Progressive Reconstruction on Region-Based Secret Image Sharing

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(Formula presented.) threshold progressive secret image sharing (PSIS) has become an important issue in recent years. In (Formula presented.) PSIS, a secret image is encrypted into n shadows such that k to n shadows can gradually reconstruct the secret image. Since an image can usually be divided into different regions in such a way that each region includes information with different importance levels, region-based PSIS has also been proposed where the reconstruction of different regions requires different thresholds on the shadow numbers. In this work, we propose new region-based (Formula presented.) PSIS that achieves a novel reconstruction model, where all regions possess the property of (Formula presented.) threshold progressive reconstruction, but the same number of shadows recovers a lower proportion of information in regions with a higher importance level. This new reconstruction model can further complete the application of region-based PSIS, where each region has an equal minimum threshold for reconstruction, and the difference in importance levels between regions can be reflected in the proportion of the recovered image using the same number of shadows. A theoretical analysis proves the correctness of the proposed scheme, and the experimental results from four secret images also show the practicality and effectiveness of the proposed scheme.

OriginalsprogEngelsk
Artikelnummer1529
TidsskriftElectronics (Switzerland)
Vol/bind13
Udgave nummer8
Antal sider10
DOI
StatusUdgivet - 2024

Bibliografisk note

Funding Information:
This research was funded in part by the Natural Science Foundation of China under Grant 62172331; the Youth Innovation Team of Shaanxi Universities (No.: 2019-38); the Natural Science Foundation of Sichuan Province (Nos.: 2022NSFSC0554, 2022NSFSC0549, and 2023NSFSC0502); the Youth Innovation Team Construction of the Shaanxi Provincial Department of Education under Grants 21JP081 and 22JP059; the Natural Science Foundation of Shaanxi under Grant 2023-YBGY-271; the Guangxi Key Laboratory of Trusted Software (No.: KX202036); and the Xi\u2019an Science and Technology Plan under Grant 22GXFW0083, 22GXFW0079.

Publisher Copyright:
© 2024 by the authors.

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