An optical image encryption scheme based on depth-conversion integral imaging and chaotic maps
This work addresses secure image transmission for applications like medical imaging or surveillance, but it is incremental as it builds on existing integral imaging and chaotic map methods.
The paper tackled the problem of degraded resolution in integral imaging-based image encryption by proposing a scheme that uses depth-conversion to reduce magnification factors, resulting in improved image quality and security as demonstrated in simulations.
Integral imaging-based cryptographic algorithms provides a new way to design secure and robust image encryption schemes. In this paper, we introduce a performance-enhanced image encryption schemes based on depth-conversion integral imaging and chaotic maps, aiming to meet the requirements of secure image transmission. First, the input image is decomposed into an elemental image array (EIA) by utilizing a pinhole array. Then, the obtained image are encrypted by combining the use of cellular automata and chaotic logistic maps. In the image reconstruction process, the conventional computational integral imaging reconstruction (CIIR) technique is a pixel-superposition technique; the resolution of the reconstructed image is dramatically degraded due to the large magnification in the superposition process as the pickup distance increases. The smart mapping technique is introduced to improve the problem of CIIR. A novel property of the proposed scheme is its depth-conversion ability, which converts original elemental images recorded at long distance to ones recorded near the pinhole array and consequently reduce the magnification factor. The results of numerical simulations demonstrate the effectiveness and security of this proposed scheme.