Hybrid prediction-based pixel-value-ordering method for reversible data hiding

Pixel-value-ordering (PVO) is an effective and promising method of reversible data hiding (RDH) and has received much attention in recent years. To improve performance, a pixel-based PVO (PPVO) method was recently introduced to predict the pixels to be embedded in a pixel-wise manner instead of the block-wise manner used by PVO. However, for PPVO, the surrounding neighbors of the predicted pixels are underutilized; moreover, its embedding does not adapt to the local complexity of the image to be embedded. To overcome the shortcomings of PPVO, this paper proposes a novel PVO method based on hybrid prediction for RDH. First, the surrounding neighbors of the pixel to be predicted are fully utilized by a hybrid prediction method, which combines rhombus prediction and pixel-wise prediction. Second, a modified embedding scheme based on multiple histograms is presented for adaptive embedding. Experimental results show the superior performance of the proposed method by comparing it with state-of-the-art RDH methods.     

A two-level secure data hiding algorithm for video steganography

Multidimensional Systems and Signal Processing - Sensitive data is exchanged frequently through wired or wireless communication that are vulnerable to unauthorized interception. Cryptography is a...     

Controlling hiding capacity using image characteristics with a 2D-DE data hiding scheme

Reversible data hiding techniques have gained much attention during the last few years because of the losslessness requirements of critical applications in military and medical fields. Among the various reversible data hiding techniques, difference expansion (DE) technique is one of the most popular techniques. The most common thing between DE-based schemes is their dependence on one or more thresholds. The threshold is used in order to control the hiding capacity aiming at keeping high visual quality of the embedded image. However, there is no such automatic way to predict or determine those thresholds as they are usually predefined. In this paper, we study the possibility of utilizing image characteristics as thresholds with a block based two-dimensional difference expansion scheme (2D-DE). The experimental results show that a threshold based on standard deviation may be used to control the hiding capacity and this leads to enhance the visual quality.     

基于Web的图像LSB隐写教学系统

为了让学生更好理解图像最不重要位(LSB)隐写算法,文中设计了一个基于Web的教学系统。该系统在ASP.net环境下开发,用C#语言编程实现,提供载体图像选择功能,实现了文本信息和数据文件的嵌入和提取,对学生理解图像LSB隐写算法有较好帮助。     

Improved interpretation of satellite altimeter data using genetic algorithms

Genetic algorithms (GA) are optimization techniques that are based on the mechanics of evolution and natural selection. They take advantage of the power of cumulative selection, in which successive incremental improvements in a solution structure become the basis for continued development. A GA is an iterative procedure that maintains a population of organisms (candidate solutions). Through successive generations (iterations), the population as a whole improves in a simulation of Darwinism's “survival of the fittest.” GAs have been shown to be successful where noise significantly reduces the ability of other search techniques to work effectively. Satellite altimetry provides useful information about oceanographic phenomena. It provides rapid global coverage of the oceans and is not as severely hampered by cloud cover as infrared imagery. Despite these and other benefits, several factors lead to significant difficulty in interpretation. The GA approach to the improved interpretation of satellite data involves the representation of the ocean surface model as a string of parameters or coefficients from the model. The GA searches in parallel a population of such representations (organisms) to obtain the individual that is best suited to survive, that is, the fittest as measured with respect to some fitness function. The fittest organism is the one that best represents the ocean surface model with respect to the altimeter data.     

一种大容量的图像可逆信息隐藏算法

提出了一种大容量的可逆信息隐藏算法的详细实现方案.利用图像直方图中的多个零点或者最小点,通过修改图像像素的灰度值来隐藏信息,并通过统计分析给出常用的信息隐藏的模型和算法.实验表明,该方法不仅可以进行大容量的信息隐藏,而且相对原始图像能够达到满意的峰值信噪比(PSNR),具有良好的性能.     

机要数据分析与数据保护方法

机要数据存在于某个范围内,在未经许可的情况下不得访问,这些数据直接关系到各个政府、企业、研究机构的核心机密,甚至威胁到国家安全。按照数据特点的不同,机要数据通常包括:机要文件、电子图纸、财务资料、专利技术、运营统计。 机要数据的主要存在形式包括:办公类电子文件,常见的格式有DOC、XLS、MDB、WPS、PDF 等;图形类文件,常见的图类型文件通常保存的格式比较特殊,且基本都使用特定的应用程序打开。 机要数据主要分布在机要类政府部分、研究类机构、制造型企业、财务部门。 对于这种机要数据存在的网络环境,通常存在以下特点:…     

基于遗传算法和高隐藏容量的数字图像隐写算法

为了获得更大的隐写容量和更高的隐写安全级别,提出一种基于遗传算法和高隐藏容量的数字图像安全隐写算法。将隐写术作为一个搜索问题进行建模,遗传算法的目的是在宿主图像中找到最优的方向和最优的起始点用于隐藏加密数据,使得隐写图像获取最大的峰值信噪比,其拟合函数为峰值信噪比。首先准备宿主图像,机密图像和染色体,利用比特位面和比特方向基因将宿主像素序列转化为比特位序列;然后将机密像素位嵌入到相应的比特像素位;最后利用拟合函数决定迭代结束次数。运用峰值信噪比(PSNR)和结构相似性度量(SSIM)评估隐写结果,与其他隐写算法相比,该算法提高了隐写质量和安全性,PSNR和SSIM在大多数情况下均高于其他算法,此外,隐藏容量相当可观,可高达49.5%。     

Convergent block-iterative algorithms for image reconstruction frominconsistent data

It has been shown that convergence to a solution can be significantly accelerated for a number of iterative image reconstruction algorithms, including simultaneous Cimmino-type algorithms, the "expectation maximization" method for maximizing likelihood (EMML) and the simultaneous multiplicative algebraic reconstruction technique (SMART), through the use of rescaled block-iterative (BI) methods. These BI methods involve partitioning the data into disjoint subsets and using only one subset at each step of the iteration. One drawback of these methods is their failure to converge to an approximate solution in the inconsistent case, in which no image consistent with the data exists; they are always observed to produce limit cycles (LCs) of distinct images, through which the algorithm cycles. No one of these images provides a suitable solution, in general. The question that arises then is whether or not these LC vectors retain sufficient information to construct from them a suitable approximate solution; we show that they do. To demonstrate that, we employ a "feedback" technique in which the LC vectors are used to produce a new "data" vector, and the algorithm restarted. Convergence of this nested iterative scheme to an approximate solution is then proven. Preliminary work also suggests that this feedback method may be incorporated in a practical reconstruction method.     

A PVD-based data hiding method with histogram preserving using pixel pair matching

This paper proposed a Pixel Value Difference (PVD) based method to embed unequal amounts of secret information using pixel complexity. In previous PVD methods, embedding was sequential. Therefore, secret information can be easily accessed by a third party by the sequence. These methods are also easily detected by difference histogram analysis since their difference histograms showed unnatural shapes when compared to the cover image. The IMF-PVD method has a smoother and more natural difference histogram but its payload is not improved over the other PVD-based methods. In the proposed method, secret information was embedded in 2×2 embedding cells which were composed with randomized embedding units to reduce the falling-off-boundary problem and to eliminate sequential embedding. Comparison results with IMF-PVD showed that the proposed method significantly had higher payload and image quality. Furthermore, the payload size may be adjusted by reference tables and threshold. Results also showed that the embedded information is not easily detected by the difference histogram analysis and chi-square test.     

Halftone image data hiding with intensity selection and connection selection

In this paper, we propose two novel algorithms, namely intensity selection (IS) and connection selection (CS), that can be applied to the existing halftone image data hiding algorithms DHSPT, DHPT and DHST to achieve improved visual quality. The proposed algorithms generalize the hidden data representation and select the best location out of a set of candidate locations for the application of DHSPT, DHPT or DHST. The two algorithms provide trade-off between visual quality and computational complexity. The IS yields higher visual quality but requires either the original multi-tone image or the inverse-halftoned image which implies high computation requirement. The CS has lower visual quality than IS but requires neither the original nor the inverse-halftoned images. Some objective visual quality measures are defined. Our experiments suggest that significant improvement in visual quality can be achieved, especially when the number of candidate locations is large.     

Correlation-and-bit-aware additive spread spectrum data hiding for Laplacian distributed host image signals

Watermarking and data hiding are important tools for copyright protection of digital media contents. To reduce the interference effect of the host signal and improve the decoding performance in the popular additive Spread Spectrum (ASS) embedding scheme, we have proposed a novel correlation-and-bit-aware additive Spread Spectrum (CASS) embedding scheme for the Gaussian distributed host signal. However, in practice, the discrete cosine transform (DCT) coefficients of real images follow the Laplacian distribution. For practical application of CASS to real images in the DCT domain, this paper proposes a CASS data hiding scheme for the Laplacian distributed host image signal. To extract the hidden message bits, we derive an optimal decoder of the ASS scheme for the Laplacian distributed host signal. The bit-error ratio (BER) of ASS and proposed CASS schemes are analyzed in theory. Finally, Monte Carlo simulations and tests on real images are carried out to illustrate the decoding performance of the ASS and proposed CASS schemes. Compared with the traditional ASS scheme, the proposed CASS scheme maintains the simplicity of the decoder, significantly reduces the host effect in data hiding and improves the decoding performance remarkably. As an extension, we discuss the CASS scheme for the generalized Gaussian distribution (GGD) distributed host signal in brief.     

Shearlet变换和奇异值分解的图像隐藏方法

为了更好地平衡Shearlet域图像隐藏不可见性、鲁棒性和算法时间复杂度之间的关系,提出了一种基于Shearlet变换和奇异值分解的图像隐藏方法。利用Shearlet变换的能量聚集性、小波包分解低频子带抗攻击性强和矩阵奇异值良好的稳定性,载体图像先进行Shearlet分解,得到的低频子带再进行二级小波包分解。将秘密图像的重要信息位平面隐藏到小波包分解低频系数的奇异值矩阵中,次要信息嵌入Shearlet高频子带中。实验表明,该算法对高斯噪声、滤波和剪切等攻击都有较好的鲁棒性,同时,不可见性较好,时间复杂度较低。     

一种基于回声隐藏的倒谱提取优化算法

在回声隐藏算法的基础上,提出一种倒谱提取优化算法.新算法改进了传统倒谱对回声位置的判断标准,提高了数据提取正确率.通过引入原始语音数据的倒谱值作为参照量,重新定义回声位置的判断标准,弥补了传统倒谱算法的缺陷.MATLAB仿真结果证明:即便在回声衰减系数较小的情况下,算法依然能明显地提高数据提取的正确率,且稳定性良好.     

基于模糊和遗传算法的阈值分割方法

提出了一种阈值分割方法。本算法将模糊集理论和遗传算法有机地结合起来,它是一种有监督的分割方法,首先确定图像阈值的数目,然后将灰度图像模糊化,确定准则函数,采用遗传算法求得意了优解,最后经过后处理得到最终分割结果。实验表明该方法运算速度快,且对噪声不敏感,具有较高的鲁棒性。     

Reversible data hiding using invariant pixel-value-ordering and prediction-error expansion

Recently, Li et al. proposed a reversible data hiding (RDH) method based on pixel-value-ordering (PVO) and prediction-error expansion. In their method, the maximum and the minimum of a pixel block are predicted and modified to embed data, and the reversibility is guaranteed by keeping PVO of each block invariant after embedding. In this paper, a novel RDH method is proposed by extending Li et al.׳s work. Instead of considering only a single pixel with maximum (or minimum) value of a block, all maximum-valued (or minimum-valued) pixels are taken as a unit to embed data. Specifically, the maximum-valued (or minimum-valued) pixels are first predicted and then modified together such that they are either unchanged or increased by 1 (or decreased by 1) in value at the same time. Comparing our method with Li et al.׳s, more blocks suitable for RDH are utilized and image redundancy is better exploited. Moreover, a mechanism of advisable payload partition and pixel-block-selection is adopted to optimize the embedding performance in terms of capacity-distortion behavior. Experimental results verify that our method outperforms Li et al.׳s and some other state-of-the-art works.     

A novel high-performance reversible data hiding scheme using SMVQ and improved locally adaptive coding method

Reversible data hiding is a method that not only embeds secret data but also reconstructs the original cover image without distortion after the confidential data are extracted. In this paper, we propose novel reversible data hiding scheme that can embed high capacity of secret bits and recover image after data extraction. Our proposed scheme depends on the locally adaptive coding scheme (LAC) as Chang&Nguyen’s scheme and SMVQ scheme. Experimental results show that the compression rate of our proposed scheme is 0.33 bpp on average. To embed secret bits we propose the normal-hiding scheme and the over-hiding scheme which have an average embedding rate of 2.01 bpi and 3.01 bpi, more than that of Chang&Nguyen’s scheme (1.36 bpi). The normal-hiding scheme and the over-hiding scheme also has high embedding efficiency of 0.28 and 0.36 on average, which are better than that of Chang&Kieu’s scheme (0.12), Chang&Nguyen’s scheme (0.18) and Chang&Nguyen’s scheme (0.16).     

Matrix encoding for data hiding using multilayer video coding and transcoding solutions

This paper proposes a multitier data hiding solution in MPEG video using matrix encoding. In the first tier of the proposed solution, raw video is encoded into two layers using multilayer Signal to Noise Ratio (SNR) encoding. During the multilayer encoding process, the quantization scales and coding parameters are stored. In the second tier, message bits are embedded in the stored quantization scales using matrix encoding. In the third and last tier, the raw video is encoded again into two layers using the modulated quantization scales and coding parameters of the first encoder. The proposed multitier solution is extended by replacing the multilayer encoder with a multilayer transcoder to accommodate situations in which the video exists in pre-coded format only. By the use of multilayer encoder or transcoding, we show that the message payload can be doubled without adversely affecting the coding quality or bitrate of the host video. We also show that message embedding using matrix encoding can be extended to modulate motion vectors. The paper also proposes two solutions for motion vector modulation based on the availability of the raw video. In comparison to existing work, the proposed solutions have higher message payloads, lower degradation in video quality and result in reduced excessive bitrate.     

基于图像分存的离散小波数据隐藏算法

数字图像分存技术将一幅秘密图像分解成几幅无意义或者杂乱无章的图像进行存储或传输,获得其中部分分存信息就能恢复出原始图像信息,以便增加图像信息的安全性.文中提出了一种基于图像分存和离散小波变换的的信息隐藏算法.首先利用置乱变换对传输图像进行加密,再将置乱后的隐秘信息分成N份,然后将隐秘信息随机嵌入到图像的小波分解系数中,...