结合均值调整整数变换的迭代自适应可逆图像水印算法

现有的均值调整整数变换可逆水印算法的阈值需人工选择,位置图生成策略不完备可能导致压缩后位置图数据过大,对嵌入矢量强制划分可能导致容量足够却无法嵌入。针对以上问题,提出一种结合均值调整整数变换的迭代自适应可逆图像水印算法。首先,根据负载数据大小以及整数矢量对峰值信噪比(PSNR)的影响,采用迭代自适应算法选择调整平移量以达到水印嵌入容量和嵌入载体视觉质量的平衡;然后,结合邻近像素值相近原则给出了完备位置图生成策略以提高位置图压缩性能;最后,采用分层有序嵌入策略将负载数据依次嵌入到最低、次低和第3低有效位以避免容量足够却无法嵌入的情况。实验结果表明,与传统均值调整整数变换可逆水印算法相比,所提算法无需预先设定阈值,但依然能保持大的嵌入容量,嵌入水印后掩体视觉质量更优,位置图生成策略性能优于传统均值调整整数变换可逆水印算法生成策略且压缩后的位置图数据更小,从而间接提高了嵌入容量,在实验样例上相对于比较算法,PSNR平均提高14.4%。     

利用像素置换的自适应可逆信息隐藏

目的 像素置换作为一种可逆信息隐藏方式具有良好的抗灰度直方图隐写分析能力,但嵌入容量偏小一直是其缺陷。针对这一问题,提出了一种基于像素置换的自适应可逆信息隐藏算法。方法 首先,与传统2×2像素块结构相比构造了尺寸更小的像素对结构,使得载体图像可以被更稠密地分割,为嵌入容量的提升提供了基数条件。其次,提出适用于该新像素结构的可嵌像素对（EPP）筛选条件,避免嵌入过程引起图像质量大幅下降。之后,根据EPP的灰度趋势差异对其进行自适应预编码,提高Huffman编码压缩比,进一步提升算法嵌入容量。最终,通过像素置换嵌入信息。结果 与2×2像素块结构的非自适应图像隐写算法相比,在同样保证灰度直方图稳定性的情况下该算法的PSNR提高了32%左右,嵌入容量提高了95%以上。其中自适应性对嵌入容量提升的贡献极大。结论 本文算法同时具有抗灰度直方图隐写分析能力与高嵌入容量性的可逆信息隐藏。算法构造了更高效的可嵌单位,并且针对不同载体图像的特点对其可嵌区域进行差异化编码。实验结果表明,本文算法在具有更好的不可见性的同时,嵌入容量得到大幅提升。     

Efficient FPGA implementation and verification of difference expansion based reversible watermarking with improved time and resource utilization

This paper presents Xilinx System Generator (XSG) model design for realization of reversible watermarking algorithm using Difference Expansion (DE) approach in System-On-Chip (SoC) Field Programmable Gate Array (FPGA) environment. The reversible watermarking is verified by taking a (4 × 4) sized test image and is applicable for larger sizes of cover images. The outcomes of the result demonstrate that the proposed structural design allows combining MATLAB-Simulink and XSG during graphical user interface for image processing applications. The superiority of the algorithm is justified by using comparative analysis with some well-known methods in both software and hardware environments. The method provides effectively higher PSNR at higher embedding capacity. It is also found that the method requires less time and hardware resources with throughput of 13.516 Mb/s at operational frequency of 80 MHz for real time implementation using FPGA.     

An adaptive HVS based video watermarking scheme for multiple watermarks using BAM neural networks and fuzzy inference system

An efficient reversible adaptive video watermarking scheme for multiple watermarks based on Bi-directional Associative Memory (BAM) Neural Networks and Fuzzy Inference System namely, Multi-BAM-FUZ scheme is proposed in this paper. The main goal of this paper is to design a robust video watermarking system which facilitates secure video transmission over a communication channel by maintaining a trade-off among imperceptibility, robustness and watermark capacity or payload. The BAM neural network supports creation of weight matrix (formed out of multiple images) and this matrix is embedded into the DWT uncorrelated mid frequency coefficients of all the components (Y, Cb, Cr) of every frames of the video with varying embedding strength ‘α’. This adaptive embedding strength is generated using the Fuzzy Inference System which takes HVS characteristics such as luminance, texture and edge of each frame as an input in the DWT transform. The simulations performed on various test videos demonstrate that the proposed Multi-BAM-FUZ not only outperforms other existing methods with respect to various video degradation processes, but also maintains a satisfactory image quality, robustness and payload. It is noted that, the implementation of the novel adaptive process enhances the visual quality of about 60.97 dB in terms of PSNR and 0.9998 in terms of SSIM, robustness of about nearly 1.0000 and 0.9999 in terms of Normalized Cross Correlation (NCC) value and Bit Correction Rate (BCR) respectively against various attacks. Moreover, the proposed scheme facilitates high level of payload without affecting the imperceptibility and robustness level.     

基于LASSO的可逆图像水印算法

对于采用差值扩展-直方图平移的可逆水印算法,提高预测的准确度有利于减小预测误差,从而在同等嵌入失真时获得更大的嵌入容量。为了进一步提高图像像素预测的准确度,构造了一种基于LASSO （Least Absolute Shrinkage And Selection Operator）的局部预测算法。具体而言,根据图像存在边缘、纹理方向的特点,将图像像素预测问题表征为基于LASSO的优化问题;然后通过优化求解得到预测系数,进而得到预测误差;随后利用预测误差,结合差值扩展-直方图平移嵌入技术设计可逆图像水印算法。实验仿真结果表明,与当前预测性能较好的、基于最小二乘局部预测的可逆图像水印算法相比,所提算法在嵌入相同的数据时拥有更高的峰值信噪比（PSNR）。     

图像插值空间大容量可逆数字水印算法

可逆数字水印技术在遥感、医学、军事等众多领域有着广泛应用,而现有大数可逆水印算法需要依赖于附加信息,严重影响了嵌入容量,为此提出一种无附加信息的大容量可逆水印算法。首先设计了一种类似双线性插值原理的图像放大方法,并利用该方法将载体图像放大为原来的4倍,放大图中有1/4的插值点保留了原始图像信息,其余插值点均可嵌入水印。为了在插值的同时同步嵌入水印,先利用随机函数选取水印嵌入位置,再由嵌入水印信息决定理论插值的最终取值,实现水印嵌入,保证了水印的均匀分布,而且最大限度地降低了嵌入水印对插值的影响,同时还提高了算法效率和水印安全性。与经典插值算法相比,生成的含水印图像质量较好,且对任何载体图像嵌入率均能达到0.75 bpp,大量实验也表明,算法隐蔽性好、安全性高、嵌入率高、实用性强。     

Adjustable prediction-based reversible data hiding

Reversible data hiding has received considerable interest recently in the field of information hiding. However, most of difference expansion (DE-based) schemes suffer from the problem that image cannot be restored into its original one free from location map. Reversible data hiding scheme with location map cannot effectively raise hiding capacity; in addition, it also incurs the computational cost during embedding and extracting. This study presents a reversible data hiding scheme that is free of location map and thus the computational cost, associated with embedding and extracting, is lower than that of most DE-based schemes. Furthermore, our scheme solves the problem of the low embedding rate of Tseng and Hsieh?s scheme because our scheme takes advantage of the bulk of relatively high small prediction-errors to raise embedding capacity. Experimental results demonstrate that the proposed scheme achieves the larger payload and the better image quality than some existing schemes by an adjustable control factor. The performance of the proposed scheme is more stable for the different images.     

SVM based robust watermarking for enhanced medical image security

Medical images are more typical than any other ordinary images, since it stores patient’s information for diagnosis purpose. Such images need more security and confidentiality as total diagnosis depends on it. In telemedicine applications, transmission of medical image via open channel, demands strong security and copyright protection. In our proposed robust watermarking model, a double layer security is introduced to ensure the robustness of embedded data. The embedded data is scrambled using a unique key and then a transform domain based hybrid watermarking technique is used to embed the scrambled data into the transform coefficients of the host image. The data embedding in medical images involves more attention, so that the diagnosis part must not be affected by any modification. Therefore, Support Vector Machine (SVM) is used as a classifier, which classify a medical image into two regions i.e. Non Region of Interest (NROI) and Region of Interest (ROI) to embed watermark data into the NROI part of the medical image, using the proposed embedding algorithm. The objective of the proposed model is to avoid any quality degradation to the medical image. The simulation is performed to measure the Peak Signal to Noise Ratio (PSNR) for imperceptibility and Structural Similarity Index (SSIM) to test the robustness. The experimented result shows, robustness and imperceptibility with SSIM of more than 0.50 and PSNR of more than 35 dB for proposed watermarking model.

     

Region based interpolation error expansion algorithm for reversible image watermarking

In this paper, we propose a new reversible image watermarking method based on interpolation-error expansion called region based interpolation error expansion (RBIEE). We improved Thodi's prediction error expansion (PEE) technique by using a novel interpolation algorithm which exploits interpixel correlation better. Furthermore, interpolation error histogram is divided into two regions. The parameters of each region are determined separately and iteratively to reach a given embedding capacity more precisely. However, adaptive embedding strategy is utilized to get better capacity-distortion performance. Advantage of the proposed method over the other state-of-the-art methods in terms of capacity and visual quality is demonstrated experimentally.     

Weighted matrix based reversible watermarking scheme using color image

High capacity, secure, reversible watermarking scheme using a color image for image authentication and tampered detection is still an important area of research. In this investigation, we have proposed a weighted matrix based reversible watermarking scheme using the color image which provides image authentication and tampered detection. Here, we decomposed the original image into R, G, B color components and partitioned into (3 × 3) pixel blocks then we performed the sum of entry-wise-multiplication operations using a modified weighted matrix to embed the watermark. The watermark embedding locations are stored within an index file to enhance security, increase data hiding capacity, gain good visual quality, achieve reversibility and confirm authenticity. The proposed watermarking scheme not only perform authentication and tampered detection but also improved both data embedding capacity up to 8.00 (bpp) as well as increase visual quality measured by PSNR, 50.03 (dB). Finally, the scheme is compared with other existing state-of-the-art methods and gives a reasonably better performance in terms of visual quality and hiding capacity. Our scheme has been evaluated through various steganographic analysis and observed that the scheme is secure and robust against various attacks.     

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。     

An adjustable-purpose image watermarking technique by particle swarm optimization

Imperceptibility, security, capacity, and robustness are among many aspects of image watermarking design. An ideal watermarking system should embed a large amount of information perfectly securely, but with no visible degradation to the host image. Many researchers have geared efforts towards developing specific techniques for variant applications. In this paper, we propose an adjustable-purpose, reversible and fragile watermarking scheme for image watermarking by particle swarm optimization (PSO). In general, given any host image and watermark, our scheme can provide an optimal watermarking solution. First, the content of a host image is analyzed to extract significant regions of interest (ROIs) automatically. The remaining regions of non-interest (RONIs) are collated for embedding watermarks by different amounts of bits determined by PSO to achieve optimal watermarking. The parameters can be adjusted relying upon user’s watermarking purposes. Experimental results show that the proposed technique has accomplished higher capacity and higher PSNR (peak signal-to-noise ratio) watermarking.     

图像分区选择的像素值排序可逆数据隐藏

目的 基于像素值排序（PVO）的数据隐藏算法因其高保真的优越性受到广泛重视,并不断得到改进。本文提出一种图像分区选择思想,以进一步充分利用图像的嵌入空间,改善PVO算法的嵌入性能,提高载秘图像的信噪比。方法 原始PVO算法通常采用预测差值“1”进行数据隐藏,对平滑像素组有较好的利用率和隐蔽性,而对毛躁像素组隐秘性能明显下降,算法性能与图像像素分布情况密切相关。本文在PVO算法基础上提出图像分区选择的思想,首先,将原始图像分为若干区域,然后按移位率从小到大的顺序依次选择图像区域;其次,在每个区域中选择合适的嵌入预测误差;最后,按顺序在被选区域利用该区域的最优嵌入差值完成信息嵌入。结果 假设将图像划分为8×8个区域,对本文算法与原始PVO算法进行比较,当嵌入量为1×10⁴ bit时,Elaine图像的移位率由81.59%降为74.40%,载秘图像的峰值信噪比（PSNR）值由55.388 2提高为56.996 9,提高了1.608 7,采用其他图像并就不同嵌入量进行实验,各图像PSNR值均表现出不同程度的提高。其次,将图像分别划分为2×2、4×4、8×8、16×16个分区,当嵌入量为1×10⁴ bit时,Lena图像PSNR由原始PVO的59.204 6逐渐增加至60.846 9,其他图像在不同嵌入量时PSNR均随着分区数的增加而有不同程度的提高。结论 本文提出的基于图像分区选择的改进PVO算法,可根据像素分布情况增加对嵌入空间的利用,在相同嵌入量情况下,改进后的算法能够获得更高的PSNR值;在一定分区数量条件范围内,分区数量与图像PSNR值表现出正相关性,随着分区数量的增加,图像PSNR值随之增加;本文方法在一定程度上改善了嵌入容量,弥补了因分区数量增加带来的辅助信息增加的问题。     

基于分块DCT变换和Arnold置乱的自适应图像水印算法

提出了一种基于分块DCT变换和Arnold置乱变换的自适应图像水印算法,该算法在水印嵌入过程中充分考虑了人类视觉系统(HVS)的特点,在不同的DCT块中嵌入不同的水印能量,从而使算法具有自适应能力。实验结果表明：该算法对于常见的图像处理具有较强的鲁棒性,特别是具有十分有效的抗击剪切的能力。     

Adaptive reversible watermarking with improved embedding capacity

Embedding capacity is one of the most important issues of the reversible watermarking. However, the theoretical maximum embedding capacity of most reversible watermarking algorithms is only 1.0 bits per pixel (bpp). To achieve a higher capacity, we have to modify the least significant bit (LSB) multiple times which definitely lowers the quality of the embedded image. To this end, this paper proposes a novel reversible watermarking algorithm by employing histogram shifting and adaptive embedding. Specifically, the amount of the embedded watermark is adaptively determined in terms of the context of each pixel. For pixels with small prediction error, we modify the second, third and even the fourth LSBs as well to embed more than one watermark bit. Consequently, the proposed method achieves the embedding capacity larger than 1.0 bpp in single-pass embedding as well as bringing relatively low embedding distortion. The superiority of the proposed method is experimental verified by comparing with other existing schemes.     

Adaptive DE-based reversible steganographic technique using bilinear interpolation and simplified location map

In this paper, an adaptive DE-based reversible steganographic scheme with bilinear interpolation and simplified location map is proposed. In traditional reversible difference expansion (DE) scheme, it suffers from two problems: the embeddable location is considered insufficient and the embedding payload control capability in single layer embedding is weak. For the first problem, the kernel of bilinear interpolation is applied to effectively improve the number of the embeddable location while the quality of the stego-image can be maintained at a good level. In addition, the proposed simplified location map is used for the existing adaptive embedding rule to improve the second problem where the secret data can be adaptively embedded and also the load of additional information can be reduced. The experimental results revealed that the proposed scheme presented better visual quality of the stego-image and carried larger embedding payload than some other revised DE schemes, such as Alattar??s and Lee??s schemes.     

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.     

使用四叉树分割进行自适应空域隐写

目的 针对自适应隐写术可有效避免对载体敏感区大量修改的关键问题,为间接提高安全性和增大隐写容量,在四叉树分割和自适应像素对匹配（APPM）的基础上提出一种自适应空域隐写术。方法 首先该方法以图像块的纹理复杂度作为一致性测度并且设置图像块大小为判别准则进行图像分割,根据四叉树分割结果中面积较小的图像块属于复杂区域,较大的属于平滑区域,按照图像块面积大小将图像分成由高复杂、中复杂、低复杂三大区域构成。其次嵌密方式采用APPM,根据密信容量和载体图像选择进制数B。最后,为了保证安全性和提高容量,优先选择高复杂区嵌入不低于B进制的密信,在中复杂区进行B进制的密信嵌入,在低复杂区选择不高于B进制的密信嵌入。结果 为了验证提出的方法,选8幅经典图作为实验,在嵌入率1.92 bit/pixel的情况下,与已有PVD系列算法和DE算法相比具有更高的PSNR值,PSNR值高达48 dB。此外与APPM算法比较,在嵌入率2.5 bit/pixel情况下,该算法的平均KL距离相比传统APPM算法减小了25.37%,平均一阶Markov安全指标值相比传统APPM算法减小了12.11%,对应的平均PSNR值相比传统APPM算法提高0.43%,在嵌入率1.5 bit/pixel情况下,该算法的平均KL距离相比传统APPM算法减小了37.84%,平均一阶Markov安全指标值相比传统APPM算法减小了26.61%,对应的平均PSNR值相比传统APPM算法提高1.56%。此外,从RSP图库中随机选1 000幅图作为数据集,在嵌入率0.5,0.6,0.7,0.8,0.9和1.0 bit/pixel条件下,结合SPAM特征和SVM分类器的最小平均错误率均高于LSB系列经典算法和APPM算法。结论 1）考虑了人类视觉系统对图像不同区域的敏感性不同,通过对图像进行四叉树分割预处理,优先选择非敏感区进行隐写,保证了一定的安全性要求,低嵌入率下抗SPAM检测和统计不可见性方面比较有优势。2）在四叉树分割中,对于隐写前后图像的四叉树分割结果不同的异常情况,采用一种图像块纹理复杂度调整方案,保证了密信正确完整提取。3）利用了APPM算法的大容量特性,可以隐写嵌入率大于1 bit/pixel的密信,比较适用于大容量的密信隐写,而且可以嵌入任意进制的密信,最大程度地减少嵌入失真,此外,进行了四叉树分割预处理,在安全性方面优于传统APPM算法。     

High-capacity reversible data hiding using quotient multi pixel value differencing scheme in encrypted images by fuzzy based encryption

The Reversible data hiding (RDH) approach can retrieve the original image from the marked image without any distortion. RDH in encrypted images is an approach that hides extra information into the ciphertext using a skill of recovering the actual data losslessly. To guarantee reversibility for addressing the information redundancy drawback, the cover image pixels are copied into two images. This paper presents a high capacity RDH scheme in encrypted images using fuzzy-based encryption. Initially, the texture classification is processed by a convolutional neural network (CNN) to classify the dense and transparent region. It automatically identifies the significant features without any individual supervision. Then, the plain text encryption is activated by the fuzzy group teaching with infinite elliptic curve (FGTIE) method. To overcome the demerit of FCM, the GTA is hybrid with FCM approach and the encryption is processed by the IE method. Next, a new embedding approach is used to enhance the embedding capacity, namely quotient multi-pixel value differencing (QMPVD). In order to obtain the higher PSNR and payload, the multi-pixel differencing is hybrid with the quotient value differencing. Finally, the original data is extracted and recovered with good quality and high capacity. The performances are evaluated using several performance metrics such as PSNR, SSIM, BER, MSE, embedding capacity/payload, sensitivity, specificity, tampering ratio, correlation coefficient, number of pixel change rate and unified average changing intensity. The performance of PSNR and capacity is compared with existing approaches named Encrypted image-based RDH with Paillier cryptosystem (EIRDH-PC), EIRDH with Redundancy Transfer (EIRDH-RT) and EIRDH with pixel value ordering (EIRDH-PVO). The performance is calculated for three groups of images such as the brain, lungs and abdomen. The implementation results show that the introduced model attained better performance compared to existing approaches in terms of PSNR and capacity. Besides, the proposed approach achieved the merits of no pixel expansion, lossless and alternative order recovery.

     

Adaptive color image watermarking by the use of quaternion image moments

The first adaptive moment-based color image watermarking is presented in this work. The proposed method exploits rotation invariance, high reconstruction capability and computation accuracy of the quaternion radial moments’ (QRMs), subject to the tradeoff between robustness and imperceptibility. The current system manages to multi-embed binary logos to color images applying QRMs as information carriers. A novel adaptive system adjusts the watermark’s embedding strength (online) by taking into account image’s morphology, with respect to robustness and imperceptibility. The method manages to experimentally justify and further eliminate the attack-free phenomenon that state-of-the-art methods suffer. The simulation results justified that the proposed framework manages to highly secure its carrying information under common signal processing and geometric attacking conditions. Furthermore, the adoption of the novel adaptive process enhances the robustness and imperceptibility requirements by reducing the Bit Error Rate even by 49% and producing even 5db higher PSNR values, respectively.