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Optical multiple-image authentication based on computational ghost imaging and hybrid non-convex second-order total

Yaoling Zhou, Yueer Sun, Mu Yang

|June 29, 2023

Summary

This study introduces a novel optical security method for multiple-image authentication using computational ghost imaging. The technique efficiently embeds and verifies multiple images even at low sampling rates, offering robust security.

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Area of Science:

Optics and Photonics
Information Security
Digital Image Processing

Background:

Secure authentication of multiple digital images is crucial in various applications.
Existing methods often face challenges with robustness and efficiency.

Purpose of the Study:

To propose a novel optical security method for multiple-image authentication.
To enhance security and robustness against image degradation and low sampling ratios.

Main Methods:

Computational ghost imaging for image encoding and sparse data extraction.
Wavelet transform and singular value decomposition (SVD) for data embedding.
Generalized Arnold transform for scrambling data.
Hybrid non-convex second-order total variation for image reconstruction and authentication.

Main Results:

Successful embedding and retrieval of multiple images with high fidelity.
Efficient verification even at a low sampling ratio of 6% using nonlinear correlation maps.
Demonstrated robustness against Gaussian and sharpen filters through optical experiments.

Conclusions:

The proposed method offers a secure and robust solution for multiple-image authentication.
It provides an effective alternative to existing optical security techniques.
The novel approach of embedding sparse data using cascaded SVDs enhances security and resilience.