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暨南大学 信息科学技术学院,广东 广州 510632
[ "张晓虹(1998—),女,暨南大学硕士研究生,E-mail:[email protected]" ]
项世军(1974—),男,教授,E-mail:[email protected]
[ "黄红斌(1966—),男,副教授,E-mail:[email protected]" ]
纸质出版日期:2024-08-20,
网络出版日期:2024-03-21,
收稿日期:2023-11-16,
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张晓虹, 项世军, 黄红斌. 利用可逆网络的音频藏图算法[J]. 西安电子科技大学学报, 2024,51(4):226-238.
Xiaohong ZHANG, Shijun XIANG, Hongbin HUANG. Hiding images in audio based on invertible neural networks. [J]. Journal of Xidian University, 2024,51(4):226-238.
张晓虹, 项世军, 黄红斌. 利用可逆网络的音频藏图算法[J]. 西安电子科技大学学报, 2024,51(4):226-238. DOI: 10.19665/j.issn1001-2400.20240303.
Xiaohong ZHANG, Shijun XIANG, Hongbin HUANG. Hiding images in audio based on invertible neural networks. [J]. Journal of Xidian University, 2024,51(4):226-238. DOI: 10.19665/j.issn1001-2400.20240303.
可逆网络因其具有天然可逆的结构
非常适用于信息隐藏领域。图像能以生动直观、有层次的方式传递信息
而音频是一种广泛传播和使用的媒体文件
具有较大的嵌入容量
因此在音频中隐藏图像具有较高的研究和应用价值。在音频藏图任务中
如何表征音频和图像数据以及如何在减少音频失真的同时提高重建图像的质量是两个重要的问题。针对这两个问题
提出了一种基于可逆网络的音频藏图算法。对于数据特征表示
受到JPEG图像压缩中数据处理方法的启发
提出了图像特征提取与表示模块
该模块对彩色图像依次进行分块离散余弦变换、锯齿扫描和高低频分离操作
提取出图像的频域特征并得到其一维表示。此外
为了减少音频失真并提高重建图像的质量
利用小波变换分离音频的高低频分量并引入可逆网络将秘密图像嵌入到载体音频的高频区域中。实验结果表明
所提出的算法在实现高嵌入率的同时
能生成质量更高的隐写音频以及重建出更加还原的彩色图像
且算法具有较高的安全性。
Invertible Neural Networks(INNs) are well suited for the field of information hiding due to the fact that their inherent reversible structure.Images are able to efficiently convey information in a vivid and hierarchical manner
while audio is a widely used and distributed media file with a large embedding capacity.Therefore
hiding images in audio is of high research and application value.In the task of hiding images in audio
how to represent audio and image data and how to improve the quality of reconstructed images while reducing audio distortion are two important issues.To address these two problems
this paper proposes an algorithm based on INNs to hide images in audio.Inspired by the data processing methods in JPEG image compression
an image feature extraction and representation module is proposed for data feature representation.This module performs block-wise discrete cosine transform
Zigzag scanning
and high-low frequency separation operation on color images
extracting the frequency domain features of the image and obtaining its one-dimensional representation.In addition
in order to reduce audio distortion and improve the quality of reconstructed images
this paper uses the wavelet transform to separate the high and low frequency components of audio and introduces INNs to embed the secret image into the high-frequency region of the cover audio.Experimental results show that the proposed algorithm can generate higher quality steganographic audio and reconstruct more restored color images while achieving a high embedding rate
and that the proposed algorithm exhibits good security.
隐写图像隐藏可逆网络小波变换离散余弦变换
steganographyimage hidinginvertible neural networkswavelet transformsdiscrete cosine transforms
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