Reversible data hiding for high dynamic range images using edge information

Multimedia Tools and Applications - In this work, a reversible data hiding (RDH) algorithm is proposed for high dynamic range (HDR) images containing an additional luminance channel. Since...     

Separable reversible data hiding in encrypted images based on scalable blocks

This paper proposes a new separable reversible data hiding method for encrypted images. Proposed scheme employs the pixel redundancy of natural images to construct embedding space. First, cover image is divided into multiple blocks with different scales. According to the pixel average value of each block, the lowest two bits of every pixel are vacated as reserved rooms. Subsequently, the whole image is encrypted by using stream cipher and the secret messages are finally embedded into the reserved rooms by the embedding key. Proposed scheme is separable in the sense that the recipient can achieve different function by the following ways: (a) If the recipient has only decryption key, an approximation plaintext image containing the embedded information can be obtained. (b) If the recipient has only embedded key, secret messages can be extracted correctly. (c) If the recipient has both decryption key and embedded key, he can not only extract the secret messages, but recover the original cover image perfectly. Extensive experiments are performed to show that our proposed schemes outperform existing reversible data hiding schemes in terms of visual quality, embedding capacity and security performance, even if a large-scale image database is used.

     

Data hiding using pseudo magic squares for embedding high payload in digital images

Multimedia Tools and Applications - In this paper, a novel information hiding scheme based on pseudo magic squares is proposed. The pseudo magic square pattern is generated using the Knight’s...     

Data hiding in AMBTC images using quantization level modification and perturbation technique

Multimedia Tools and Applications - A novel data hiding method for Absolute Moment Block Truncation Coding (AMBTC) compressed image based on quantization level modification is proposed. Blocks of...     

Data hiding based on compressed VQ indices of images

The VQ-based data hiding technique has not received much attention compared to various spatial domain-based data hiding techniques in digital images. Consequently, a new data hiding scheme, applied in the VQ-compressed domain of cover images, is introduced in this article. To provide more hiding capacity for secret data and to keep an acceptable bit rate for the compressed cover images, the search-order-coding (SOC) algorithm was implemented to compress the VQ indices of the cover images in the process of data hiding. During the process of data hiding, the proposed scheme embeds secret data into the compressed VQ indices of the cover image adaptively, adjusting the bit rate according to the size of the secret data and the compressed cover image. In addition, the hiding process induces no extra coding distortion. Experiments show that the receiver can efficiently receive both the secret data and the compressed cover image simultaneously with an acceptable bit rate. Simulation results also demonstrate that our proposed scheme outperforms earlier proposed methods.     

Data hiding in scrambled images: A new double layer security data hiding technique

The contemporary multimedia and communication technology has made it possible to replicate and distribute digital media easier and faster. This ease of availability causes the problem of exposing transmitted digital data on the network with the risk of being copied or intercepted illegally. Many cryptographic techniques are in vogue to encrypt the data before transmission to avert any security problems. However, disguised appearance of the encrypted data makes the adversary suspicious and increases the chances of malicious attack. In such a scenario data hiding has received significant attention as an alternate way to ensure data security. This paper presents a data hiding technique based on the concepts of scrambling and pseudorandom data hiding; to provide a data hiding system with two layer security to the embedded data, and good perceptual transparency of the stego images. The proposed system uses the novel concept of embedding the secret data in scrambled (encrypted) cover images. The data embedding is carried out in the Intermediate Significant and least significant bit planes of encrypted image at the predetermined locations pointed to by Pseudorandom Address Space (PAS) and Address Space Direction Pointer (ASDP). Experimental results prove the efficacy of scheme viz-a-viz various parameters of interest.     

Data hiding method using image interpolation

Data hiding is to conceal the existence of secret data. A reversible data hiding method can extract the cover image without any distortion from the stego-image after the hidden data have been extracted. This paper proposes a new interpolation and a data hiding method. The proposed scaling-up neighbor mean interpolation method has a low-time complexity and high-calculation speed. The proposed data hiding method is based on interpolation. Comparison on data hiding methods is divided into reversible or not. Our experimental results show the proposed method can embed a large amount of secret data while keeping a very high visual quality, the PSNR is guaranteed to be higher than 35 dB compared with other reversible data hiding methods. And also capacity is larger than any other reversible data hiding methods and comparable to other data hiding methods.     

Reversible data hiding method using meaningful encrypted images

Encrypted image-based reversible data hiding methods have recently been introduced to conduct research on data encryption. In these methods, an image provider generates encrypted images that are supplied to a data sender. The data sender embeds secret data into the images in order to securely communicate with a data receiver. The data receiver can extract secret data and recover the cover image from the encrypted images. Past research has shown that attackers can easily become suspicious in such cases since all images are scrambled during communication. In this paper, we propose a reversible data hiding method that uses meaningful encrypted images. The proposed method is independent from image provider, data sender, and data receiver respectively by separating the images used and the secret data hidden from each other. In addition, the proposed method reduces distortion during image encryption, and features a data embedding scheme to conceal the existence of secret data from attackers. Experimental results show that the proposed method has high embedding capacity and yields satisfactory image quality with a meaningful image.     

A nonlinear laplace operator as edge detector in noisy images

An edge detection scheme is developed robust enough to perform well over a wide range of signal-to-noise ratios. It is based upon the detection of zero crossings in the output image of a nonlinear Laplace filter. Specific characterizations of the nonlinear Laplacian are its adaptive orientation to the direction of the gradient and its inherent masks which permit the development of approximately circular (isotropic) filters. We have investigated the relation between the locally optimal filter parameters, smoothing size, and filter size, and the SNR of the image to be processed. A quantitative evaluation shows that our edge detector performs at least as well—and in most cases much better—than edge detectors. At very low signal-to-noise ratios, our edge detector is superior to all others tested.     

Information hiding in edges: A high capacity information hiding technique using hybrid edge detection

The multimedia security is becoming more and more important as the data being exchanged on the Internet is increasing exponentially. Though cryptography is one of the methods which is used to secure the data during transit, but the camouflaged appearance of the scrambled data alerts the adversary about some critical information being shared. In such a scenario, steganography has been used as an alternate solution to secure the secret information. In this paper a color image steganographic algorithm based on hybrid edge detection is proposed. The color image is partitioned into constituent Red (R), Green (G) and Blue (B) planes. Hybrid edge detection is used for finding the edge and non-edge pixels of Green and Blue planes of cover image. The Green and Blue planes are used for hiding the data while Red plane holds the pixel status (whether edge or non-edge) of these planes. The RC4 encryption algorithm is used to encrypt secret message before embedding it in the cover image to enhance security of the secret data. A fragile watermark/logo (whose size is less than 1% of total secret data) has been embedded, besides secret data in the cover image, to facilitate content authentication and early tamper detection. At the receiver, firstly logo is extracted. If it is same as one embedded at transmitter, indicating that secret data has not been altered during transit, secret data is extracted. Otherwise (if extracted logo is not same as used at input) the receiver does not waste critical time to extract compromised data but sends an automatic retransmission request. Experimental investigations reveal that the proposed scheme is capable of providing high quality of stego-images for a fairly high pay load. A comparison of the proposed technique with some state of art schemes substantiates the above arguments.     

利用可变预测的密文域可逆信息隐藏

目的 随着云计算和云存储场景中用户隐私保护的需求日益增加,密文域图像可逆信息隐藏（reversible data hiding in encrytpted images,RDHEI）受到了广泛关注。然而大多数RDHEI算法以提升嵌入率和保障图像加密安全性为目的,复杂化图像的预处理操作。为此,提出一种基于可变预测和多MSB(most significant bit)替换的密文域图像可逆信息隐藏算法。方法 提出可变预测位平面翻转策略,用相邻像素值迭代预测当前像素值的多位最高有效位。若预测值比翻转值更接近目标像素值,则当前预测位平面可以用于信息隐藏,将其比特值修改为0。同时,用位置图自适应地标记可嵌入像素点。所生成的位置图具有稀疏特征,可以使用算术编码无损压缩。最后,对预留空间后的图像进行加密,通过多MSB替换的策略嵌入隐秘信息和压缩位置图。结果 经实验测试,本文算法在BOWS-2(break our watermarking system 2nd)数据集上平均嵌入率为2.953 bit/像素,并记录了1 000幅图像在预处理前后的每个位平面信息熵,其中最高位平面的信息熵比原始MSB下降了0...     

Reversible data hiding using side-match predictions on steganographic images

Information hiding is an important method to achieve multi-media security. Recently, many researchers have paid attention to the reversible data hiding scheme, which can completely recover original multi-media files after the embedded data are extracted. In this paper, a side-match approach is proposed to achieve more capacity in histogram-based reversible data hiding for grayscale images. The histogram is created by exploiting the difference in all the values between pixels and their predictedive values. Experimental results show that our method is capable of providing a great embedding capacity without causing noticeable distortion. In one-level hiding, where it has the best capacity, our method conserves image qualities larger than 48 dB. Furthermore, in multilevel hiding, a rotation strategy is proposed to further improve image qualities. Experimental results show that our method performs better than other existing methods in multilevel hiding cases.     

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.     

分块自适应JPEG图像数据隐藏算法*

为提高隐秘JPEG图像视觉质量与隐藏容量,在修改JPEG缺省量化表的前提下,针对JPEG图像提出一种自适应数据隐藏算法。该算法首先根据图像分块视觉特性确定用于数据隐藏的图像分块,然后应用LSB替换方法修改DCT域量化后AC系数以嵌入秘密数据。实验结果表明,该算法在保证较好透明性的同时,显著提高了JPEG图像隐藏容量,与其他同类算法相比,隐藏容量提高约21%。该方案可为互联网环境图像实时通信提供安全保障手段。     

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.     

DWT-based reversible information hiding scheme using prediction-error-expansion in multimedia images

Peer-to-Peer Networking and Applications - This article presents an information hiding scheme for Multimedia IoT (MIoT) applications, with particular concern the services where the context of cover...     

Area segmentation of images using edge points

A new method for segmenting images using abrupt changes in intensity (edge points) to separate regions of smoothly varying intensity is discussed. Region segmentation using edge points has not been very successful in the past because small gaps would allow merging of dissimilar regions. The present method uses an expansion-contraction technique in which the edge regions are first expanded to close gaps and then contracted after the separate uniform regions have been identified. In order to preserve small uniform regions, the process is performed iteratively from small to large expansions with no expansion for edge regions that separate different uniform regions. The final result is a set of uniform intensity regions (usually less than 100) and a set of edge boundary regions. The program has successfully segmented scenes with industrial parts, landscapes, and integrated circuit chips.     

整数变换实现大容量图像无损信息隐藏

目的 针对图像无损信息隐藏中嵌入容量和隐藏图像质量问题,描述了一种基于可逆整数变换算法在图像中实现较大容量数据嵌入的无损隐藏方法。方法 定义的可逆整数变换算法先计算图像块n个像素点的整数平均值,在整数变换过程中将各像素点与平均值之间的差值扩展到4倍。结果 整数变换后图像块所有像素点最低两位有效位相同,产生的冗余信息可用来嵌入2(n-1)比特数据。结论 给出了一种新的可逆整数变换算法并实现较大容量图像无损信息隐藏,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藏图像质量,嵌入数据和原宿主图像均能从隐藏图像中无失真恢复。     

Reversible data hiding of high payload using local edge sensing prediction

This paper tries to analyse a new framework in lossless data hiding research. Its key is how adaptively to get better difference image architectures for given applications. A unique sampled pattern is introduced and described in term of high-similar interpolation image. The proposed method updates a type of conventional algorithm, smoothly accesses to current reconstruction implementation, and outperforms solo weighing approach, particularly in the perceptual quality. Combinational weight factor can be adaptively adjusted by estimating interpolation errors around neighbor pixels. Seeking higher peak value in the difference-image is also our concerns. As an entire algorithm, reversible data hiding based on histogram-difference-shift is also reported. Simulations results demonstrate and verify that our approach is much effective than some recent methods with good generalization performance.     

Parallel edge splatting for scalable dynamic graph visualization

We present a novel dynamic graph visualization technique based on node-link diagrams. The graphs are drawn side-byside from left to right as a sequence of narrow stripes that are placed perpendicular to the horizontal time line. The hierarchically organized vertices of the graphs are arranged on vertical, parallel lines that bound the stripes; directed edges connect these vertices from left to right. To address massive overplotting of edges in huge graphs, we employ a splatting approach that transforms the edges to a pixel-based scalar field. This field represents the edge densities in a scalable way and is depicted by non-linear color mapping. The visualization method is complemented by interaction techniques that support data exploration by aggregation, filtering, brushing, and selective data zooming. Furthermore, we formalize graph patterns so that they can be interactively highlighted on demand. A case study on software releases explores the evolution of call graphs extracted from the JUnit open source software project. In a second application, we demonstrate the scalability of our approach by applying it to a bibliography dataset containing more than 1.5 million paper titles from 60 years of research history producing a vast amount of relations between title words.