High capacity reversible hiding scheme based on interpolation,difference expansion,and histogram shifting

Difference expansion and histogram shifting methods are two popular hiding strategies that have been widely used in many researches. For example, Hong and Chen developed a reversible hiding method based on interpolation and histogram shifting. The image quality of their scheme is exceptional; however, their scheme needs to keep and transmit two peak points for secret data extraction and pixel recovering. Moreover, the reference pixels in their scheme cannot be used to embed secret data that will decrease the hiding capacity. Therefore, this paper shall propose a reversible hiding method to enhance their scheme. The proposed method applies the difference expansion, histogram shifting and interpolation strategies to conceal secret data in the reference pixels for increasing the hiding payload. Experimental results indicate that the proposed method performs better in terms of hiding capacity than recently developed methods.     

Reversible data hiding for high quality images exploiting interpolation and direction order mechanism

Reversible data hiding can restore the original image from the stego image without any distortion after the embedded secret message is exactly extracted. In this paper, a novel, reversible, data hiding scheme for high quality images is proposed in spatial domain. To increase embedding capacity and enhance image quality, the proposed scheme classifies all pixels as wall pixels and non-wall pixels. For wall pixel, the interpolation error is used to embed secret data over the interpolation prediction method. In contrast, the difference value between the non-wall pixel and its parent pixel, which is defined by the direction order, is computed to hide secret data based on the histogram shifting. The experimental results demonstrate that our scheme provides a larger payload and a better image quality than some existing schemes. Moreover, the performance of the proposed scheme is more stable for different images.     

High capacity data hiding based on interpolated image

We investigate the use of parabolic interpolation in data hiding and propose a novel data hiding algorithm with high capacity based on interpolated image. Specifically, the proposed algorithm creates an interpolated image from input image by parabolic interpolation, and embeds secret bits into interpolated pixels in terms of the relation between the interpolated value and the mean value. Ten standard benchmark images are taken as test images for validating efficiency of our algorithm. The results illustrate that our algorithm has better performances than some popular data hiding methods in embedding capacity and visual quality with respect to PSNR and SSIM.     

A reversible data hiding scheme using complementary embedding strategy

Obtaining good visual quality and high hiding capacity with reversible data hiding systems is a technically challenging problem. In this paper, we propose a simple reversible data hiding scheme that uses a complementary hiding strategy. The proposed method embeds one secret bit horizontally and vertically into one cover pixel of a grayscale cover image by decreasing odd-valued pixels and increasing even-valued pixels by one. Experimental results show that the hiding capacity measured by bit per pixel (bpp) of the proposed scheme is at least 1.21 bpp with a PSNR (peak signal-to-noise ratio) value greater than 52 dB for all standard test images. Especially in the case of four-layer embedding, the PSNR value of the proposed method is still greater than 51 dB at a hiding capacity of about 5 bpp for all standard test images. In addition, the proposed method is quite simple because it primarily uses additions and subtractions. These results indicate that the proposed scheme is superior to many existing reversible data hiding schemes introduced in the literature.     

Development of a data hiding scheme based on combination theory for lowering the visual noise in binary images

In order to raise the embedding capacity and simultaneously reduce the artifact effect caused by embedding secret messages into binary images, a novel data hiding method based on the combination theory is proposed. In the proposed scheme, a secret position matrix is designed to improve the hiding capacity which is capable of preventing the least distortion based on the combination theory. Our new scheme enables users to conceal more than one bit of secret data by changing at most one pixel in one subimage. We have derived a formula for computing the payload and the possible modification pixels of a block. Compared with the existing schemes in terms of the hiding capacity and the visual artifacts, as our experimental results show, the proposed scheme is capable of providing a better image quality protector even with a more efficient secret data hider.     

Adaptive (<Emphasis Type="Italic">k</Emphasis>, <Emphasis Type="Italic">F</Emphasis><Subscript>1</Subscript>) interpolation-based hiding scheme

In 2012, Lee et al. proposed an interpolation technique with neighboring pixels (INP) as the base to conceal secret information in predicted pixels. Their method can effectively predict the pixel between two neighboring pixels. However, the different lengths of secret messages caused great distortion when a large secret message was concealed in the predicted value. Therefore, the proposed scheme applies the center folding strategy to fold the secret message for reducing image distortion. Furthermore, the proposed scheme references the variance of the neighboring pixel to determine the length of the secret message for controlling image quality. The parameter pair (k, F ₁) is used to categorize the variance and determine the size of the secret message hidden in each category. k is the total number of thresholds which computed based on the characteristics of each image for balancing hiding payload and image quality. F ₁ is the length of the secret message for the smoothest area. The experimental results show that the embedding capacity of the proposed method is 1.5 bpp higher than that of existing methods. For the same hiding payload, the image quality of the proposed method is 1.6 dB higher than that of existing methods.     

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.     

A secret sharing scheme for EBTC using steganography

In this paper, a new method based on Block Truncation Coding (BTC) and the halftoning technique is proposed for secret sharing of lossy compressed images. BTC is a simple and efficient image compression technique. However, it yields images of undesirable quality, and significant blocking effects are seen as the block size that is used increases. A modified method known as Enhanced Block Truncation Coding (EBTC) is proposed to solve these problems. For secret sharing, we propose a (2, 2) secret sharing scheme which provides authentication using DE scheme. This scheme was developed for data hiding with grayscale images, but our proposed EBTC uses bitmap images for which the DE scheme is not appropriate. We show the solution for such a problem. Moreover, we reduce the computation complexity for secret sharing using the DE algorithm because past schemes which used polynomial or interpolation algorithms require too much time for secret sharing. In addition, we show how to authenticate a cover image. Experimental results show that our proposed scheme provides secret sharing with proper authentication and acceptable computational complexity.     

Reversibility of image with balanced fidelity and capacity upon pixels differencing expansion

Reversible data hiding has attracted considerable attention in recent years. Being reversible, the decoder can extract hidden data and recover the original image completely, and the difference expansion (DE) scheme can lead to a lossless pixel after secret data exacting. Furthermore, despite achieving pixel reversibility based on the concept of expanded differencing, the difference expansion scheme can cause enormous image distortion because of the size of the difference. The proposed scheme in this paper describes a novel prediction for achieving predictive error based reversible data hiding by considering the relation between a pixel and its neighboring pixel and using the predictor to identify the projected difference in pixel value. Experimental results show that the proposed scheme is capable of providing great embedding capacity without causing noticeable distortion by selecting the minimal predictor based on pixel expansion. In multilevel cases, this proposed method performs better than other existing methods. Moreover, the proposed scheme is able to pass the Chi-square test, a test used to find whether an image utilizes LSB for data hiding.     

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.     

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.     

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。     

Image interpolating based data hiding in conjunction with pixel-shifting of histogram

Information hiding is an important research issue in digital life. In this paper, we propose a two-stage data hiding method with high capacity and good visual quality based on image interpolation and histogram modification techniques. At the first stage, we first generate a high-quality cover image using the developed enhanced neighbor mean interpolation and then take the difference values from input and cover pixels as a carrier to embed secret data. In this stage, our proposed scheme raises the image quality a lot due to the ENMI method. At the second stage, a histogram modification method is applied on the difference image to further increase the embedding capacity and preserve the image quality without distortion. Experimental results indicate that the proposed method have better PSNR value of stego-image with improving 43 % on the average when compared the past key-studies.     

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。     

Reversible data hiding scheme based on neighboring pixel differences

In this paper, we propose a reversible data hiding algorithm for grayscale images. Specifically, our algorithm is based on the histogram modification technique. The premise of this algorithm is that a histogram is constructed from the differences between each pixel and its neighbors. In the data embedding process, a modified histogram shifting scheme is used to embed a secret message into the pixels whose pixel difference is located at the peak value within the histogram. Experimental results show that our algorithm can achieve higher embedding capacity and imperceptible distortion. Performance comparisons with other existing algorithms are also provided to demonstrate the feasibility of our proposed algorithm in reversible data hiding.     

基于三次拉格朗日插值的自适应图像缩放

传统的插值算法由于低通滤波效应通常会使目标图像边缘模糊,难以得到满意的视觉效果.为了取得较好的图像缩放质量,提出一种基于三次拉格朗日插值的自适应图像缩放算法.该算法首先计算目标像素点周围三组源像素点的方差,选取方差最小的一组源像素点,然后采用三次拉格朗日插值公式求得目标像素点的灰度值.实验结果表明,本文算法所得的目标图像边缘清晰,且算法复杂度较低,便于硬件实现,可以实现实时图像缩放.     

基于边缘复杂度和插值法的隐写算法

为了在提高隐写容量的同时保持较好的不可感知性, 依据人眼对图像边缘区域变化不敏感的特性, 提出一种新的自适应隐藏算法。该方案完善了图像边缘复杂度的描述方法, 利用边缘检测理论计算出像素的嵌入强度, 然后通过改进的插值法, 根据嵌入强度, 对图像像素进行插值, 构造出插值点与基准点之间的冗余空间, 从而嵌入相应数据量的秘密信息。实验结果表明, 与传统算法相比, 该方法提高了隐写容量并具有较好的隐蔽性。     

High-capacity image hiding scheme based on vector quantization

A novel grayscale image hiding scheme that is capable of hiding multiple secret images into a host image of the same size is proposed in this paper. The secret images to be hidden are first compressed by vector quantization with additional index compression process. Then, the compressed secret images are encrypted and embedded into the least-significant bits of the host pixels. To provide good image quality of the stego-image, the modulus function and the image property are employed to hide the secret bits into the host pixels and determine the number of hidden bits in each host pixel, respectively. According to the results, the proposed scheme provides a higher hiding capacity and a higher degree of security than that of the virtual image cryptosystem.     

Inter-view local texture analysis based stereo image reversible data hiding

To enhance security of three-dimensional images, an inter-view local texture analysis (ILTA) based stereo image reversible data hiding method is presented. Due to low accuracy of existing predictors, two novel predictors are proposed to improve the prediction precision. In the first predictor, a texture analysis model is built by using ILTA, in which the texture similarity between a pair of matched pixels in the stereo image is used to classify pixels into horizontal texture, vertical texture, smooth and complex types. Thus, the accurate prediction is adaptively computed by considering the pixel type. Moreover, an intra-view based predictor as the second predictor is also described to predict pixels by optimal weights finding (OWF). Since ILTA and OWF predictors are combined to predict pixels in the stereo image, sharp prediction error histograms of two views are both constructed, and then multi-level histogram shifting is used to embed secret data reversibly for obtaining low image distortion and high embedding capacity. Experimental results demonstrates that ILTA and OWF predictors can obtain precise predicted values, and the proposed data hiding method outperforms some state-of-the-art data hiding methods in terms of embedding capacity and quality of stego stereo image.     

Lossless data hiding for absolute moment block truncation coding using histogram modification

This paper presents a lossless data hiding method for an absolute moment block truncation coding (AMBTC) images, which is a compressed grayscale image. It is not easy to hide secret data in an AMBTC-compressed image because it is composed of bit planes. Thus, it is very sensitive to change some pixels. Nevertheless, to improve the hiding capacity, we present an efficient extension of the histogram modification technique by counting the coefficients of the bit planes in each 4 × 4 block. In addition, our proposed scheme has low complexity and achieves a high embedding capacity with the good perceptual quality compared to the prior arts. In an experiment, we verified our proposed data hiding scheme through the comparison with previous methods.