Information security scheme using deep learning-assisted single-pixel imaging and orthogonal coding

Abstract

Providing secure and efficient transmission for multiple optical images has been an important issue in the field of information security. Here we present a hybrid image compression, encryption and reconstruction scheme based on deep learning-assisted single-pixel imaging (SPI) and orthogonal coding. In the optical SPI-based encryption, two-dimensional images are encrypted into one-dimensional bucket signals, which will be further compressed by a binarization operation. By overlaying orthogonal coding on the compressed signals, we obtain the ciphertext that allows multiple users to access with the same privileges. The ciphertext can be decoded back to the binarized bucket signals with the help of orthogonal keys. To enhance reconstruction efficiency and quality, a deep learning framework based on DenseNet is employed to retrieve the original optical images. Numerical and experimental results have been presented to verify the feasibility and effectiveness of the proposed scheme.