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Updated: Oct 16, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

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Published on: July 5, 2024

Image Encryption Scheme Based on Multiscale Block Compressed Sensing and Markov Model.

Yuandi Shi¹, Yinan Hu¹, Bin Wang¹

¹The Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Dalian 116622, China.

Entropy (Basel, Switzerland)

|October 23, 2021

Summary

This study introduces a novel multiscale block compressed sensing image encryption scheme. It enhances decrypted image quality by using varied sampling rates for different image frequencies, improving security and reconstruction accuracy.

Keywords:

Markov model image encryption multiscale block compressed sensing state transition matrix

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Area of Science:

Cryptography
Image Processing
Signal Processing

Background:

Existing compressed sensing image encryption methods often yield poor decrypted image quality.
A need exists for more robust and secure image encryption techniques with high reconstruction fidelity.

Purpose of the Study:

To develop an advanced image encryption scheme using multiscale block compressed sensing.
To improve the quality of decrypted images compared to existing methods.

Main Methods:

Image decomposition using three-level wavelet transform.
Calculation of sampling rates for coefficient matrices based on multiscale block compressed sensing theory.
Two rounds of permutation on coefficient matrices and the combined matrix.
Application of independent and forward-backward diffusion for pixel-level encryption.
Setting different sampling rates for low- and high-frequency image components.

Main Results:

The proposed scheme achieves superior decrypted image reconstruction quality.
Demonstrates excellent encryption effect and resistance to various attacks.
Leverages the randomness of the Markov model for enhanced security.

Conclusions:

Multiscale block compressed sensing offers a viable approach to enhance image encryption quality.
Differentiated sampling rates based on image frequency content are crucial for improved reconstruction.
The developed scheme provides a secure and effective solution for image encryption.