引入超分辨率下采样误差的图像边信息估计隐写  

Spatial image steganography based on side information estimated by super resolution

作　　者：赵鑫[1,2] 王垚飞[1,2] 陈可江 张卫明 俞能海[1,2] Zhao Xin;Wang Yaofei;Chen Kejiang;Zhang Weiming;Yu Nenghai(School of Cyber Security,University of Science and Technology of China,Hefei 230027,China;Key Laboratory of Electromagnetic Space Information,Chinese Acaderny of Sciences,Hefei 230027,China)

机构地区：[1]中国科学技术大学网络空间安全学院,合肥230027 [2]中国科学院电磁空间信息重点实验室,合肥230027

出　　处：《中国图象图形学报》2022年第1期226-237,共12页Journal of Image and Graphics

基　　金：国家自然科学基金项目(62102386,62072421,62002334);中央高校基本科研业务费专项资金资助(WK2100000018);中国博士后科学基金项目(2021M693091)。

摘　　要：目的由于空域图像下采样过程中提供的量化误差边信息能够有效提升隐写安全性,为了得到下采样之前的高分辨率图像,提出一种基于超分辨率网络的空域图像边信息估计隐写方法。方法受原始下采样边信息隐写方法的启发,使用超分辨率网络生成被称为预载体的高分辨率图像。同时利用现有的空域图像对称失真算法得到每个像素点的修改失真,然后以浮点型精度对预载体下采样,得到和载体同分辨率的图像形式,利用对应像素点间的差值指导像素点的修改方向,实现基于初始失真的非对称失真调整。首先以峰值信噪比和极性估计准确率为指标对比了多种超分辨率网络以及基于传统插值方法的上采样性能,并通过调整初始失真分别进行隐写和隐写分析实验,选择使安全性提升最大的残差通道注意力机制网络及其对应调整系数作为本文的下采样边信息估计隐写方法。结果使用隐写领域中常用的3个数据库、两种传统初始失真函数以及两类隐写分析方法进行实验。在跨数据集的隐写安全性上,相比传统隐写方法,在对抗基于手工特征和基于深度学习的隐写分析时,本文方法的安全性均有显著提升,如在测试集载体图像上,嵌入率为0.5 bit/像素时,安全性分别提升6.67%和6.9%;在训练集载体图像上,本文方法的安全性在比传统方法有很大提升的基础上,甚至在一些情况下能够高于原始边信息隐写方法的安全性,如在对抗基于手工特征的隐写分析器且嵌入率为0.1 bit/像素时,安全性提升1.08%;在对抗基于深度学习的隐写分析器且嵌入率为0.5 bit/像素时,安全性提升0.6%。结论实验表明,使用超分辨率网络作为下采样边信息估计的工具,并利用估计边信息调整嵌入修改的初始失真,能够有效提升传统隐写方法的安全性,并接近甚至在部分情况下超越了原始边信息隐写的安全性。除�Objective Steganography is a way of covert communication to achieve the transmission of a secret message via slight modification of the elements on the cover images without causing suspicion of the steganalysis.Security is capable to embed the secret message with minimal distortion via syndrome-trellis codes(STC),steganographic polar codes(SPC)or optimal analogue embedding.The embedding rate and loss function is demonstrated.The initial symmetric distortions function assigns the same cost for the modification of pixel values±1.Some adapting methods on top of symmetric distortion have also been generated,demonstrating the effectiveness of asymmetric distortion steganography for improving steganographic security.To improve steganography security,the prompted guidance of the adjustment of the initial cost and previous work has proved that the quantization error information provided via image downsampling used as auxiliary information Steganography does not have the original image before downsampling in many real scenes.For computer vision,super-resolution tasks are rapidly evolving,which can end-to-end generate high-resolution images corresponding to low-resolution images.In order to get the high-resolution images before downsampling based on the downsampled side information,this research has proposed a steganography based on super-resolution networks for estimating side information of spatial domain images.The unique side information provided by the estimated high-resolution images in the downsampling process can effectively improve steganography security excluding high scaling.Method Based on the initial side information steganography method,the steganographer cover for embedding is obtained via various image processing processes in common,such as the downsampling process involved.A pre-cover downsampling image has been called for obtained cover.This research has briefly proposed some relevant super-resolution networks to assess the quality of the resulting image via peak signal to noise ratio(PSNR)and polarity e

关 键 词：隐写 边信息估计 超分辨率网络 下采样 失真调整 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]