基于直方图移位的AMBTC域无损信息隐藏

针对秘密信息的安全传输,提出了一种信息隐藏算法,将混沌置乱变换及行程压缩编码同时应用于秘密信息预处理,旨在改善隐藏载体的嵌入容量和鲁棒。该算法将直方图移位技术应用于信息嵌入过程,在绝对矩阵块截断编码（AMBTC）生成的高低平均值序列上隐藏预处理后的秘密信息,实现了载体的无损隐藏并提升了嵌入容量,且嵌入容量高于直接在由AMBTC生成的高低平均值序列上进行隐藏的算法。实验结果表明,在受到某些攻击后仍保证提取出的秘密信息具有较高的可辨识度,归一化系数始终高于0.6,证明了该算法在鲁棒性和隐藏效率方面的优势。因此,提出的信息隐藏方法能达到秘密信息安全传输的目的,同时具有很好的抗攻击性。     

最大奇异值移位的鲁棒图像信息隐藏

为了提高图像信息隐藏的鲁棒性和不可感知性,提出了一种基于图像块最大奇异值移位的鲁棒信息隐藏算法.算法首先对图像分块并对每个图像块进行奇异值分解,根据图像块最大奇异值的大小选择合适的阈值,并对图像块的最大奇异值进行区间划分,通过将最大奇异值移位到与秘密信息比特相对应的区间实现秘密信息的嵌入.实验结果表明,该算法具有较大的嵌入容量,且在嵌入相同大小的秘密信息时与其他同类算法相比,具有更好的图像视觉质量和鲁棒性.该算法更能适应噪声环境下的信息隐藏.     

基于图像块像素差的大容量无损信息隐藏算法

为使提取嵌入的秘密信息后能无损恢复原始载体图像,提出一种基于图像块相邻像素差的大容量无损信息隐藏算法。将原始载体图像进行分块,并按一定顺序扫描图像块得到一系列像素序列,通过计算每个序列中相邻像素的差值得到差值直方图,从中选择2个最大峰值点将秘密信息嵌入。实验结果表明,与其他无损嵌入算法相比,该算法在保证较好不可见性的情况下,信息嵌入容量较大,峰值信噪比较高。     

小波域基于差分统计量直方图平移的图像鲁棒可逆信息隐藏算法

随着互联网技术的飞速发展和5G时代的到来,数字多媒体的交流和传播变得越来越便捷。为了解决网络环境下,数字图像的版权保护、完整性认证和篡改定位等问题,本文提出了一种小波域基于差分统计量直方图平移的图像鲁棒可逆信息隐藏算法,其主要思想为：1）对载体图像进行Haar小波变换;2）对变换后所得到的低频子带进行分块并计算分块的差分统计量以构造差分统计量的直方图;3）通过平移直方图将秘密信息嵌入到图像的低频子带中,并通过Haar小波逆变换得到带秘密信息的图像;4）在接收方,通过计算低频子带的分块差分统计量可以将秘密信息准确地提取出来,并且通过执行直方图平移的逆操作可以无损地还原出原始的低频子带,从而无失真地恢复出原始载体图像;5）带秘密信息的图像在遭到一定程度的图像处理操作的攻击后,被嵌入的秘密信息仍然可以被有效地提取出来,例如压缩因子为30的JPEG压缩和标准差为30的加性高斯噪声。与现有的几种鲁棒可逆信息隐藏算法相比,本文算法有更强的鲁棒性。实验结果验证了本文算法的有效性。     

基于LBP人脸纹理特征的差分直方图移位无损信息隐藏算法

针对信息隐藏算法中提高嵌入量与增强鲁棒性之间的矛盾问题,提出一种多载体信息隐藏算法。使用多幅人脸表情图像作为载体,采用局部二值模式（LBP）纹理特征识别人脸表情区域来嵌入加密信息;计算出载体区域的相邻像素差值矩阵,通过对差值矩阵的对应元素的直方图进行移位构造出嵌入空间来实现加密信息的可逆隐藏与载体图像的无损恢复。算法分析证明了比现有算法具有更大的嵌入容量并保持较高的鲁棒性的优势,在最大嵌入容量达到0.561时具有38.421 dB的信噪比（PSNR）,且在识别的嵌入区域PSNR值达到46.286。鲁棒性实验表明,该算法对于滤波攻击可以与原始信息图像的相似度大于99%;面对剪切、平移攻击时,秘密图像归一化系数◢NC◣最小为0.743和0.728,远大于其他算法。从与其他算法的对比实验结果看,该算法是有效的。     

增强图像平滑度的可逆信息隐藏方案

随着互联网技术的发展和社交网络的普及,可逆信息隐藏技术因其具有无损恢复载体信息的特性而被广泛应用于医疗、军事等领域的隐蔽信息传输。传统的可逆信息隐藏方案大多聚焦于嵌入容量提升和载密图像失真率降低,并未过多关注人们对图像视觉细节的要求,难以抵抗隐藏信息检测方法。针对上述挑战,从增强图像视觉平滑度方面入手,提出了一种增强图像平滑度的可逆信息隐藏方案,在嵌入隐蔽信息的同时提升载密图像最终的视觉质量。具体来说,所提方案将目标图像分为参考区域与非参考区域,利用非参考区域的图像像素预测值与原始像素值的差值作为信息嵌入的判断依据,通过差值平移来嵌入信息;进而构造图像平滑机制,采用高斯滤波作为秘密信息嵌入时像素值修改的模板,对预测值进行滤波计算,将滤波差值无损地加入载体图像中,以达到图像平滑的效果;同时将参考区域的像素值作为边信息,用于实现信息提取方对原始载体图像和秘密信息的无损恢复和提取;并以高斯函数中的滤波系数作为预置秘密信息对嵌入信息进行加密处理以保证嵌入信息的机密性。大量经典图像数据集的测试与分析结果表明,所提方案处理过的载密图像视觉平滑度得到了显著增强,具有较低的失真率、较高的嵌入率和较高的嵌入提取效率。在典型环境下,其生成的载密图像与高斯滤波后的图像相似度可达0.996 3,且可获得37.346的峰值信噪比和0.328 9的嵌入容量。     

基于混沌和斜变换的卫星图像抗压缩隐藏传输

针对星上一些重要图像数据的传输问题,提出了一种基于混沌序列和斜变换的大容量卫星遥感图像抗压缩隐藏传输方法.通过利用混沌序列随机选取原始高分辨率遥感载体图像块,并对其进行斜变换后在斜变换域中高频系数中嵌入秘密图像的斜变换系数,对选取的载体图像块进行逆斜变换得到含密载体图像.含密载体图像在经过卫星数传系统有损数据压缩后下传,地面接收端可以从解压后的含密载体图像中正确提取秘密图像.实验结果表明,提出的隐藏算法可抵抗星上JPEG2000有损压缩,并在保证良好的不可见性的情况下获得了较高的嵌入容量,可应用于卫星数据传输.     

基于码分复用的音频文件大容量可逆信息隐藏算法

针对音频文件可逆信息隐藏算法嵌入容量小、安全性不高的问题,文中提出了一种基于码分复用(Code Division Multiplexing,CDM)的音频文件大容量可逆信息隐藏(Reversible Data Hiding,RDH)算法.所提算法采用正交扩展序列将秘密信息可逆地嵌入音频文件中,不但可以保障所嵌入信息的无损提取,而且能够完全恢复原始音频信号;同时,基于嵌入向量的正交特性,将机密信息叠加嵌入到原始载体图像中,在嵌入过程中,不同嵌入向量中的大部分元素相互抵消,使得所提算法在大容量信息嵌入的情况下可取得更高的音频保真能力.而且,接收方只有采用相同的嵌入向量才能实现嵌入信息的正确提取与原始音频信息的无损恢复,有效提升了算法的安全性能.实验结果表明,与其他音频可逆信息隐藏算法相比,基于码分复用(CDM)的音频文件可逆信息隐藏(RDH)算法在相同文件失真情况下具有更大的可逆信息嵌入容量.     

谱段交织预测的多光谱图像可逆信息隐藏算法

针对现有可逆信息隐藏算法嵌入容量不高并且不适合多光谱图像的问题,提出一种基于谱段交织预测的多光谱图像可逆信息隐藏算法.利用含秘图像像素值与原始图像像素值相差不大于1的特点,结合含秘谱段对多光谱图像进行多波段预测,通过预测误差直方图移位技术嵌入秘密信息.Landsat卫星和Terra卫星多光谱图像仿真结果表明,提出的算法和典型可逆信息隐藏算法相比具有更好的视觉质量和隐藏容量.     

基于风格迁移纹理合成与识别的构造式信息隐藏

传统的信息隐藏算法大都通过修改载体达到隐藏秘密信息的目的,但不可避免地会在载体数据中留下修改痕迹,故常难以抵抗隐写分析技术的检测,为此无载体信息隐藏应运而生.无载体信息隐藏并非不使用载体,而是不对载体数据进行修改.为了提高无载体信息隐藏算法的隐藏容量和鲁棒性,提出了一种基于风格迁移纹理合成与识别的构造式信息隐藏算法.该算法首先选取不同类别的自然图像和纹理图像分别建立内容图像库和纹理风格图像库,并根据内容图像库中自然图像的类别构建二进制码的映射字典;其次为了接收方能够从含密图像中提取出秘密信息,需要构建带标签的纹理图像库,并将其作为训练集输入到卷积神经网络中,通过迭代训练获得纹理图像识别模型.在秘密信息隐藏时,根据秘密信息片段选择对应类别的自然图像,并按照一定的顺序组合成含密拼接图像,随后从纹理图像库中随机选择一张纹理图像,通过风格迁移的方法将含密拼接图像转换成含密纹理图像,从而完成秘密信息隐藏过程.在信息提取过程中,通过纹理图像识别模型可准确识别出含密纹理图像原本对应的图像类别,再对照映射字典即可提取出秘密信息.实验结果表明,所提算法生成的含密纹理图像具有良好的视觉效果,秘密信息隐藏容...     

A lossless robust data hiding scheme

This paper presents a lossless robust data hiding scheme. The original cover image can be recovered without any distortion after the hidden data have been extracted if the stego-image remains intact, and on the other hand, the hidden data can still be extracted correctly if the stego-image goes through JPEG compression to some extent. The proposed scheme divides a cover image into a number of non-overlapping blocks and calculates the arithmetic difference of each block. Bits are embedded into blocks by shifting the arithmetic difference values. The shift quantity and shifting rule are fixed for all blocks, and reversibility is achieved. Furthermore, owing to the separation of bit-0-zone and bit-1-zone as well as the particularity of arithmetic difference, minor alteration applying to the stego-image generated by non-malicious attacks such as JPEG compression will not cause the bit-0-zone and the bit-1-zone to overlap, and robustness is achieved. Experimental results show that, compared with previous works, the performance of the proposed scheme is significantly improved.     

Adaptive lossless steganographic scheme with centralized difference expansion

In this paper, a novel adaptive lossless data hiding scheme is presented that is capable of offering greater embedding capacity than the existing schemes. Unlike the fixed hiding capacity each block provides in most of the currently available lossless data hiding approaches, the proposed method utilizes a block-based lossless data embedding algorithm where the quantity of the hidden information each block bears is variable. To both reduce the image distortion and increase the hiding capacity, the payload of each block depends on its cover image complexity. Due to the fact that schemes with difference expansion tend to damage the image quality seriously in the edge areas, in the proposed scheme, smoother areas are chosen to conceal more secret bits. This way, a better balance can be reached between the embedding ratio and the stego-image quality. In addition, when recovered the cover image can came back to its old self to the last bit without any distortion at all. Experimental results, as this paper will show, have demonstrated that the proposed method is capable of hiding more secret data while maintaining imperceptible stego-image quality degradation.     

基于块参照像素的无损信息隐藏算法

提出一种具有高嵌入容量的图像无损信息隐藏算法。首先将载体图像分成互不重叠的子块,然后在每块中选定一个参照像素,并计算参照像素与块内其它像素的差。在像素差直方图移位产生冗余空间之后,机密信息就可以无损地嵌入到这些冗余空间中。该方法在机密信息提取后可完全恢复载体图像,而且提取机密信息和恢复载体图像不需要除机密信息长度之外的任何信息。实验结果表明了该算法的有效性。     

High-capacity reversible data hiding in binary images using pattern substitution

Data hiding, as the term itself suggests, means the hiding of secret data in a cover image. The result is a so-called stego-image. Reversible data hiding is technique, where not only the secret data can be extracted from the stego-image, but the cover image can be completely rebuilt after the extraction of secret data. Therefore, reversible data hiding is the choice in cases of secret data hiding, where the recovery of the cover image is required. In this paper, we propose a high-capacity reversible data hiding scheme based on pattern substitution. Our scheme gathers statistical data concerning the occurrence frequencies of various patterns and quantifies the occurrence frequency as it differs from pattern to pattern. In this way, some pattern exchange relationships can be established, and pattern substitution can thus be used for data hiding. In the extraction stage, we reverse these patterns to their original forms and rebuild an undistorted cover image. Our experimental results demonstrate the practicability of the proposed method. In fact, our new scheme gives a better performance than pair-wise logical computation (PWLC) in terms of both hiding capacity and stego-image visual quality.     

An adaptive image steganographic scheme based on Noise Visibility Function and an optimal chaotic based encryption method

Steganography is the science of hiding secret message in an appropriate digital multimedia in such a way that the existence of the embedded message should be invisible to anyone apart from the sender or the intended recipient. This paper presents an irreversible scheme for hiding a secret image in the cover image that is able to improve both the visual quality and the security of the stego-image while still providing a large embedding capacity. This is achieved by a hybrid steganography scheme incorporates Noise Visibility Function (NVF) and an optimal chaotic based encryption scheme. In the embedding process, first to reduce the image distortion and to increase the embedding capacity, the payload of each region of the cover image is determined dynamically according to NVF. NVF analyzes the local image properties to identify the complex areas where more secret bits should be embedded. This ensures to maintain a high visual quality of the stego-image as well as a large embedding capacity. Second, the security of the secret image is brought about by an optimal chaotic based encryption scheme to transform the secret image into an encrypted image. Third, the optimal chaotic based encryption scheme is achieved by using a hybrid optimization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) which is allowing us to find an optimal secret key. The optimal secret key is able to encrypt the secret image so as the rate of changes after embedding process be decreased which results in increasing the quality of the stego-image. In the extracting process, the secret image can be extracted from the stego-image losslessly without referring to the original cover image. The experimental results confirm that the proposed scheme not only has the ability to achieve a good trade-off between the payload and the stego-image quality, but also can resist against the statistics and image processing attacks.     

利用改进整数变换实现图像无损信息隐藏

为了在图像中实现无损信息隐藏,并提高数据嵌入容量和隐蔽性,给出一种基于改进整数变换的无损信息隐藏方法。首先对图像块采用改进算法进行整数变换,使得变换前后图像块引入失真较少,然后自适应选择整数变换后引入失真较小的可修改图像块进行整数变换,并嵌入较大数据量的机密信息,在公共信道进行传输后接收端能正确提取机密信息,并无损恢复原宿主图像。实验结果表明,该方法具有较大的数据嵌入容量和较好的隐蔽性,可用于医学图像中隐藏病历信息及遥感、军事图像的无损隐秘传输等领域。     

A new robust lossless data hiding scheme and its application to color medical images

The last few years witnessed an increased interest in the robust lossless data hiding schemes because they can verify the main requirements of the lossless data hiding (i.e., reversibility, capacity, and invisibility) and at the same time provide robustness against attacks. The reversibility is one of the important requirements of those methods. Another important requirement is the improvement of the robustness against attacks. The methods that improve the robustness are at the cost of reducing capacity and invisibility. Taking into consideration the need for improving the four requirements that have been mentioned above, this paper presents a novel robust lossless data hiding method in the transform domain. The proposed algorithm depends on transforming non-overlapping blocks of the host image using Slantlet transform (SLT) matrix and embedding data bits by modifying the difference between the mean values of the SLT coefficients in the high frequency subbands. As a practical application, the proposed algorithm has been adjusted in order to be applied to the color medical images. The data bits can be embedded not only in a single channel but also in the three channels of the RGB color image and thus further improving the embedding capacity. The results of the experiments that were conducted and the comparisons with the previous robust lossless data hiding (i.e., robust reversible watermarking) methods prove the effectiveness of the proposed algorithm.     

Reversible steganography based on side match and hit pattern for VQ-compressed images

Data hiding is an important technique in multimedia security. Multimedia data hiding techniques enable message senders to disguise secret data by embedding them into cover media. Thus, delivering secret messages is as easy as sending the cover media. Recently, many researchers have studied reversible data hiding for images. Those methods can reconstruct the original cover image and extract the embedded secret data from a stego-image. This study proposes a novel reversible steganographic method of embedding secret data into a vector quantization (VQ) compressed image by applying the concept of side match. The proposed method uses extra information, namely the hit pattern, to achieve reversibility. Moreover, its small hit pattern enables the embedding of the entire hit pattern along with the secret data in most cases. To optimize visual quality of the output stego-image, the method applies the concept of partitioned codebooks (state codebooks). The partition operation on the codebook uses a look-up table to minimize embedding and extraction time. We also propose the use of diagonal seed blocks to embed the entire hit pattern into the cover image without producing any extra control messages. Compared to the Chang and Lin method, the experimental results show that the proposed method has higher capacity, better visual quality, and shorter execution time.     

An image-hiding method with high hiding capacity based on best-block matching and k-means clustering

This paper presents a novel image-hiding method that exhibits a high hiding capacity that allows the embedded important image to be larger than the cover image, a facility that is seldom described in the literature. In the proposed method, the entire important image is divided into many nonoverlapping blocks. For each block of the important image, a block-matching procedure is used to search for the best similar block from a series of numbered candidate blocks. The obtained indices of the best-matching blocks are encoded using Huffman coding scheme, and then recorded in the least-significant-bit planes of the cover image through a monoalphabetic transposition cipher. The proposed method exhibits the following advantages over existing methods: (1) a high hiding capacity such that the embedded important image can be larger than the cover image; (2) a stego-image with a high quality, which improves the secrecy of the hidden image; and (3) a small error between the extracted important image and the original important image indicating that the extracted important image is of acceptable quality.