Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Computed Tomography01:10

Computed Tomography

7.6K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
7.6K
Convolution Properties I01:20

Convolution Properties I

372
Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
372

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Federated Learning Backdoor Attack Based on Frequency Domain Injection.

Entropy (Basel, Switzerland)·2024
Same author

Stable and Fast Deep Mutual Information Maximization Based on Wasserstein Distance.

Entropy (Basel, Switzerland)·2023
Same author

Secure Ring Signature Scheme for Privacy-Preserving Blockchain.

Entropy (Basel, Switzerland)·2023
Same author

Wasserstein Distance-Based Deep Leakage from Gradients.

Entropy (Basel, Switzerland)·2023
Same author

Image Adversarial Example Generation Method Based on Adaptive Parameter Adjustable Differential Evolution.

Entropy (Basel, Switzerland)·2023
Same author

A Parallel Multi-Modal Factorized Bilinear Pooling Fusion Method Based on the Semi-Tensor Product for Emotion Recognition.

Entropy (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Nov 19, 2025

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.9K

An Efficient Plaintext-Related Chaotic Image Encryption Scheme Based on Compressive Sensing.

Zhen Li1,2, Changgen Peng1, Weijie Tan1

  • 1College of Computer Science and Technology, State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025, China.

Sensors (Basel, Switzerland)
|January 27, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel image encryption method combining chaotic maps and compressive sensing for simultaneous compression and security. The proposed scheme offers superior security and compression performance for network applications.

Keywords:
chaotic systemcompressive sensingimage encryptionplaintext related

More Related Videos

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
07:56

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

8.8K

Related Experiment Videos

Last Updated: Nov 19, 2025

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.9K
A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
07:56

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

8.8K

Area of Science:

  • Computer Science
  • Information Security
  • Image Processing

Background:

  • Mobile networks (5G/6G) necessitate secure and efficient digital image handling.
  • High-resolution images strain bandwidth and cloud storage.
  • Existing methods often lack simultaneous compression and encryption.

Purpose of the Study:

  • To propose an efficient and secure plaintext-related chaotic image encryption scheme.
  • To achieve simultaneous compression and encryption of digital images.
  • To enhance digital image security and reduce storage/bandwidth requirements.

Main Methods:

  • Key generation using plain image and initial key.
  • Discrete Wavelet Transform for coefficient matrix conversion.
  • Permutation and diffusion using chaotic maps (2D-SLIM, 2D-LSCM).
  • Plaintext-related compressive sensing with a 2D-SLIM generated measurement matrix.

Main Results:

  • The scheme achieves simultaneous compression and encryption.
  • Demonstrates excellent security performance with low correlation and uniform distribution.
  • Exhibits superior compression efficiency compared to recent works.
  • Quantified measurement results to 0-255 for cipher image uniformity.

Conclusions:

  • The proposed scheme effectively balances security and compression for network image applications.
  • Offers a viable solution for secure and efficient image transmission in modern networks.
  • Outperforms existing methods in both security and compression metrics.