Journal
OPTICS LETTERS
Volume 47, Issue 18, Pages 4762-4765Publisher
Optica Publishing Group
DOI: 10.1364/OL.469466
Keywords
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Funding
- National Natural Science Foundation of China
- Sichuan University
- [61975138]
- [U20A20215]
- [2020SCUNG205]
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This study proposes a light-field 3D encryption scheme based on monocular depth rendering, which utilizes a convolution residuals network (CRN) to generate depth maps and applies reversible state loop cellular automata (RSL-CA) for RGB image encryption. Experimental results demonstrate the effectiveness of the proposed method in optical 3D reconstruction.
The real-time performance of light-field 3D encryption tech-nology based on the integral imaging principle is restricted by the acquisition speed and the data of the elemental image array (EIA). Herein, we propose a light-field 3D encryp-tion scheme based on monocular depth rendering. With the help of a convolution residuals network (CRN), the pro-posed scheme can generate the corresponding depth map from a single RGB image and simplify the pickup process of the EIA according to the image mapping. For encryption, using reversible state loop cellular automata (RSL-CA) to encrypt a single RGB image updates traditional 3D encryp-tion, greatly improving the security and efficiency of the encryption algorithm. It is experimentally demonstrated that optical 3D reconstruction is clear and brightly colorful and also has a good parallax effect. The proposed method can open a brand-new research perspective for light-field 3D encryption.(c) 2022 Optica Publishing Group
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