Deep-learning-based optical image hiding Article Swipe
Jiaosheng Li
,
Yuhui Li
,
Ju Li
,
Qinnan Zhang
,
Guo Yang
,
Shimei Chen
,
Chen Wang
,
Jun Li
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2003.04130
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2003.04130
A novel framework of optical image hiding based on deep learning (DL) is proposed in this paper, and hidden information can be reconstructed from an interferogram by using an end to end network with high-quality. By using the prior data between the hidden image and the object image, a generative adversarial network was trained so that it can learn the hiding model, which resulting in only an interferogram needs to be transmitted and recorded to reconstruct image. Moreover, reconstruction process can be obtained without the parameters in optical inverse diffraction and the reconstruction result will not be affected by the phase shifts deviation and noise, which is convenient for practical application. The feasibility and security of the proposed method are demonstrated by the optical experiment results.
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Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2003.04130
- https://arxiv.org/pdf/2003.04130
- OA Status
- green
- Cited By
- 5
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3010227479
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3010227479Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2003.04130Digital Object Identifier
- Title
-
Deep-learning-based optical image hidingWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-03-05Full publication date if available
- Authors
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Jiaosheng Li, Yuhui Li, Ju Li, Qinnan Zhang, Guo Yang, Shimei Chen, Chen Wang, Jun LiList of authors in order
- Landing page
-
https://arxiv.org/abs/2003.04130Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2003.04130Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2003.04130Direct OA link when available
- Concepts
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Artificial intelligence, Computer science, Image (mathematics), Information hiding, Computer vision, Deep learning, Process (computing), Iterative reconstruction, Image restoration, Object (grammar), Inverse, Noise (video), Pattern recognition (psychology), Image processing, Mathematics, Geometry, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1, 2023: 1, 2022: 2, 2021: 1Per-year citation counts (last 5 years)
- References (count)
-
23Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.novel | 1 |
| abstract_inverted_index.phase | 100 |
| abstract_inverted_index.prior | 38 |
| abstract_inverted_index.using | 27, 36 |
| abstract_inverted_index.which | 62, 105 |
| abstract_inverted_index.hidden | 18, 42 |
| abstract_inverted_index.hiding | 6, 60 |
| abstract_inverted_index.image, | 47 |
| abstract_inverted_index.image. | 76 |
| abstract_inverted_index.method | 118 |
| abstract_inverted_index.model, | 61 |
| abstract_inverted_index.noise, | 104 |
| abstract_inverted_index.object | 46 |
| abstract_inverted_index.paper, | 16 |
| abstract_inverted_index.result | 93 |
| abstract_inverted_index.shifts | 101 |
| abstract_inverted_index.between | 40 |
| abstract_inverted_index.inverse | 88 |
| abstract_inverted_index.network | 32, 51 |
| abstract_inverted_index.optical | 4, 87, 123 |
| abstract_inverted_index.process | 79 |
| abstract_inverted_index.trained | 53 |
| abstract_inverted_index.without | 83 |
| abstract_inverted_index.affected | 97 |
| abstract_inverted_index.learning | 10 |
| abstract_inverted_index.obtained | 82 |
| abstract_inverted_index.proposed | 13, 117 |
| abstract_inverted_index.recorded | 73 |
| abstract_inverted_index.results. | 125 |
| abstract_inverted_index.security | 114 |
| abstract_inverted_index.Moreover, | 77 |
| abstract_inverted_index.deviation | 102 |
| abstract_inverted_index.framework | 2 |
| abstract_inverted_index.practical | 109 |
| abstract_inverted_index.resulting | 63 |
| abstract_inverted_index.convenient | 107 |
| abstract_inverted_index.experiment | 124 |
| abstract_inverted_index.generative | 49 |
| abstract_inverted_index.parameters | 85 |
| abstract_inverted_index.adversarial | 50 |
| abstract_inverted_index.diffraction | 89 |
| abstract_inverted_index.feasibility | 112 |
| abstract_inverted_index.information | 19 |
| abstract_inverted_index.reconstruct | 75 |
| abstract_inverted_index.transmitted | 71 |
| abstract_inverted_index.application. | 110 |
| abstract_inverted_index.demonstrated | 120 |
| abstract_inverted_index.high-quality. | 34 |
| abstract_inverted_index.interferogram | 25, 67 |
| abstract_inverted_index.reconstructed | 22 |
| abstract_inverted_index.reconstruction | 78, 92 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile |