Image quality enhancement of embedded holograms in holographic information hiding using deep neural networks

• URL: http://arxiv.org/abs/2112.11246v1
• Date: Mon, 20 Dec 2021 01:21:28 GMT
• Title: Image quality enhancement of embedded holograms in holographic information hiding using deep neural networks
• Authors: Tomoyoshi Shimobaba and Sota Oshima and Takashi Kakue and and Tomoyoshi Ito
• Abstract summary: 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. 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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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