Single Exposure Optical Image Watermarking Using a cGAN Network
A single exposure optical image watermarking framework based on deep learning (DL) is proposed in this paper, and original watermark image information can be reconstructed from only single-frame watermarked hologram by using an end-to-end network with high-quality. First, the single exposure waterma...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9383841/ |
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| Summary: | A single exposure optical image watermarking framework based on deep learning (DL) is proposed in this paper, and original watermark image information can be reconstructed from only single-frame watermarked hologram by using an end-to-end network with high-quality. First, the single exposure watermarked hologram is acquired with our presented phase-shifted interferometry based optical image watermarking (PSOIW) frame, and then all holograms and corresponding watermark images are constructed to the train datasets for the learning of an end-to-end conditional generative adversarial network (cGAN), finally retrieved the watermark image well with the trained cGAN network using only one hologram. This DL-based method greatly reduces the recording or transmitting data burden by 1/4 compared with our presented PSOIW technique, and may provide a new way for the real-time 3D image/video security applications. The feasibility and security of the proposed method are demonstrated by the optical experiment results. |
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| ISSN: | 1943-0655 |