A local variance-controlled reversible data hiding method using prediction and histogram-shifting

The stego image quality produced by the histogram-shifting based reversible data hiding technique is high; however, it often suffers from lower embedding capacity compared to other types of reversible data hiding techniques. In 2009, Tsai et al. solved this problem by exploiting the similarity of neighboring pixels to construct a histogram of prediction errors; data embedding is done by shifting the error histogram. However, Tsai et al.’s method does not fully exploit the correlation of the neighboring pixels. In this paper, a set of basic pixels is employed to improve the prediction accuracy, thereby increasing the payload. To further improve the image quality, a threshold is used to select only low-variance blocks to join the embedding process. According to the experimental results, the proposed method provides a better or comparable stego image quality than Tsai et al.’s method and other existing reversible data hiding methods under the same payload.     

Multiple predictors hiding scheme using asymmetric histograms

In recent years, many data hiding techniques have been proposed, and they can be generally classified into two types according to the reversibility of the image; these two types are reversible and irreversible data hiding. This study focused on reversible data hiding, which makes recovering the cover image possible after the secret data has been extracted. In 2013, Chen et al. proposed an asymmetric-histogram reversible data hiding method. In their scheme, two prediction error histograms (maximum and minimum error histograms) were used to embed the secret message. Two histograms were shifted in opposite directions. Hence, some stego-pixels were shifted to their original values. The complementary embedding strategy is effective. However, the predictor in the method is rough. Only neighboring pixels were used to generate the prediction errors, thereby resulting in poor prediction efficiency. To enhance the prediction efficiency, this paper combines several well-known predictors such as gradient adjusted gap (GAP), median edge detect, and interpolation by neighboring pixel (INP) to generate prediction errors. Different predictors along with the asymmetric-histogram method can achieve better results. The predictor GAP used more neighboring pixels to obtain the prediction value; therefore, it is suitable for complex images. However, the predictor INP only considers that closer pixels can achieve great results for smooth images. Hence, the proposed scheme combines GAP and asymmetric histogram for complex images. However, the predictor INP along with asymmetric histogram is used for smooth images. Experimental results showed that the PSNR value of the proposed method is greater than that of the asymmetric-histogram shifting method and other recent approaches.     

基于非对称直方图平移的可逆信息隐藏算法

利用两个非对称直方图分别向相反方向平移嵌入信息,会产生像素值的补偿还原效应,提出了一种更好的像素值预测方法,生成两个更偏向0值右侧和左侧的非对称预测误差直方图,这样的两个直方图在进行第二层信息嵌入时,会出现更多的像素点恢复到原始图像像素值,减少图像扭曲失真,提高载密图像质量。与传统算法相比,减少了参与直方图修改的像素量,进一步保护了载密图像质量。     

基于帧间预测误差扩展的可逆视频水印

为了提高可逆视频水印的嵌入容量和嵌水印视频质量,提出一种使用运动估计和预测误差直方图修改的算法.在嵌入端,根据视频中相邻帧间的内容关系,对每一帧使用运动估计获得其像素的预测误差,生成预测误差直方图,并通过扩展位于直方图峰值点的预测误差来嵌入水印;在每帧的嵌入过程中会产生少量用于提取水印和还原视频的头信息,包括运动向量和边界表等,将其与水印一起嵌入到该帧的参考帧中.在提取端,先获取参考帧中的水印和头信息并还原参考帧,保证提取操作具有正确的上下文,然后根据获取的头信息和还原后的参考帧提取当前帧中的水印.实验结果表明,采用文中算法获得的预测误差直方图具有高度的集中性,并且对像素值的修改十分微小,比其他可逆水印算法具有更大的嵌入容量和更好的嵌水印视频质量.     

基于中值预测的四轮嵌入可逆信息隐藏算法

传统基于预测误差直方图平移的可逆信息隐藏算法大多通过固定顺序来扫描原始图像,从而进行数据嵌入,这种方式没有考虑图像本身的纹理信息,导致无效移位像素点较多,伪装图像视觉质量较差。为解决该问题,提出一种基于中值预测的四轮嵌入可逆信息隐藏算法,以在提高嵌入容量的同时降低伪装图像的失真率。利用相邻像素之间具有较强相关性的特点,在较小的误差值处聚集大量像素点,以得到更陡峭的预测误差直方图并提高嵌入容量。对每个像素点定义复杂度,根据复杂度的高低对预测误差进行排序,优先在图像平滑区域嵌入数据,从而有效减少无效移位像素点个数,降低伪装图像的失真率。实验结果表明,该算法的最大嵌入率可以达到0.3 bpp,在0.1 bpp的嵌入率下峰值信噪比高达55.15 dB,与非对称直方图算法、误差直方图移位算法等相比,其具有较高的嵌入容量和较小的视觉失真率。     

Reversible data hiding for high quality images using modification of prediction errors

In this paper, a reversible data hiding scheme based on modification of prediction errors (MPE) is proposed. For the existing histogram-shifting based reversible data hiding techniques, though the distortion caused by embedding is low, the embedding capacity is limited by the frequency of the most frequent pixel. To remedy this problem, the proposed method modifies the histogram of prediction errors to prepare vacant positions for data embedding. The PSNR of the stego image produced by MPE is guaranteed to be above 48 dB, while the embedding capacity is, on average, almost five times higher than that of the well-known Ni et al. techniques with the same PSNR. Besides, MPE not only has the capability to control the capacity-PSNR, where fewer data bits need less error modification, but also can be applied to images with flat histogram. Experimental results indicate that MPE, which innovatively exploits the modification of prediction errors, outperforms the prior works not only in terms of larger payload, but also in terms of stego image quality.     

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。     

Reversible data hiding scheme with edge-direction predictor and modulo operation

Since the first histogram shifting technique was proposed by Ni et al., many histogram based data hiding methods were proposed to improve their scheme. One of the methods is using difference value between cover image and prediction image. Another method is using two point pairs and absolute value for improving Ni et al.’s scheme. In this paper, novel reversible data hiding scheme with edge-direction predictor and modulo operation was proposed for improving histogram shifting technique with 3 cases. We considered as much as possible around pixels by using edge-direction predictor with odd and even line embedding Also, we utilize two point pairs and absolute value at the same time by using modulo operation with wrap around. In the experimental results, the proposed scheme shown a good quality image result about 48dB as similar as other schemes and enhanced hiding capacity over 50 % than other schemes.     

An adaptive reversible data hiding scheme based on prediction error histogram shifting by exploiting signed-digit representation

A prediction error histogram shifting (PEHS)-based reversible data hiding scheme is proposed in this paper. A novel representation for the secret stream, called signed-digit representation, is proposed to improve the image quality. The secret binary stream is first converted into a signed-digit stream, which results in a high occurrence of ‘0’. Meanwhile, a block-wise-based prediction is performed on the original image to generate prediction errors, which lead to a sharp prediction error histogram. Then, the converted signed-digit stream is embedded into the prediction errors according to the improved histogram shifting (HS)-based scheme with multiple selected peak points, resulting in an adaptive embedding capacity. The experimental results validate that the proposed scheme outperforms state-of-the-art schemes in terms of embedding capacity while maintaining a good image quality.

     

基于预测误差和直方图对的无损数据隐藏方法

针对目前存在的大部分图像数据隐藏方法的嵌入量不大和视觉效果一般的问题,提出一种基于预测误差和直方图对的无损数据隐藏方法。在多灰度图像中,用某一像素点周围的八个像素点来预测中心像素点的灰度值,同时得到预测误差。再利用直方图对的方法,把数据嵌入到预测误差中。在嵌入过程中,以嵌入阈值和起伏阈值作为指导进行嵌入,通过调整这两个阈值,得到最佳的嵌入效果。实验表明,该方法在视觉效果和嵌入容量方面都取得很好的效果。