基于预测误差双重编码的大容量密文域可逆信息隐藏算法

针对目前密文域可逆信息隐藏算法嵌入容量较小的问题,提出了基于预测误差双重编码的大容量密文域可逆可分离信息隐藏算法。首先为了预留秘密信息的嵌入空间,图像拥有者利用基于预测误差的哈夫曼编码及扩展游程编码对图像进行预处理,然后加密图像;数据嵌入者在加密后的图像中嵌入秘密信息;接收者根据信息隐藏密钥可以准确无误地提取秘密信息,根据解密密钥可以无损恢复图像,两者无顺序要求。实验结果表明,预测误差双重编码的应用有效地提高了嵌入容量。     

彩色图像的无损数据隐藏

提出一种在彩色图像中新的无损数据隐藏算法。首先对RGB图像直方图调整分别压缩灰度动态范围。然后进行整数YUV变换和Y分量整数小波变换。最后通过算术编码和哈希变换，将待隐藏信息连同压缩灰度动态范围剩余数据，嵌入小波高分辨率子带的中间位平面内，达到小波反变换时防止溢出的目的，实现无损数据隐藏。文中用6个通用的图像隐藏数据为例，嵌入数据容量达到19～73kbits。将该方法用于电子政务中，取得了良好的效果。     

基于JPEG2000的图像联合压缩加密算法

为实现图像的压缩和加密同步,在深入研究MQ算术编码器的基础上,将Lorenz混沌系统生成的随机序列作为流密钥对JPEG2000压缩算法中比特平面编码形成的上下文和判决进行修正,以改变MQ编码时的概率分布来使得输出的码流发生变化,从而实现图像联合压缩加密.阐述了上下文修正和判决修正加密算法的规则.对算法进行仿真,结果表明,相对于原始压缩算法,所提出的算法对图像的压缩效率几乎没有影响,且安全性好、实时性高.     

自适应算术编码及其在图像编码中的应用

文章介绍了自适应算术编码的基本原理和实现方法,提出了一种基于预测编码和自适应算术编码的图像编码的算法,这种方法能根据图像的区域特征自适应地选取相应的编码模式,提高编码效率。仿真结果表明该算法能有效地提高图像无损编码的效率。     

一种基于神经网络模型的遥感图像的快速无损压缩方法

感知器是一种分层的神经网络模型,具有自适应自学习的能力.本文提出一种基于感知器模型的自适应预测的遥感图像无损压缩方法,编码时,先对当前像素进行自适应预测,然后采用快速有效的Rice编码器对误差图像编码.以TM遥感数据为实验对象,实验结果表明,该方法能够有效地去除遥感图像的空间及谱间相关性,压缩效率明显优于基于算术编码的JPEG最优无失真模式;与LOCO-I算法相比,三维预测的平均压缩比和编解码速度也有较大的提高.     

基于提升Directionlet变换的零块嵌入图像编码算法

提出一种新的基于提升Directionlet变换的图像压缩算法, 能有效捕捉图像中的多方向各向异性特征, 并具备格形可分离的滤波和采样结构. 利用四叉树分块寻找局部最优的变换方向, 针对Directionlet变换系数分布构造了块集合分裂嵌入编码, 并通过改进链表排序方式和设计新的上下文算术编码器, 进一步提高压缩性能. 仿真实验结果表明, 与基于原始Directionlet变换的压缩算法和基于小波变换的SPECK, SPIHT, JPEG 2000等经典算法相比, 本文算法在性能参数和视觉效果方面均有较大提高, 且在低比特率下仍能较完整地保留图像中的边缘和细节信息.     

基于全方向预测与误差扩展的可逆数据隐藏

提出一种具有高容量低失真特点的可逆图像数据隐藏算法.通过扩展像素的预测误差值将数据嵌入图像宿主中,可在提取嵌入的数据后准确还原原始图像.与大部分基于预测误差扩展的算法不同的是,提出一种具有全方向上下文的预测器以提高预测精度.提出一种基于差值扩展的嵌入算法将数据嵌入预测误差中,并提出一种仅需少量附加数据的边界表策略以避免像素溢出问题.实验数据表明,提出的全方向预测器能有效提高预测精度,并且结合提出的扩展算法与边界表,其嵌入容量与宿主图像质量较已有的可逆数据隐藏算法都有所提高.     

基于上下文修正的ROI联合压缩加密算法

提出一种基于上下文修正的ROI图像联合压缩加密算法。对零树结构进行改进,引入自适应算术编码器,利用密钥对ROI图像压缩产生的原始上下文进行修正,修正后的上下文与原始判决一起送入自适应算术编码器中实现对ROI图像的联合压缩加密。为了满足不同权限用户的需求,对感兴趣区域按树型结构扫描的方式进行加密,并对该算法进行仿真。结果表明:在相同码率条件下,与原始压缩算法相比,所提出的算法具有基本相当的压缩效率;在压缩率保持不变的情况下,相对于区间分裂的算术编码而言,所提出的算法安全性能更好。     

基于EZW的牙颌模型三维数据压缩

针对牙颌模型深度数据的压缩处理问题,阐述了嵌入零树小波(Embedded Zerotree Wavelet,EZW)编码算法的基本原理和算法实现,讨论了基于感兴趣区域的EZW算法及其实现,并在实验室进行了深度数据和三维重构图像的基于感兴趣区域的EZW编码实验.实验表明,EZW编码既能实现图像的有损压缩也可实现图像的无损压缩,并具有很大的压缩比.     

基于自适应哈夫曼编码的密文可逆信息隐藏算法

随着云存储和隐私保护的发展,密文域可逆信息隐藏作为一种可以在密文中嵌入秘密信息,保证嵌入后的信息可以无错误提取,并能无损恢复原始明文图像的技术,越来越受到人们的关注.本文提出了一种基于自适应哈夫曼编码的密文域可逆信息隐藏算法,对不同的图像采用不同的哈夫曼码字编码腾出空间来嵌入秘密信息.首先利用自然图像相邻像素间的相关性对原始明文图像进行像素值预测,从最高有效位到最低有效位,对原始像素值和预测像素值的相同比特位进行自适应的哈夫曼编码标记.然后,利用流密码对原始明文图像进行加密.最后在腾出的空间,通过位替换来自适应的嵌入秘密信息.由于哈夫曼编码和解码的可逆性,合法接收者可以对原始明文图像和秘密信息实现分离的无损恢复和提取.实验结果表明,与现有的几种方法相比,本文提出的方法具有更好的安全性和更高的嵌入率,在BOSSBase、BOWS-2和UCID三个数据集上的平均嵌入率比MPHC算法分别提高了0.09bpp、0.062 bpp和0.06bpp,在最佳情况下比MPHC算法能分别高出0.958 bpp、0.797 bpp和0.320 bpp,最差情况下的嵌入率比MPHC算法也分别高出了 0.01 bpp、0.039 bpp和0.061 bpp.     

基于混沌系统的图像可逆信息隐藏算法

为了提高图像可逆信息隐藏算法的安全性、透明性、嵌入容量,提出了一种基于混沌系统的图像可逆信息隐藏算法.该隐藏算法通过将载体图像直方图峰值点与其两侧多个连续零值点之间建立关系的方式,实现在载体图像的单个峰值点嵌入多个秘密信息位,以保证较高的透明性和较大的嵌入容量.为了保证嵌入载体图像内的秘密信息的安全性,采用混沌系统对秘...     

基于幅度调制的彩色图像水印

提出了一种基于幅度调制的彩色数字图像水印方案.通过改变蓝色通道的信息,实现了在空域嵌入水印.水印的嵌入位置通过一个密钥控制来实现随机的选取.为了提高鲁棒性,每一位水印被多次嵌入在不相关的多个位置中.同时,在有效水印的前面增加了一个模式序列,形成一个完整的水印序列,这个模式能够在水印提取过程中生成一个自适应的阈值,提高了水印提取的鲁棒性.水印提取不需要原始的宿主图像.试验结果显示该方案具有较强的抵御信号处理和几何攻击的鲁棒性.     

A semi fragile watermarking algorithm based on compressed sensing applied for audio tampering detection and recovery

Research on audio tampering detection and recovery plays an important role in the field of audio integrity, and authenticity certification. Generally, we use technology of fragile/semi fragile watermarking to detect and recover tampered audio. In this study, a new scheme for watermark embedding, tampering detection, and recovery is proposed. In the new scheme, we get the compressed version of original audio signal using compressed sensing technology and apply discrete wavelet transform (DWT) to each audio frame. In process of embedding, a new self-adaptive algorithm is proposed. Watermark is the quantized reference value of original framed audio signal and tampering location data, and is embedded in the region with low energy of high frequency coefficients and high energy of low frequency coefficients respectively after 2-level DWT. In process of detection, we locate tampered areas by comparing the value of generated random number and extracted watermark after XOR operation with the extracted location data. As for speech, we set a threshold to judge whether it is tampered or not. At last, we extract watermark in areas which are not damaged and get the recovered signal after decompression. Experiments and analysis show that signal after embedding has at least 5 dB higher average signal-to-noise ratio than others, and broken frames and groups can be detected exactly. When signal is destroyed by 20%, 98% of the corpus is intelligible after recovery, and even destroyed by 50%, 80% of the corpus recovered is also intelligible. Compared with other recovery algorithms, audio signal recovered by our proposal has a higher signal-to-noise ratio and a better robustness to some signal processing. When tampering rate is 50%, the average detection rate is over 93%, which indicates that our method is workable.

     

Audio watermarking scheme based on embedding strategy in low frequency components with a binary image

With the recent development of information technology and computer network, digital format of data has become more and more popular. However, a major problem faced by digital data providers and owners is protecting data from unauthorized copying and distribution. As a solution to the problem, digital watermark technology is now attracting attention as new method of protection against said unauthorized copying and distribution. The aim of the digital audio watermarking is to take prespecified data that carries certain information and hide it within the audio stream such that it is not audible to the human ear (i.e., transparent) but at the same time renders the file more resistant to removal (i.e., robust). In this paper, we propose a new method for embedding digital watermarks into audio signals in low frequency components, which method mitigates these and other related shortcomings. The proposed method uses the wavelet transform constructed by lifting-based wavelet transform (LBWT) in order to provide a fast implementation between watermark embedding and extraction parts. In the first stage of the proposed method, the original audio host signal is converted to a wavelet domain using LBWT. The signal is thus decomposed into low and high frequency components. Approximation coefficients correspond to low frequency components of the signal. Next, the watermark generated by pseudorandom numbers is embedded into wavelet approximation coefficients of the segmented host audio signal depending on the binary value of the binary image. The reason for embedding the watermark in the low frequency components is that these components' energy is greater than that of high frequency components in such a way that the watermark is inaudible; therefore, it should not alter the audible content and should not be easy to remove. The proposed method uses a binary image to decide whether or not the watermark generated by pseudorandom numbers is embedded in the audio host signal. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including bit error rate (BER) and signal-to-noise ratio (SNR) are conducted. The tests' results show that the proposed method yields a high recovery rate after attacks by commonly used audio data manipulations such as low-pass filtering, requantization, resampling and MP3 compression.     

结合BEMD与Hilbert曲线的重复嵌入图像水印算法

为解决数字图像水印算法中水印图像与宿主图像在嵌入时尺寸匹配上的局限问题,并提高图像水印算法在抗大尺度剪切、高斯噪声和椒盐噪声等攻击的鲁棒性,提出一种结合二维经验模态分解算法(BEMD)与Hilbert曲线的重复嵌入图像水印算法.首先,利用Arnold变换对水印图像进行置乱处理,以增加水印图像的安全性;其次,利用Hilbert曲线将置乱后的二维水印图像进行数据降维,得到一维水印信号.数据降维不仅有效地解决了嵌入时水印图像与宿主图像在尺寸匹配上的局限,同时也进一步置乱了水印图像,加强了水印图像的安全性.对宿主图像进行BEMD分解得到不同尺度下的内蕴模态函数和余量信息,并检测第1个内蕴模态函数对应图像的极值点作为水印嵌入位置.最后,依据人类视觉系统的纹理掩蔽特性,将一维水印信号按照从左至右、自上而下的顺序依次、重复嵌入到第1个内蕴模态函数对应图像的极值点中,并结合剩余内蕴模态函数及余量信息重建得到嵌入水印后的图像.水印图像的提取为该嵌入过程的逆过程.通过对多组图像进行水印嵌入,得到嵌入水印后图像的峰值信噪比均在40 dB以上;对嵌入水印后图像进行高斯噪声、椒盐噪声、大尺度剪切等攻击实验,得到提取水印图像与原始水印图像的归一化相关系数均在0.96以上.实验结果表明,嵌入水印图像具有良好的不可见性,并对高斯噪声、椒盐噪声,特别是对大尺度剪切具有较强的鲁棒性.     

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.     

A novel key-embedded scheme for secure video multicast systems

The secure distribution and maintenance of key information are essential for controlling access to video multicast systems. Unlike the conventional approaches using a dedicated channel independent of the video stream, this paper proposes a novel data embedding scheme, which we refer to as SMDE (statistical modulation data embedding), to support the media-dependent approach that exploits data-dependent channel to transmit and maintain key information. Using embedded data to convey key information is able to achieve added security and reduce bandwidth resource consumption. To this end, we present some new algorithms to embed key messages. By adopting the statistical properties of host video signal, new coding approach for embedded data, and error control algorithm, the proposed SMDE scheme can provide error resilience, transparence for adaptation mechanism, high accuracy of detecting embedded data and real-time processing capability for video applications. These advantages have been demonstrated by the extensive experimental results.     

Perceptual Digital Watermarking for Image Authentication in Electronic Commerce

Digital watermarking has been presented to protect the copyright of electronic multimedia data. The previous proposed watermarking algorithms mostly embed sequences of random numbers or binary images as the watermarks. In this paper, an image accreditation technique by embedding digital gray-level image watermarks in images is proposed. In the proposed method, the host image and the watermark are decomposed into wavelet coefficients. The contextual energies of the host-image wavelet coefficients are computed to select embedding coefficients. The watermark wavelet coefficients are sorted and then embedded in the selected host coefficients. The experiments show that the proposed method provides extra robustness against JPEG-compression, image-processing, and even composite attacks compared to the traditional embedding methods. Moreover, the proposed method has no need of the original image to extract the embedded watermarks. The proposed method facilitates electronic commerce application developers to select adequate digital watermarking techniques for their development systems.     

Data embedding in audio signal using multiple bit marking layers method

One of the biggest challenges in data embedding is that the confidential data need to be in the ‘transparency’ after being embedded into the audio signal. Therefore, embedding methods must reduce the influence of embedded data onto the original audio signal. In this paper, the multiple bit marking layers (MBML) method has been proposed to fulfill this requirement. This method reuses the results from the previous embedding time (layer) as the input data to continue embedding it into audio signals (i.e. the next layer). The quality of the proposed method is evaluated through embedding error (EE), signal-to-noise ratio (SNR), embedded capacity (EC) and contribution error (CE). Experimental results have shown that the proposed method provides better quality of EE, and SNR than any other proposed embedding methods such as: LSB (Least Significant Bit), ELS (Embedding Large Sample.), BM (Bit Marking), and the BM/SW (Sliding Window) method with a single layer.     

一种结合小波域和空域的图像数字水印新算法

提出了一种结合小波域和空域的图像数字水印新算法。依据重要性将原始水印分成两部分,分别嵌入载体图像小波域和空域。并利用混沌系统对水印序列的嵌入位置进行置乱。重要水印嵌入小波域多级分解的低频子图;采用二值量化算法。其余水印嵌入载体空域非LSB的中间比特位;并采用最小化像素改变策略。实验结果证明了该算法在提高水印容量的同时,嵌入水印也具有很好的安全性、隐蔽性和鲁棒性。