Optical image conversion and encryption based on structured light illumination and a diffractive neural network

Abstract

In this paper, an optical image encryption method is proposed based on structured light illumination and a diffractive neural network (DNN), which can realize conversion between different images. With the use of the structured phase mask (SPM) in the iterative phase retrieval algorithm, a plaintext image is encoded into a DNN composed of multiple phase-only masks (POMs) and ciphertext. It is worth noting that ciphertext is a visible image such that the conversion of one image to another is achieved, leading to high concealment of the proposed optical image encryption method. In addition, the wavelength of the illuminating light, all Fresnel diffraction distances, the optical parameters of the adopted SPM such as focal length and topological charge number, as well as all POMs in the DNN are all considered as security keys in the decryption process, contributing to a large key space and high level of security. Numerical simulations are performed to demonstrate the feasibility of the proposed method, and simulation results show that it exhibits high feasibility and safety as well as strong robustness.