高技术通讯2026，Vol.36Issue(2)：147-156,10.DOI:10.3772/j.issn.1002-0470.2026.02.004
基于混沌映射和可逆神经网络的图像隐写算法研究
Research on image steganography algorithm based on chaotic mapping and invertible neural network
摘要
Abstract
To address the problem of image quality degradation caused by large-scale steganography,a new reversible steganography network is designed in this paper.This network combines chaotic mapping and invertible neural net-work,greatly improving the security of steganography while ensuring large-scale capacity.Firstly,a four-dimen-sional chaotic system with line balance is designed.The contents of the secret image are scrambled using a chaotic mapping encryption algorithm to prevent secret image information leakage during transmission.In addition,the cov-er image is preprocessed to hide the secret image in the Y channel,significantly enhancing the steganographic ca-pacity.Extensive experiments have been conducted on the DIV2K and COCO datasets.The peak signal-to-noise ra-tio(PSNR)of the cover image and stego image is as high as41.63 dB,and that of the secret image and recovered image is 43.29 dB.The experimental results demonstrate that the proposed method not only maintains excellent steg-anographic performance under large capacity steganographic conditions but also produces steganographic images with high fidelity.Furthermore,its anti-steganographic capability is far superior to existing advanced algorithms.关键词
图像隐写/混沌映射/可逆神经网络/图像质量/抗隐写分析/鲁棒性Key words
image steganography/chaotic mapping/invertible neural network/image quality/anti-steganog-raphy analysis/robustness引用本文复制引用
梁梦华,赵鸿图..基于混沌映射和可逆神经网络的图像隐写算法研究[J].高技术通讯,2026,36(2):147-156,10.基金项目
河南省科技厅科技攻关和软科学项目(192102310446)和河南省高校基本科研业务费专项资金(NSFRF210406)资助项目. （192102310446）
