Image quality enhancement of embedded holograms in holographic information hiding using deep neural networks
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Abstract (arXiv)
Holographic information hiding is a technique for embedding holograms or images into another hologram, used for copyright protection and steganography of holograms. Using deep neural networks, we offer a way to improve the visual quality of embedded holograms. The brightness of an embedded hologram is set to a fraction of that of the host hologram, resulting in a barely damaged reconstructed image of the host hologram. However, it is difficult to perceive because the embedded hologram's reconstructed image is darker than the reconstructed host image. In this study, we use deep neural networks to restore the darkened image.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 23 references that are in the map. First posted on arXiv 20 Dec 2021.
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References · 2
- 2015Deep Residual Learning for Image Recognitioncited by 52,096
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
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