The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Double random fractional Fourier-domain encoding for optical security
Abstract
We propose a new optical encryption technique using the fractional Fourier transform. In this method, the data are encrypted to a stationary white noise by two statistically independent random phase masks in fractional Fourier domains. To decrypt the data correctly, one needs to specify the fractional domains in which the input plane, encryption plane, and output planes exist, in addition to the key used for encryption. The use of an anamorphic fractional Fourier transform for the encryption of two-dimensional data is also discussed. We suggest an optical implementation of the proposed idea. Results of a numerical simulation to analyze the performance of the proposed method are presented.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Ozaktas, H. M., & Aytür, O. (1995) · Signal Processing · doi:10.1016/0165-1684(95)00076-p · Cited by 141
Cited by
Optical image encryption by random shifting in fractional Fourier domains
Hennelly, B., & Sheridan, J. T. (2003) · Optics Letters · doi:10.1364/ol.28.000269 · Cited by 425
A review of optical image encryption techniques
Liu, S., Guo, C., & Sheridan, J. T. (2014) · Optics & Laser Technology · doi:10.1016/j.optlastec.2013.05.023 · Cited by 406
A technique for image encryption using digital signature
Sinha, A., & Singh, K. (2003) · Optics Communications · doi:10.1016/s0030-4018(03)01261-6 · Cited by 131
Kaur, G., Agarwal, R., & Patidar, V. (2022) · The Visual Computer · doi:10.1007/s00371-021-02066-w · Cited by 78
Metadata
- Authors
- Unnikrishnan, G.
- Venue
- Optical Engineering
- Publisher
- SPIE-Intl Soc Optical Eng
- Published
- 2000-11-01
- Volume
- 39
- Issue
- 11
- Pages
- 2853
- ISSN
- 0091-3286 (ISSN-L)
- OpenAlex
- W2122651704
- Cited by
- 218
- References
- 1
- FWCI
- 5.70
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Double random fractional Fourier-domain encoding for optical security. https://app.cochat.ai/papers/10.1117/1.1313498
- The paper
- Unnikrishnan, G. (2000). Double random fractional Fourier-domain encoding for optical security. Optical Engineering. https://doi.org/10.1117/1.1313498
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
