Computational Imaging Encryption with a Steganographic and Holographic Authentication Strategy

Robust data security is of paramount importance, particularly for highly classified information. To achieve this, advanced encryption and decryption methods, along with stringent access control and physical security measures, are essential to mitigate the risk of unauthorized access and data exposure. Ghost imaging (GI), a computational imaging technique that operates indirectly, offers a distinct approach compared to traditional spatially resolved imaging techniques. By utilizing computational algorithms, GI enables indirect image reconstruction, making it well-suited for encryption applications. This proposal introduces a new computational imaging encryption scheme that combines Fourier ghost imaging (FGI) and computational holography. The scheme utilizes an untrained-tree-network to generate two camouflaged computer-generated holograms (CGHs). Integration of CGH-based steganography and holographic authentication enhances the encoding and decoding processes of FGI encryption. The effectiveness and security of the proposed scheme are rigorously validated through numerical simulations and optical experiments. The results demonstrate promising potential for effectively merging direct and indirect imaging methods in security applications. Wang and colleagues present an advanced computational imaging encryption scheme that merges Fourier ghost imaging with computational holography. This approach combines direct and indirect imaging techniques and incorporates deep neural network, resulting in improved data access control and reinforced physical security measures. The results demonstrate the promising potential of computational imaging in security applications. image