Speckle-based optical encryption with complex-amplitude coding and deep learning.

We propose a speckle-based optical encryption scheme by using complex-amplitude coding and deep learning, which enables the encryption and decryption of complex-amplitude plaintext containing both amplitude and phase images. During encryption, the amplitude and phase images are modulated using a superpixel-based coding technique and feded into a digital micromirror device. After passing through a 4f system, the information undergoes disturbance modulation by a scattering medium, resulting in a diffracted speckle pattern serving as the ciphertext. A Y-shaped convolutional network (Y-Net) model is constructed to establish the mapping relationship between the complex-amplitude plaintext and ciphertext through training. During decryption, the Y-Net model is utilized to quickly extract high-quality amplitude and phase images from the ciphertext. Experimental results verify the feasibility and effectiveness of our proposed method, demonstrating that the potential of integrating speckle encryption and deep learning for optical complex-amplitude encryption.