High Payload Reversible Data Hiding Scheme Using Difference Segmentation and Histogram Shifting

Steganography is a technique that conceals secret data into a cover medium for delivering secret data over public computer networks. Reversible data hiding schemes not only can achieve secret data delivery, but also can restore the cover medium. Histogram shifting is one of the most popular reversible data hiding techniques. Luo et al. presented a reversible data hiding technique that shifts the histogram of prediction error. But the embedding payload of Luo et al.'s method can further be improved. The proposed method uses a difference segmentation strategy and pseudo pixel generation to increase the height of peak in the prediction error histogram. The experimental results show that the embedding payload of the proposed method is higher than that of Luo et al.'s method.     

High capacity multi-bit data hiding based on modified histogram shifting technique

A novel data hiding technique based on modified histogram shifting that incorporates multi-bit secret data hiding is proposed. The proposed technique divides the image pixel values into embeddable and nonembeddable pixel values. Embeddable pixel values are those that are within a specified limit interval surrounding the peak value of an image. The limit interval is calculated from the number of secret bits to be embedded into each embeddable pixel value. The embedded secret bits can be perfectly extracted from the stego image at the receiver side without any overhead bits. From the simulation, it is found that the proposed technique produces a better quality stego image compared to other data hiding techniques, for the same embedding rate. Since the proposed technique only embeds the secret bits in a limited number of pixel values, the change in the visual quality of the stego image is negligible when compared to other data hiding techniques.     

基于插值预测和块分类的低失真可逆数据隐藏

提出一种基于插值预测和块分类模型的低失真可 逆数据隐藏算法。首先,对原始图像 进行插值预测, 得到预测误差图像;然后根据误差图像建立直方图,使得产生的直方图更陡峭,峰值点出现 频率更大;接 着对误差图像进行分块,利用块分类模型,在隐藏块内利用直方图平移隐藏信息,尽可能地 减少平移点的 数量;最后,相应地修改原始像素的灰度值,得到低失真的隐秘图像。实验结果表明,本文 算法不仅可以实现可逆数据隐藏,而且隐藏效果较好,有效载荷较高。     

基于分块最佳预测的可逆数据隐藏

为了提高嵌入算法的性 能,提出一种基于分块最佳预测和直方图平移的灰度图像可逆数据隐藏算法。根据嵌 入阈值,统计 每一图像块中4种预测方案的嵌入容量,选择最大容量对应的预测方案作为该图像块的最佳 预测方案。嵌 入算法充分利用像素值局部相关性,自适应地选择最佳预测方案,有效提高嵌入容量。实验 结果表明,本 文算法在保证图像质量的同时有效提高嵌入容量,算法的整体性能比其它同类算法更优。     

Reversible data hiding based on prediction-error histogram shifting and EMD mechanism

This paper proposes a reversible data hiding scheme for gray-level images. The scheme exploits the similarity among adjacent pixels and uses the side-match predictors to obtain prediction-error histogram. Then secret bits are embedded by using histogram shifting method. To achieve high capacity, nonary Exploiting Modification Direction (EMD) algorithm and multi-layer embedding mechanism are used when embedding the secret bits. Additionally, we improve the method of preventing overflow and underflow problems which enhances the compression ability of location map. In the extraction process, we use the same predictors to generate the error histogram, then we can extract the secret bits and recover the original cover image. Experimental results show that our algorithm can achieve better performance compared with the previous related algorithms.     

Reversible data hiding scheme using reference pixel and multi-layer embedding

This paper presents a lossless data hiding scheme. The proposed scheme is based on the pixel difference histogram shifting to spare space for data hiding. Pixel differences are generated between a reference pixel and its neighbors in a pre-assigned block. After the difference histogram shifting, a large number of data can be embedded into the cover image, and multi-layer embedding is used to improve the hiding capacity. Different from previous works based on histogram shifting the proposed scheme can extract the hidden data and recover the exact original cover image with no extra information except the length of hidden data and the stego-image itself. Experimental results show that the average pure payload among eight commonly used grayscale images is up to 1.08 bits per pixel (bpp) while keeping low distortion.     

基于双直方图平移的彩色图像可逆数据隐藏

提出一种基于双直方图平移的彩色图像可逆数据隐藏算法.利用色彩分量间的相关性减小差值,使差值直方图更加紧凑、直方图的峰值更大.采用直接调整像素值的方法在差值中嵌人数据,由像素值的二次可调整性定位不可调整像素,并嵌入少量的标志信息代替定位图,从而提高嵌入容量.实验结果表明,本文算法在保证图像质量的同时大幅提高了嵌入容量,与...     

基于块容量标签的密文图像可逆数据隐藏方法

密文图像的可逆数据隐藏技术既能保证载体内容不被泄露,又能传递附加信息。本文提出了一种基于块容量标签(block capacity label, BCL)的高容量密文图像可逆数据隐藏算法。该方案在图像加密之前进行预处理,首先将图像分为两个区域：参考像素区域和预测像素区域。然后将预测像素区域分为不重叠的块,根据所提出的算法确定分块的BCL,在对图像进行加密之后嵌入BCL,生成加密图像;在秘密数据嵌入阶段,根据BCL和数据隐藏密钥嵌入秘密数据。实验测试了BOWS-2数据集,平均嵌入容量为3.806 8 bpp,与现有方法相比,该方法可以获得更高的秘密数据嵌入容量,并可以实现原始图像的完美重建。     

基于图像块动态参照像素的无损信息隐藏算法

提出了一种基于动态参照像素和多层嵌入的图像无损信息隐藏方法,其能在保持较小图像失真的同时,实现大容量的信息嵌入,且机密信息提取后能完全恢复原载体图像.特别地,与其他基于直方图移位的算法不同,本文方法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其他信息.实验结果表明了该算法的有效性.     

Reversible data-hiding for progressive image transmission

This research presents a multi-resolution reversible data-hiding algorithm to enable multi-scale marked images that are transmitted progressively to be exactly recovered at the receiver side once hidden data has been extracted. Based on the spatially hierarchical multi-layer structures of progressive-image transmission, the proposed algorithm first decimates the incoming image pixels into a pre-specified number of hierarchical layers of pixels. Then, it modifies pixel values in each hierarchical layer by shifting the interpolated-difference-values histogram between two neighboring layers of pixels to embed secret information into the corresponding hierarchical layer images. The proposed algorithm offers a reversible data-hiding ability for applications that use progressive image transmission to render progressive-image authentication, information-tagging, covert communications, etc. With progressive-reversible data-hiding, users of progressive image transmission can receive each original progressive image and complete hidden messages related to the received progressive image. This allows users to make real-time definite decisions according to an application's requirements. In contrast to other reversible data-hiding schemes, the algorithm proposed in this study features reversible data-hiding in progressive-image transmission based on a hierarchical decimation and interpolation technique. The interpolating process is used to reduce the difference values between the target pixel values in one progressive layer and their interpolated ones. This increases the hiding capacity of interpolation-differences histogram shifting. The experimental results demonstrate that the proposed method provides a greater embedding capacity and maintains marked images at a higher quality. Moreover, the proposed method has a low computational complexity as it requires only simple arithmetic computations.     

Reversible data embedding for indices based on histogram analysis

Reversible data hiding is a technique that not only protects the hidden secrets but also recovers the cover media without any distortion after the secret data have been extracted. In this paper, a new reversible data hiding technique for VQ indices which are compressed streams based on the mapping function and histogram analysis of transformed VQ indices is introduced to enhance the performance of some earlier reversible data hiding schemes that are based on VQ indices. As a result, the proposed scheme achieves high embedding capacity and data compression simultaneously. Moreover, the original VQ-compressed image can be perfectly reconstructed after secret data extraction. To estimate the performance of the proposed scheme, variety of test images are used in the experimental testing. As can be seen in the experimental result, our scheme is superior to some previous schemes in term of compression rate and embedding rate while maintaining the reversibility.     

分区域的医学图像高容量无损信息隐藏方法

针对医学图像的分区域典型特征,提出一种基于区域和直方图平移的高容量无损信息隐藏方法。本方法用最大类间距分割法求得原始图像的前景区域,再用聚合多边形逼近和图像拟合法得到其数据嵌入区域。在数据嵌入过程中,提出利用差值直方图循环平移和基于编码的直方图平移方法分别在前景和背景区域嵌入数据,提高了原始直方图平移方法容量和解决了溢出问题。实验结果表明该方法总的嵌入容量可达1 bit/packet以上,并且隐秘图像质量在40dB左右,适用于具有区域特征的质量敏感图像的大容量信息隐藏。     

基于多项式秘密共享的图像密文域可逆信息隐藏

针对密文域可逆信息隐藏在多用户场景下算法嵌入率低、载体图像容灾性能较弱等问题，该文提出一种基于多项式秘密共享的图像密文域可逆信息隐藏方案。通过将图像分割成多幅影子图像并存储在不同的用户端，可以增强图像的容灾性，为了实现额外信息在图像重构前后提取的可分离性，该方案包括两种嵌入算法:算法1在图像分割的过程中，将额外信息嵌入多项式的冗余系数中得到含有额外信息的影子图像，该算法支持在图像重构之后提取额外信息；算法2针对图像分割后的任一影子图像，利用秘密共享的加法同态特性实施嵌入，该算法支持直接从影子图像中提取额外信息。实验在不同门限方案和影子图像压缩率的条件下进行测试，当压缩率为50%时，(3, 4)门限方案的嵌入率达4.18 bpp(bit per pixel)，(3, 5)门限方案的嵌入率达3.78 bpp。结果表明，两种嵌入算法分别支持从影子图像与重构图像中提取额外信息，实现了方案的可分离性；与现有方案相比，所提算法嵌入率较高、计算复杂度较低，具有较强的实用性。     

基于三直方图平移和互补嵌入的可逆信息隐藏

为了提高嵌入算法的整体性能,提出一种基于三 差值直方图平移和互补嵌入的彩色 图像可逆信息 隐藏算法。利用色彩分量之间的相关性以及预测误差之间的关系减小差值,以增加差值直方 图的峰值。采 用三差值直方图平移和双重嵌入方法提高嵌入容量,两次嵌入过程中像素值沿相反方向扩展 ,部分像素值 扩展量相互抵消。选择两种不同的预测方向计算预测误差,以增加扩展量抵消的机会,解决 双重嵌入时图 像质量严重下降的难点问题。实验结果表明,本文算法在保证图像质量的同时大幅提高嵌入 容量,算法的整体性能优于其它同类算法。     

An efficient high-capacity reversible data hiding scheme for encrypted images

Reversible data hiding in encrypted images is an effective technique to embed information in encrypted domain, without knowing the original content of the image or the encryption key. In this paper, a high-capacity reversible data hiding scheme for encrypted images based on MSB (most significant bit) prediction is proposed. Since the prediction is not always accurate, it is necessary to identify the prediction error and store this information in the location map. The stream cipher is then used to encrypt the original image directly. During the data hiding phase, up to three MSBs of each available pixel in the encrypted image are substituted by the bits of the secret message. At the receiving end, the embedded data can be extracted without any errors and the original image can be perfectly reconstructed by utilizing MSB prediction. Experimental results show that the scheme can achieve higher embedding capacity than most related methods.     

PVO based reversible data hiding technique for roughly textured images

Multidimensional Systems and Signal Processing - Recently, several reversible data hiding (RDH) techniques based on pixel value ordering (PVO) have been proposed that precisely embed the secret...     

基于边缘检测和像素分类的可逆数据隐藏

为了提高嵌入算法的整体性能,提出一种基于边缘检测和像素分类的灰度图像可逆数据隐藏算法。算法按嵌入容量优先原则自适应地选择最佳阈值提取图像边缘,并根据边缘信息和指定的图像质量控制因子将像素分为平滑、弱边缘和强边缘像素3类。对平滑像素,通过增加嵌入强度的方法提高嵌入容量,预测误差直方图平移2位;对弱边缘像素,像素值最大修改量为1,从而保证图像含密质量;强边缘像素的像素值保持不变,进一步提高含密图像质量。实验结果表明,本文算法在保证图像质量的同时有效提高嵌入容量,算法的整体性能优于其它同类算法。     

基于编码压缩和加密的图像可逆信息隐藏算法

提出一种编码压缩和加密的图像可逆信息隐藏算 法。计算载体像素预测值与其像素值的差值, 对差值进行哈夫曼编码压缩,通过压缩数据和随机数据加密重构图像,得到载体数据。将哈 夫曼编码的码 表和秘密信息隐藏在载体数据中,实现信息隐藏。在载密数据中提取码表数据和秘密信息, 对加密压缩数 据进行解密,结合码表和预测方法恢复原始图像。实验结果表明,本文算法具有较大的隐藏 容量,不仅能 正确提取秘密信息,还能无损恢复原始图像。     

High-capacity reversible data hiding in encrypted image based on specific encryption process

This paper proposes a novel reversible data hiding method in encrypted images based on specific encryption process. In the proposed specific encryption algorithm, the stream cipher and prediction error are combined to vacate room for data embedding. After that, a permutation operation is performed on the encrypted image to improve the security. In the embedding process, we can embed a large amount of secret data in the encrypted image by pixel value expansion because most of the pixel values are less than 128 by the specific encryption process. At the receiver end, the encrypted image can be recovered from the marked encrypted image without knowing the secret data. Therefore, even if the recipient only has the encryption key, the original image will be perfectly recovered. If the recipient only has the data-hiding key, the secret data will be extracted. And if the recipient has both keys, the original image and the secret data are both available. The proposed method achieves a higher embedding capacity than that of methods based on vacating room after encryption. It does not require the image owner to perform reversible data hiding techniques on the original image, which is more convenient than methods based on reserving room before encryption. Experimental results demonstrate that the proposed method outperforms other state-of-the-art methods.     

Adaptive smoothness evaluation and multiple asymmetric histogram modification for reversible data hiding

In this paper, an adaptive reversible data hiding (RDH) algorithm based on multiple asymmetric histograms is proposed by making full use of the image content. Different from existing multiple prediction error histogram (PEHs) modification methods that directly cluster all the pixels of a cover image into multiple categories, we firstly utilize a smoothness threshold to exclude as many pixels in complex regions as possible for reducing unnecessary pixel shifting, and then exploit fuzzy C-means with multiple deliberately-designed features to construct multiple sharply-distributed categories, which helps in increasing the subsequent embedding performance. Two asymmetric PEHs for each class are generated using a pair of asymmetric predictors, and the short part of each asymmetric PEH is modified to reduce the number of invalid modifications. The improved discrete particle swarm optimization is used to adaptively select the best bin while reducing computational complexity. The experimental results show that the proposed method outperforms several state-of-the-art RDH methods.