Sparse point spread function-based multi-image optical encryption
Ning Xu, Dalong Qi, Long Cheng, Zhen Hua Pan, Cheng Zhou, Wenzhang Lin, Hongmei Ma, Yunhua Yao, Yuecheng Shen, Lianzhong Deng, Zhenrong Sun, Shian Zhang · Communications Physics · 2025
Multi-image optical encryption (MOE) has demonstrated promising potential in image data protection owing to its parallel processing capability and abundant degrees of freedom. However, existing methods suffer from either low compression ratios or stringent experimental conditions, such as accurate calibration of phase modulation, precise manufacturing of encryption elements, and no ambient light interference. This work introduces a lensless sparse point spread function-based multi-image optical encryption (sPSF-MOE) technique that addresses these challenges and enhances performance. In the encryption process, each plaintext image is encoded using a sparsely distributed PSF with specifically designed geometric shapes through spatial phase engineering. The resulting ciphertexts are superimposed to produce a compressed ciphertext. During decryption, an iterative algorithm recovers encrypted images with improved reconstruction quality. We show that sPSF-MOE ensures high fidelity for binary (gray-scale) images at a compression ratio of 12 (6) and resists autocorrelation-based attacks. Integrating principal component analysis (PCA) into decryption preserves image high fidelity under ambient light interference. sPSF-MOE reduces the bandwidth requirement for data transmission while ensuring data integrity. Optical encryption is used to protect image data but often struggles with low compression or strict experimental setups. The authors introduce a lensless method that securely encrypts multiple images with high compression and robustness, using smart point spread patterns and compressed sensing algorithms.