural network
arXiv:1902.07985 · doi:10.1016/j.optcom.2020.125476
Abstract
A cascaded phase-only mask architecture (or an optical diffractive neural network) can be employed for different optical information processing tasks such as pattern recognition, orbital angular momentum (OAM) mode conversion, image salience detection and image encryption. However, for optical encryption and watermarking applications, such a system usually cannot process multiple pairs of input images and output images simultaneously. In our proposed scheme, multiple input images can be simultaneously fed to an optical diffractive neural network (DNN) system and each corresponding output image will be displayed in a non-overlap sub-region in the output imaging plane. Each input image undergoes a different optical transform in an independent channel within the same system. The multiple cascaded phase masks in the system can be effectively optimized by a wavefront matching algorithm. Similar to recent optical pattern recognition and mode conversion works, the orthogonality property is employed to design a multiplexed DNN.
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Cited by in corpus (5)
- Optical secret sharing with cascaded metasurface holography
- Polarized deep diffractive neural network for classification, generation, multiplexing and de-multiplexing of orbital angular momentum modes
- Complex-valued universal linear transformations and image encryption using spatially incoherent diffractive networks
- Express Wavenet -- a low parameter optical neural network with random shift wavelet pattern
- Phase-multiplexed optical computing: Reconfiguring a multi-task diffractive optical processor using illumination phase diversity