Integral imaging-based cryptographic algorithms provide a new way to design secure and robust image encryption systems. In this paper, we introduce a performance-enhanced image encryption scheme based on depth-conversion integral imaging and hybrid cellular automata (CA), aiming to meet the requirements of secure image transmission. First, the input image is decomposed into an elemental image array (EIA) using the depth-converted integral imaging technique. The obtained elemental images then are encrypted by utilizing the CA model and chaotic sequence. The conventional computational integral imaging reconstruction (CIIR) technique is a pixel-superposition technique. The resolution of the reconstructed image is dramatically degraded by the large magnification factor in the superposition process as the pickup distance increases. In the proposed reconstruction process, the pixel mapping technique is introduced to solve these problems. A novel property of the proposed scheme is its depth-conversion property, which reconstructs an elemental image originally recorded at long distances from the pinhole array as one that was recorded near the pinhole array and consequently reduces the magnification factor. The results of numerical simulations demonstrate the effectiveness and security of the proposed scheme. HighlightsChaotic image encryption based on the pixel mapping method.Proposed method improves robustness against data loss attacks.Cellular automata provides high-key space encryption algorithm.
['Xiao-Wei Li', 'Chengqing Li', 'In-Kwon Lee']
Chaotic image encryption using pseudo-random masks and pixel mapping