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Quantifying Intermembrane Distances with Serial Image Dilations

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

A Secure and Efficient Scalable Secret Image Sharing Scheme with Flexible Shadow Sizes.

Dong Xie^1,2,3, Lixiang Li^1,3, Haipeng Peng^1,3

¹Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China.

|January 11, 2017

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This study introduces a new scalable secret image sharing (SSIS) scheme using compressed sensing. It offers flexible shadow sizes, noise resilience, and improved security for image sharing applications.

Area of Science:

Cryptography
Image Processing
Information Security

Background:

Existing scalable secret image sharing (SSIS) schemes often produce large image shadows.
Current SSIS methods lack flexibility in adjusting shadow size and are vulnerable to noise.

Purpose of the Study:

To develop a novel SSIS scheme addressing limitations of existing methods.
To introduce flexibility in shadow size and enhance noise resilience in secret image sharing.

Main Methods:

A new SSIS scheme is proposed utilizing compressed sensing technology.
The scheme allows for a trade-off between shadow size and reconstructed image quality.

Main Results:

The proposed SSIS scheme demonstrates flexibility in managing shadow sizes.

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Last Updated: Mar 9, 2026

Quantifying Intermembrane Distances with Serial Image Dilations

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

The scheme exhibits smooth scalability, noise-resilient capabilities, and high security.

Conclusions:

The novel SSIS scheme based on compressed sensing offers significant advantages over existing methods.
Experimental results validate the feasibility and superiority of the proposed scheme for secure and scalable image sharing.