Secure Color Traffic Image Transmission Through Enhanced Visual Encryption
ABSTRACT With the rapid advancement of intelligent transportation systems (ITS), secure processing of color traffic images has become critical for traffic management, safety monitoring, and flow analysis. However, ITS are increasingly susceptible to malicious attacks and data tampering. To address this, we propose an advanced visual encryption method specifically for color traffic images. Our approach employs discrete wavelet transform (DWT) to represent images sparsely, followed by dynamic three‐dimensional spiral disruption for encryption. Chaotic systems then compress the encrypted data, embedding it into a carrier image via least significant bit (LSB) techniques. Experimental results demonstrate robust visual security, achieving a peak signal‐to‐noise ratio (PSNR) above 42 dB, strong resilience against common attacks, and a substantial a key space of 2 512 ×10 60 , effectively resisting brute‐force attacks. Neighboring pixel correlation coefficients drop below 0.15, compared to original images (>0.87), and under shear resistance attack with 128×128 data loss, PSNR remains above 23 dB. Additionally, employing P‐tensor product compressed sensing significantly reduces measurement matrix dimensionality, enhancing transmission efficiency. This method offers a viable solution for secure storage and transmission in modern ITS, significantly bolstering privacy and system robustness. The implementation is available at: https://gitee.com/zhangshuo‐aly/image‐encryption .
Authors
- Yongzhi Huang (ORCID: https://orcid.org/0000-0002-2503-1589)
- Wei Jiang (ORCID: https://orcid.org/0000-0002-1197-202X)
- Yueping Wang (ORCID: https://orcid.org/0000-0003-3786-9810)
- Shuo Zhang (ORCID: https://orcid.org/0000-0002-8663-8616)
- Bin Wang (ORCID: https://orcid.org/0009-0001-2658-3756)
Institutions
- Dalian University of Foreign Languages (CN)
- Dalian University of Technology (CN)
- Ministry of Education (ET)
Publication Details
- Journal
- IET Image Processing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1049/ipr2.70172
- Primary Topic
- Advanced Steganography and Watermarking Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Liaoning Province
- Higher Education Discipline Innovation Project
- Overseas Expertise Introduction Center for Discipline Innovation of Food Nutrition and Human Health (111 Center)