利用改进整数变换实现图像无损信息隐藏

为了在图像中实现无损信息隐藏,并提高数据嵌入容量和隐蔽性,给出一种基于改进整数变换的无损信息隐藏方法。首先对图像块采用改进算法进行整数变换,使得变换前后图像块引入失真较少,然后自适应选择整数变换后引入失真较小的可修改图像块进行整数变换,并嵌入较大数据量的机密信息,在公共信道进行传输后接收端能正确提取机密信息,并无损恢复原宿主图像。实验结果表明,该方法具有较大的数据嵌入容量和较好的隐蔽性,可用于医学图像中隐藏病历信息及遥感、军事图像的无损隐秘传输等领域。     

Quadruple Difference Expansion-Based Reversible Data Hiding Method for Digital Images

ABSTRACT

Lossless data hiding is a special type of data hiding technique that guarantees not only the secret data but also the ability of cover media to be reconstructed without any distortion. A latest lossless data hiding technique is proposed by Hong Lin Jin's that is based on hiding only one data bit in the spatial domain in gray-level image. However, this method uses double difference expansion to embed bits which results in a small embedding capacity. For this purpose, we propose an improved algorithm with the potential of increasing the payload capacity and maintaining good image quality. The proposed improved algorithm is characterized by two aspects. First, the proposed improved reversible data hiding scheme is enhanced to exhibit data hiding in color palette images. Second, the embedding level is improved by using quadruple difference expansion to guarantee the embedding of 2-bit data into color images. Experiments of the proposed improved method have been conducted over several well-known test images. The results show that the proposed improved method significantly improves the embedding capacity over Hong Lin Jin's scheme by the range of 15–35% for grayscale images and 20–46% for color images while still maintaining the quality of the stego-images.     

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.     

Huffman-code strategies to improve MFCVQ-based reversible data hiding for VQ indexes

Data hiding, which embeds secret data into cover media, is one type of technology used to achieve the multimedia security. A reversible data hiding method has the characteristic that the cover media can be completely reconstructed after secret data are extracted. Recently, some reversible data hiding schemes have focused on the vector quantization (VQ)-compressed format. Using the modified fast correlation vector quantization (MFCVQ) concept, Lu et al. proposed a reversible data hiding scheme for VQ-index tables. In this paper, a new MFCVQ-based scheme is proposed. Specifically, our method will enlarge the embedding capacities by embedding multiple bits into a VQ index, thereby reducing the compressed bit rates by applying the Huffman-code concept and the 0-centered classification. Experimental results indicate that this method has greater pure embedding capacities and fewer compressed bit rates than that of previous MFCVQ-based methods.     

基于预测误差修改的医学图像数据隐藏方法

针对医学图像可逆数据隐藏高保真、高容量、高频繁地插入和可逆性等特点,提出了一种基于预测误差修改的可逆数据隐藏算法,不需要对图像进行分块处理,利用加权线性预测得到预测图像,在预测误差直方图中采用4峰值点进行隐秘数据嵌入,较好地解决了医学图像中出现得较多的溢出问题,并在保证图像质量的同时增加了嵌入容量。理论分析和实验结果证明了算法的优越性。     

Reversible steganography based on side match and hit pattern for VQ-compressed images

Data hiding is an important technique in multimedia security. Multimedia data hiding techniques enable message senders to disguise secret data by embedding them into cover media. Thus, delivering secret messages is as easy as sending the cover media. Recently, many researchers have studied reversible data hiding for images. Those methods can reconstruct the original cover image and extract the embedded secret data from a stego-image. This study proposes a novel reversible steganographic method of embedding secret data into a vector quantization (VQ) compressed image by applying the concept of side match. The proposed method uses extra information, namely the hit pattern, to achieve reversibility. Moreover, its small hit pattern enables the embedding of the entire hit pattern along with the secret data in most cases. To optimize visual quality of the output stego-image, the method applies the concept of partitioned codebooks (state codebooks). The partition operation on the codebook uses a look-up table to minimize embedding and extraction time. We also propose the use of diagonal seed blocks to embed the entire hit pattern into the cover image without producing any extra control messages. Compared to the Chang and Lin method, the experimental results show that the proposed method has higher capacity, better visual quality, and shorter execution time.     

Multilevel reversible data hiding based on histogram modification of difference images

Reversible data hiding has drawn considerable attention in recent years. Reversibility allows original media to be completely recovered from marked media without distortion after embedded message has been extracted. In this paper we propose a multilevel reversible data hiding scheme based on the difference image histogram modification that uses the peak point to hide messages. Through a joint imperceptibility and hiding capacity evaluation, we show that our proposed scheme uses a multilevel hiding strategy to achieve large hiding capacity and keep distortion low. Performance comparisons with other existing reversible hiding schemes are provided to demonstrate the validity of our proposed scheme.     

Prediction-based reversible data hiding

For some applications such as satellite and medical images, reversible data hiding is the best solution to provide copyright protection or authentication. Being reversible, the decoder can extract the hidden data and recover the original image without distortion. In this paper, a reversible data hiding scheme based on prediction error expansion is proposed. The predictive value is computed by using various predictors. The secret data is embedded in the cover image by exploiting the expansion of the difference between a pixel and its predictive value. Experimental results show that our method is capable of providing a great embedding capacity without making noticeable distortion. In addition, the proposed scheme is also applicable to various predictors.     

Embedding capacity raising in reversible data hiding based on prediction of difference expansion

Most of the proposed methods of reversible data hiding based on difference expansion require location maps to recover cover images. Although the location map can be compressed by a lossless compression algorithm, this lowers embedding capacity and increases computational cost during the procedures of embedding and extracting. The study presents an adaptive reversible data scheme based on the prediction of difference expansion. Since each cover pixel generally resembles its surrounding pixels, most of the difference values between the cover pixels and their corresponding predictive pixels are small; therefore, the proposed scheme gains from embedding capacity by taking full advantage of the large quantities of smaller difference values where secret data can be embedded. The proposed scheme offers several advantages, namely, (1) the location map is no more required, (2) the embedding capacity can be adjusted depending on the practical applications, and (3) the high embedding capacity with minimal visual distortion can be achieved. Moreover, the experimental results demonstrate that the proposed scheme yields high embedding capacity by comparing the related schemes that are proposed recently.     

A new steganographic method for color and grayscale image hiding

In this paper, we present a steganographic method for embedding a color or a grayscale image in a true color image. Three types of secret images can be carried by the proposed method: hiding a color secret image, hiding a palette-based 256-color secret image, and hiding a grayscale image in a true color image. Secret data are protected by the conventional crypto system DES. We compare the image quality and hiding capacity of the proposed method with those of the scheme in Lin et al.’s scheme. According to the experimental results, the image quality of the proposed method is better than that of the Lin et al.’s scheme. In addition, annotation data can be hidden with the secret image in the host image. The hiding capacity of the proposed method is greater than that of other compared schemes. The experimental results show that the proposed method is a secure steganographic method that provides high hiding capacity and good image quality.     

Reversible data hiding based on block median preservation

This paper proposes a reversible data hiding scheme for gray level images. It exploits the high correlation among image block pixels to produce a difference histogram. Secret data is embedded based on a multi-level histogram shifting mechanism with reference to the integer median of each block. The image blocks are divided into four categories due to four corresponding embedding strategies, aiming at preserving the medians during data embedding. In decoder, the median pixels are retrieved first followed by the hidden data extraction, and the host image can be accurately recovered via an inverse histogram shifting mechanism after removing the secret data from the marked image. Experimental results validate the effectiveness of our scheme and demonstrate that it outperforms several previous methods in terms of capacity and marked image’s quality.     

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.     

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.     

结合层次结构和直方图平移的无损数据隐藏

针对现有基于差值直方图方法利用原始图像结构关系上的不足,提出了一种基于层次结构和差值直方图平移的无损数据隐藏方法RDH-HSDHS。RDH-HSDHS利用原始图像数据块中像素的差值形成直方图,充分利用图像中相邻像素间的相关性嵌入数据,为了进一步利用数据块中的参考像素进行数据嵌入,将参考像素组成新的图像进行下一层水印嵌入,直到当前层的嵌入容量小于解码所需的附加信息的长度或隐秘图像质量小于给定阈值。实验仿真结果表明,RDH-HSDHS能较好利用原始图像的全局和局部特性,在嵌入容量和隐秘图像质量之间达到较好的折中,在隐秘图像质量超过30 dB的同时,嵌入容量大于0.75 bit/pixel。另外,与相似方法的性能比较证明了提出方法的优势。该方法能有效应用于高质量需求的图像载体中进行信息隐藏。     

A high stego-image quality steganographic scheme with reversibility and high payload using multiple embedding strategy

Tian’s method is a breakthrough reversible data embedding scheme with high embedding capacity measured by bits per pixel (bpp) and good visual quality measured by peak signal-to-noise ratio (PSNR). However, the embedding capacity and visual quality of this method can be significantly improved. Thus, we propose a simple reversible steganographic scheme in spatial domain for digital images by using the multiple embedding strategy. The proposed method horizontally and vertically embeds one secret bit into one cover pixel pair. The experimental results show that the proposed reversible steganographic method achieves good visual quality and high embedding capacity. Specifically, with the one-layer embedding, the proposed method can obtain the embedding capacity of more than 0.5 bpp and the PSNR value greater than 54 dB for all test images. Especially, with the five-layer embedding, the proposed method has the embedding capacity of more than 2 bpp and the PSNR value higher than 52 dB for all test images. Therefore, the proposed method surpasses many existing reversible data embedding methods in terms of visual quality and embedding capacity.     

High capacity lossless data embedding technique for palette images based on histogram analysis

Recently data embedding over images has drawn tremendous interest, using either lossy or lossless techniques. Although lossy techniques can allow large hiding capacity, host image cannot be recovered with high fidelity. Some applications require exact recovery of the host image, i.e. in medicine patient data can be embedded without affecting the medical image. In general lossless data hiding techniques suffer from limited capacity as the host image should be kept intact. In this paper a lossless embedding technique is proposed. In this technique image histograms are analyzed to identify the embedding capacity of different image types. Histogram maxima and minima are used in embedding capacity estimation. The proposed technique gives hiding capacity that can reach up to 50% of the host image size for images with large homochromatic regions (cartoons-like). In fact, our study showed that the embedding capacity is not only affected by the host image size but also by its histogram distribution. The data embedding and extraction is performed using simple processing operations that can save on power consumption for wireless devices.     

Using quad smoothness to efficiently control capacity-distortion of reversible data hiding

One of the main uses of data hiding is to protect secret messages being transmitted on the Internet. Reversible data hiding can fully recover the original host image after extracting the secret message. It is especially suitable for applications where, after extracting the secret message, the quality of the recovered host image cannot be compromised, such as for medical or military image data.Many difference-expansion-based (DE-based) reversible data hiding methods have made use of a threshold value to control the stego-image's quality. Usually repeated trial and error is required to find a relatively good threshold with acceptable capacity-distortion behavior. This paper introduces a scheme that does not require a threshold value, such as is used in Alattar's quad-based reversible data hiding. It applies a prediction of quad of quads smoothness to determine the embedding sequence. The proposed scheme is shown to perform better than other DE-based schemes. Results showed that it has the ability of maintaining embedding quality at all capacity levels, especially when the embedding capacity is at low to medium levels.     

NEQR量子图像下的差分扩展可逆数据隐藏算法

量子图像安全处理是一个新兴的研究领域,而量子图像数据隐藏是量子图像安全处理技术的一种,在不损害载体的情况下可用于保护量子图像的版权和认证量子图像是否完整。目前尚缺乏对量子图像可逆数据隐藏的详细技术研究。结合差值扩展技术,本文提出了一种量子图像可逆数据隐藏算法：1）选用NEQR量子图像表示法来表示图像;2）借鉴经典的差值扩展算法,在NEQR量子图像上对量子比特进行处理,可逆嵌入数据;3）设计了信息嵌入、信息提取和载体无损恢复的量子线路图,并进行了仿真。基于经典图像的实验结果表明,本文算法是可逆的,可用于将来对量子图像的认证和保护。     

多层嵌入的多光谱图像可逆信息隐藏算法

针对现有可逆信息隐藏算法嵌入容量偏低、不适合多光谱图像等问题,提出一种基于预测误差直方图移位和波段顺序重排的多层嵌入的多光谱图像可逆信息隐藏算法。对于每层嵌入,首先用提出的排序算法对波段进行重新排序,然后利用多光谱图像的空间相关性和谱间相关性对图像进行自适应联合预测,最后通过预测误差直方图移位技术嵌入秘密信息。Landsat卫星多光谱图像仿真结果表明,提出的算法和典型可逆信息隐藏算法相比具有更好的视觉质量和更大的隐藏容量。     

A new robust lossless data hiding scheme and its application to color medical images

The last few years witnessed an increased interest in the robust lossless data hiding schemes because they can verify the main requirements of the lossless data hiding (i.e., reversibility, capacity, and invisibility) and at the same time provide robustness against attacks. The reversibility is one of the important requirements of those methods. Another important requirement is the improvement of the robustness against attacks. The methods that improve the robustness are at the cost of reducing capacity and invisibility. Taking into consideration the need for improving the four requirements that have been mentioned above, this paper presents a novel robust lossless data hiding method in the transform domain. The proposed algorithm depends on transforming non-overlapping blocks of the host image using Slantlet transform (SLT) matrix and embedding data bits by modifying the difference between the mean values of the SLT coefficients in the high frequency subbands. As a practical application, the proposed algorithm has been adjusted in order to be applied to the color medical images. The data bits can be embedded not only in a single channel but also in the three channels of the RGB color image and thus further improving the embedding capacity. The results of the experiments that were conducted and the comparisons with the previous robust lossless data hiding (i.e., robust reversible watermarking) methods prove the effectiveness of the proposed algorithm.