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。     

基于互补嵌入的彩色图像可逆数据隐藏

针对传统差值直方图平移算法嵌入容量偏低、多重嵌入时图像质量严重下降等缺陷,提出一种基于互补嵌入的彩色图像可逆数据隐藏算法。利用色彩分量之间的相关性和整数小波系数之间的关系减小差值,以增加差值直方图的峰值。采用双重直方图平移方法提高嵌入容量,两次嵌入过程的像素值扩展方向相反,部分像素值扩展量相互抵消,扩展量最大值为1。实...     

基于小波系数差值直方图平移的可逆数据隐藏

针对传统差值直方图平移算法嵌入容量偏低、多重嵌入时图像质量严重下降等缺陷,提出一种基于整数小波系数差值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和小波系数间的关系减小差值,使差值直方图更加紧凑、峰值更大。采用双重嵌入方法提高嵌入容量,两次嵌入的像素值扩展方向相反,使得部分像素扩展量相互抵消,像素扩展量...     

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。     

基于视点间关系预测的立体图像可逆水印

针对特殊应用领域的立体图像安全性问题,提出 了基于视点间关系预测的立体图像可逆水印, 能够无损地恢复原始立体图像。根据左右视点匹配像素具有较强相关性的特征,能够较 准确地预测立 体图像的像素,并建立峰值点较高的预测误差直方图。通过直方图峰值点的平移,并采用多 层水印嵌入, 从而达到较高的水印容量。此外,根据水印嵌入代价率,为峰值寻找最优零点,从而减少了 非水印嵌入的 数据平移量,提高了含水印立体图像的质量。实验结果表明,相比现有预测算法,提出的基 于视点间的预 测算法更加精确;在相同水印容量的情况下,本文方法的图像质量高于现有扩展的立体图像 可逆水印方法,在较大水印容量时,峰值信噪比(PSNR)的提高尤其明显。     

基于预测方式选择的可逆信息隐藏

为了提高信息隐藏算法的性能,提出一种基于预测 方式选择和直方图平移的灰度图像可逆信息隐藏算法。通过两种相对准确的预测方法对像素 进行预 测,对突变像素进行标记,标记像素不做任何处理。最后选择其中一种相对准确 的预测值方法作为最终预测方法,求出预测误差并利用预测误差扩展和直方图平 移技术进行数据嵌入。算法自适应地选择最佳预测方法,充分利用图像冗余,有 效提高嵌入容量(EC)。实验结果显示,本文算法充分利用邻近像素间的关联性 ,在保证EC的同时有效提高了峰值信噪比(PSNR)和算法的整体性能。     

基于直方图平移的医学图像可逆水印算法

结合医学图像特点,提出一种基于分块的灰度直方图平移水印算法.首先构建图像的灰度直方图,寻找峰值点和零值点;然后对图像分块,根据图像块的特点设定标志位;最后在指定的图像块内通过直方图变换来嵌入水印.实验结果表明,该算法不仅可以实现可逆水印,而且水印不可见性较好,嵌入容量较高,算法复杂度较低.该算法可以应用到信息隐藏、图像认证、隐秘传输等安全领域.     

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。     

Reversible data hiding with contrast enhancement using adaptive histogram shifting and pixel value ordering

Existing image-based reversible data hiding (RDH) methods tend to focus on increasing embedding capacity, but few consider keeping or improving visual image quality. Wu et al. proposed a new RDH method with contrast enhancement (RDH-CE) by pair-wisely expanding the histogram to the lower end and upper end. RDH-CE is especially valuable in exploiting the details of poorly illustrated images for which the visibility of image details is more important than just keeping PSNR high. However, obvious visual image distortion appears when embedding level gets high, and embedding capacity is relatively low when embedding level is small. In this paper, Wu et al.'s work is improved from three perspectives, namely image contrast enhancement, visual distortion reduction, and embedding capacity increment. The image contrast is improved by making the histogram shifting process adaptive to the histogram distribution characteristics, the image visual distortion is reduced by cutting off half the modification range of pixels induced in histogram pre-shifting, and the embedding capacity is increased by exploiting the pixel value ordering technique at the early stage of data embedment. Experimental result proves that the proposed work is effective in improving image contrast, reducing visual image distortion, and increasing embedding capacity.     

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 embedding for high quality images using interpolation and reference pixel distribution mechanism

This paper proposes a reversible data hiding method based on image interpolation and the detection of smooth and complex regions in the cover images. A binary image that represents the locations of reference pixels is constructed according the local image activity. In complex regions, more reference pixels are chosen and, thus, fewer pixels are used for embedding, which reduces the image degradation. On the other hand, in smooth regions, less reference pixels are chosen, which increases the embedding capacity without introducing significant distortion. Pixels are interpolated according to the constructed binary image, and the interpolation errors are then used to embed data through histogram shifting. The pixel values in the cover image are modified one grayscale unit at most to ensure that a high quality stego image can be produced. The experimental results show that the proposed method provides better image quality and embedding capacity compared with prior works.     

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.     

Reversible data hiding in encrypted color images using cross-channel correlations

In recent years, the increasing requirements in cloud storage and cloud computing have made it necessary to encrypt digital images for privacy protection. Meanwhile, many reversible data hiding (RDH) algorithms in the encrypted domain have been proposed. However, most of these algorithms are for gray-level images, and the intrinsic cross-channel correlations of color images cannot be utilized to improve the embedding capacity. In this paper, we propose a novel data hiding method for encrypted color images. In the encryption stage, the homomorphic property of encryption is achieved by basic modular addition. During the data hiding process, the cross-channel correlations between R, G and B channels are generated in encrypted domain, and data hiding is performed by the difference histogram shifting. Analysis and experiments demonstrate that the proposed method is secure and the RDH performance is superior.     

An integer wavelet transform based scheme for reversible data hiding in encrypted images

In this paper, a novel reversible data hiding (RDH) scheme for encrypted digital images using integer wavelet transform, histogram shifting and orthogonal decomposition is presented. This scheme takes advantage of the Laplacian-like distribution of integer wavelet high-frequency coefficients in high frequency sub-bands and the independence of orthogonal coefficients to facilitate data hiding operation in encrypted domain, and to keep the reversibility. Experimental results has demonstrated that this scheme outperforms all of other existing RDH schemes in encrypted domain in terms of higher PSNR at the same amount of payload. Compared with the state-of-the-arts, the proposed scheme can be applied to all natural images with higher embedding rate.     

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。