一种新的基于双伪随机数的图像隐写算法

为提高数字图像隐写中的隐藏信息容量,提出了一种基于双伪随机数的图像隐写算法.首先介绍了伪随机数生成和双像素嵌入信息原理,然后将随机产生的整数伪随机数看作一个辅助像素值,结合载体图像中的一个像素值将两位秘密信息同时嵌入到一个载体图像像素中,从而在像素改变较小的情况下提高隐藏容量.最后分析了算法的嵌入性能,并通过仿真实验证明,该方法在提高隐藏信息容量的同时,也具有很好的安全性能.     

基于视觉感知与菱形编码的图像隐写算法

为提供较大的隐写容量和保持良好的载密图像质量,提出一种基于视觉感知和菱形编码的图像隐写算法。根据人类视觉系统,针对人眼对图像的高中低灰度区、纹理区及平滑区的敏感度的不同,在不同区域选择嵌入不同数量的秘密信息;同时为了尽可能减少对图像像素值的改变,采用改进的菱形编码来嵌入秘密信息。实验结果表明,与HVS-OPAP算法相比,该算法图像的嵌入容量提高了4.09%,获取的隐写图像具有更好的不可感知性,同时峰值信噪比平均提高了1.5dB,而且该算法具有抗RS隐写分析能力,安全性更高。     

基于LSBMR图像边缘自适应隐写的检测

在图像边缘自适应LSB匹配改进隐写算法中,秘密信息嵌入位置的选择仅由某个方向上像素对的差值决定,未考虑该像素与其邻域内其他像素的差值变化的特点.针对该问题,对隐写前后图像的八方向差分直方图进行分析,提出一种基于LSB匹配改进算法(LSBMR)边缘自适应隐写检测的算法.该算法计算图像的八方向绝对差分直方图,提取直方图中隐写前后变化较为明显的频数用以构建特征向量,并使用支持向量机完成检测.对较低嵌入率下(≤0.5 bpp)的EALSBMR隐写结果进行检测,结果表明该算法的平均检测率均高于现有典型的隐写分析算法.     

利用像素置换的自适应可逆信息隐藏

目的 像素置换作为一种可逆信息隐藏方式具有良好的抗灰度直方图隐写分析能力,但嵌入容量偏小一直是其缺陷。针对这一问题,提出了一种基于像素置换的自适应可逆信息隐藏算法。方法 首先,与传统2×2像素块结构相比构造了尺寸更小的像素对结构,使得载体图像可以被更稠密地分割,为嵌入容量的提升提供了基数条件。其次,提出适用于该新像素结构的可嵌像素对（EPP）筛选条件,避免嵌入过程引起图像质量大幅下降。之后,根据EPP的灰度趋势差异对其进行自适应预编码,提高Huffman编码压缩比,进一步提升算法嵌入容量。最终,通过像素置换嵌入信息。结果 与2×2像素块结构的非自适应图像隐写算法相比,在同样保证灰度直方图稳定性的情况下该算法的PSNR提高了32%左右,嵌入容量提高了95%以上。其中自适应性对嵌入容量提升的贡献极大。结论 本文算法同时具有抗灰度直方图隐写分析能力与高嵌入容量性的可逆信息隐藏。算法构造了更高效的可嵌单位,并且针对不同载体图像的特点对其可嵌区域进行差异化编码。实验结果表明,本文算法在具有更好的不可见性的同时,嵌入容量得到大幅提升。     

基于边缘匹配与最低有效位的图像隐写方法

提出一种基于边缘匹配与最低有效位的图像隐写方法。根据人类视觉特性,利用像素与其相邻像素间的像素差值,将图像分为平滑区、过渡区、边缘区,在3个区域中分别采用不同比特数的最低有效位进行嵌入。实验结果表明,该方法能增加图像嵌入容量并可保持较高的载密图像质量。     

结合高色彩相似度预处理的压缩域隐写算法

为提高图像隐写算法的载荷能力,增强载体的嵌入容量,提出一种结合高色彩相似度预处理的压缩域隐写算法。对图像进行预处理,利用超像素分割(SLIC)将图像根据内容进行分块,该分块方式具有空间接近度低、色彩相似度高的特点,增强图像的载荷能力;利用改进后的AMBTC压缩编码算法对形状和大小不规则的超像素块进行重新编码并嵌入秘密信息。通过设计率失真实验和有效性实验,验证了该预处理算法对提高嵌入容量的有效性。     

基于变步长量化的安全图像隐写

图像隐写通过将信息隐藏在载体图像中进行秘密传送,实现隐蔽通信.提出了VSQS图像隐写算法,利用密钥控制生成高斯序列并取整,用于对经伪随机排列后的图像像素进行变步长量化,根据量化像素与秘密信息之间的关系来修改像素,实现信息的嵌入.同时给出了该算法的一种扩展(称为TLQS隐写).实验结果表明,VSQS和TLQS图像隐写可提供较大的隐藏容量,并能抵抗几种常见的隐写分析方法.     

像素差自适应隐写方案*

提出了一种新的基于相邻像素差的自适应隐写算法。该算法结合图像位平面性质以及人眼对像素值起伏剧烈的区域敏感性较差的视觉特性,根据相邻像素高五位比特值之差的不同选择不同的嵌入策略,通过改变每对像素的最低三位比特值实现信息嵌入。通过理论分析和实验证明,该算法具有较高的嵌入容量,具有良好的隐写安全性,同时算法复杂度低,实现简单。     

基于DCT域的数字图像隐写容量归一化方法

针对现有方法存在的隐写容量较小问题,提出基于DCT域的数字图像隐写容量归一化方法.结合隐写术不可感知性、鲁棒性等特点,根据对"囚犯问题"的分析,从信息嵌入、载体传输与信息提取三方面构建隐写系统模型;对载体图像做DCT变换,使其呈现频谱均匀特征;利用序列密码方式对秘密信息加密,产生混沌序列,确定嵌入的最佳位置、时机与强度等条件,将隐秘信息嵌入到量化系数中,获得秘密图像;分别提取DCT块内与块间容量特征,通过改变像素中1位容量,利用突显缩放方法确保容量特征子集具有相同1-范数,实现容量归一化.仿真结果表明,上述方法能够有效提高隐写容量,获取的秘密图像信噪比更高.     

基于图像插值和直方图平移的可逆水印算法

现有的基于直方图的可逆水印算法嵌入容量较少,针对这一问题,结合图像放大后像素点的特征,提出一种新的可逆水印算法。利用插值方法将图像放大4倍,既增加了图像的像素个数,又增强了像素之间的相关性;使用上下左右4个像素点计算像素点的预测误差值,并构造直方图,在峰值点处嵌入水印信息;利用相反的过程提取水印,并根据插值原理恢复原始图像。实验结果表明,将图像放大后再嵌入,可嵌入水印容量提高了3倍。算法不可见性较好、嵌入容量较大,可用于图像隐藏、信息安全等领域。     

改进的双线性插值算法在信息隐藏中的应用*

针对传统信息隐藏算法隐藏容量小和对图像质量影响较大的缺点,提出了一种新的信息隐藏算法。利用灰度级插值的方法来修改秘密信息嵌入点的像素灰度值,为隐藏秘密信息创造出更大的冗余空间;同时采用新的相邻像素差值计算方法以实现秘密信息的嵌入,使得嵌入大量秘密信息后,载密图像的质量得到很好的保证。实验结果表明,当PSNR＞40 dB时,最低也可以隐藏145 800 bit。与传统的算法相比,隐藏容量有了更大提升的同时,PSNR值也保持在很高的水平。     

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。     

周期线性干扰信号的阶频谱图像信息隐藏仿真

为了解决现有图像信息隐藏方法未考虑图像插值而导致的图像信息隐藏效果差,以及图像信息传输的安全性低的问题,提出周期线性干扰信号的阶频谱图像信息隐藏方法。选用改进的双线性插值方法对周期线性干扰信号的阶频谱图像信息进行预处理,包括图像传输的加密与解密、概率密度函数的计算,并对秘密信息的嵌入点进行重新插值,从而为秘密信息创造更大的冗余空间,增大信息的隐藏容量。通过改变相邻像素插值的思想,计算图像水平、垂直、斜方向的嵌入式插值,实现周期线性干扰信号的阶频谱图像信息隐藏。仿真结果表明,所提方法具有较好的隐藏效果,是一种切实有效的图像信息隐藏方法。     

A high capacity reversible data hiding scheme with edge prediction and difference expansion

To enhance the embedding capacity of a reversible data hiding system, in this paper, a novel multiple-base lossless scheme based on JPEG-LS pixel value prediction and reversible difference expansion will be presented. The proposed scheme employs a pixel value prediction mechanism to decrease the distortion caused by the hiding of the secret data. In general, the prediction error value tends to be much smaller in smooth areas than in edge areas, and more secret data embedded in smooth areas still meets better stego-image quality. The multiple-base notational system, on the other hand, is applied to increase the payload of the image. With the system, the payload of each pixel, determined by the complexity of its neighboring pixels, can be very different. In addition, the cover image processed by the proposed scheme can be fully recovered without any distortion. Experimental results, as shown in this paper, have demonstrated that the proposed method is capable of hiding more secret data while keeping the stego-image quality degradation imperceptible.     

An image interpolation based reversible data hiding scheme using pixel value adjusting feature

In this paper, we propose an image interpolation based reversible data hiding scheme using pixel value adjusting feature. This scheme consists of two phases, namely: image interpolation and data hiding. In order to interpolate the original image, we propose a new image interpolation method which is based on the existing neighbor mean interpolation method. Our interpolation method takes into account all the neighboring pixels like the NMI method. However, it uses different weight-age as per their proximity. Thus, it provides the better quality interpolated image. In case of data hiding phase, secret data is embedded in the interpolated pixels in two passes. In the first pass, it embeds the secret data into the odd valued pixels and then in the second pass, the even valued pixels are used to embed the secret data. To ensure the reversibility of the proposed scheme, the location map is constructed for every pass. Basically, the proposed scheme only increases/decreases the pixel values during data hiding phase, which improves the performance of the proposed scheme in terms of computation complexity. Experimentally, our scheme is superior to the existing scheme in terms of data hiding capacity, image quality and computation complexity.     

Separable reversible data hiding in encrypted images based on scalable blocks

This paper proposes a new separable reversible data hiding method for encrypted images. Proposed scheme employs the pixel redundancy of natural images to construct embedding space. First, cover image is divided into multiple blocks with different scales. According to the pixel average value of each block, the lowest two bits of every pixel are vacated as reserved rooms. Subsequently, the whole image is encrypted by using stream cipher and the secret messages are finally embedded into the reserved rooms by the embedding key. Proposed scheme is separable in the sense that the recipient can achieve different function by the following ways: (a) If the recipient has only decryption key, an approximation plaintext image containing the embedded information can be obtained. (b) If the recipient has only embedded key, secret messages can be extracted correctly. (c) If the recipient has both decryption key and embedded key, he can not only extract the secret messages, but recover the original cover image perfectly. Extensive experiments are performed to show that our proposed schemes outperform existing reversible data hiding schemes in terms of visual quality, embedding capacity and security performance, even if a large-scale image database is used.

     

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。     

基于预测误差双重编码的大容量密文域可逆信息隐藏算法

针对目前密文域可逆信息隐藏算法嵌入容量较小的问题,提出了基于预测误差双重编码的大容量密文域可逆可分离信息隐藏算法。首先为了预留秘密信息的嵌入空间,图像拥有者利用基于预测误差的哈夫曼编码及扩展游程编码对图像进行预处理,然后加密图像;数据嵌入者在加密后的图像中嵌入秘密信息;接收者根据信息隐藏密钥可以准确无误地提取秘密信息,根据解密密钥可以无损恢复图像,两者无顺序要求。实验结果表明,预测误差双重编码的应用有效地提高了嵌入容量。     

A novel data hiding scheme based on modulus function

Four criteria are generally used to evaluate the performance of data hiding scheme: the embedding capacity, the visual quality of the stego-image, the security, and the complexity of the data-embedding algorithm. However, data hiding schemes seldom take all these factors into consideration. This paper proposes a novel data hiding scheme that uses a simple modulus function to address all the performance criteria listed above. According to the input secret keys, the encoder and decoder use the same set-generation functions H_r() and H_c() to first generate two sets Kr and Kc. A variant Cartesian product is then created using Kr and Kc. Each cover pixel then forms a pixel group with its neighboring pixels by exploiting an efficient modulus function; the secret data are then embedded or extracted via a mapping process between the variant of the Cartesian product and each pixel group. The proposed scheme offers several advantages, namely (1) the embedding capacity can be scaled, (2) a good visual quality of the stego-image can be achieved, (3) the computational cost of embedding or extracting the secret data is low and requires little memory space, (4) secret keys are used to protect the secret data and (5) the problem of overflow or underflow does not occur, regardless of the nature of the cover pixels.We tested the performance of the proposed scheme by comparing it with Mielikainen’s and Zhang and Wang’s schemes for gray-scale images. The experimental results showed that our proposed scheme outperforms Mielikainen’s in three respects, namely scalable embedding capacity, embedding rate, and level of security. Our data hiding scheme also achieved a higher embedding capacity than Zhang and Wang’s. The proposed scheme can easily be applied to both gray-scale and color images. Analyses of its performance showed that our proposed scheme outperforms Tsai and Wang’s in terms of its time complexity and memory space requirement.