基于小波系数相对模糊关系的水印方法

提出一种基于带参数整数小波变换和相对小波系数模糊关系的数字水印算法.应用基于视觉系统小波域量化噪声的视觉权重分析方法,自适应的构造模糊关系矩阵,在水印的提取过程中实现了盲检测.本方法与经典的密码理论以及高级加密算法相结合.应用Rabin方法生成单向Hash函数,信息隐藏算法可以完全公开.水印算法不可感知性好,鲁棒性强,是一种有效的版权保护方法.     

基于遗传算法的多约束网格检查对策问题研究

综合考虑物品数量以及列容量约束,将隐藏成本与检查概率引入支付函数,建立一种新的多约束的网格检查对策模型.根据矩阵对策性质及Hlder不等式,将对策论问题转化为非线性整数规划问题.提出一个基于遗传算法的模型求解方法,将归一化处理得到的变量进行二进制编码,通过数据变换将问题转化为无约束问题,采用轮盘赌选择、多点交叉及单点变异操作求解模型.仿真结果表明了模型及所提算法的有效性.     

求解一般整数规划问题的改进蝙蝠算法

蝙蝠算法是一种新型的智能优化算法,本文针对基本蝙蝠算法易陷入局部最优、过早处于停滞阶段等不足之处,在蝙蝠速度更新公式中引入了惯性权重,并采用权值动态递减的方式变换权重,更好地平衡了算法的全局搜索能力和局部搜索能力.通过求解一系列经典整数规划问题,并与已有算法进行比较,结果表明:改进的蝙蝠算法在一般整数规划问题的求解中具有较高的计算效率和精度,以及较强的全局搜索能力.     

多气源天然气管网运行优化问题的混合整数规划模型及其算法

对于多气源天然气管网运行优化问题,文章首先引入了刻画压缩机开关的0-1整数变量,并对非线性的管道压降方程进行了合理的松弛化处理,建立了更符合实际的非线性混合整数规划模型.其次,基于序列线性化的思想,设计了一种求解该模型的序列混合整数线性化算法.最后,在不同规模的天然气管网系统中进行了多方面的对比实验.实验结果表明,新模型及求解算法能够有效降低成本、减少压缩机能耗,并且所需求解时间大大减少.     

基于小波边缘刻画与LBF水平集变分模型的图像分割

本文研究了基于水平集的图像分割的问题.利用小波变换的方法,构造出图像边缘刻画函数,引入到LBF水平集分割变分模型中,获得了基于小波变换的WLBF模型,同时给出了WLBF模型的数值求解算法.针对不同情景下的典型灰度图像,给出了图像分割实例,推广了LBF模型及算法,实验结果证明WLBF模型及算法对图像分割的有效性.     

基于小波变换和人眼视觉系统特性的图像降噪方法

利用小波变换与人眼视觉系统（human visual system,HVS）的多通道特性相匹配的特点,提出一种基于人类视觉系统的图像降噪方法.该方法在P-M模型中引入小波变换与视觉敏感函数,并且结合视觉敏感函数的带通特性,提出一种新的扩散函数.实验结果表明,该方法得到的图像不论在客观评价（峰值信噪比）方面还是主观测评方面,都能达到较好的效果.     

微粒群算法及其在热轧生产调度中的应用

针对整数规划问题的特点,提出了一种在整数空间中进行进化计算的PSO算法,使微粒群的进化限于整数空间。给出了热轧生产调度问题的最优轧制单元数学规划模型。并将该方法成功应用于最优轧制单元求解。     

整数规划问题的滤子填充函数算法

全局优化是最优化的一个分支,非线性整数规划问题的全局优化在各个方面都有广泛的应用.填充函数是解决全局优化问题的方法之一,它可以帮助目标函数跳出当前的局部极小点找到下一个更好的极小点.滤子方法的引入可以使得目标函数和填充函数共同下降,省却了以往算法要设置两个循环的麻烦,提高了算法的效率.本文提出了一个求解无约束非线性整数规划问题的无参数填充函数,并分析了其性质.同时引进了滤子方法,在此基础上设计了整数规划的无参数滤子填充函数算法.数值实验证明该算法是有效的.     

带最小交易单位的Markowitz模型及算法

在证券交易市场中,交易规则要求购买的股票数量为整数.基于这种情况,将Markowitz模型中资产的投资比例改进为资产的投资数量,构造了一个二次整数规划模型.设计了求解该模型的算法,经过实证分析,算法是有效的.     

基于Hartley变换的三维真振幅偏移算子研究

在实际应用中，以快速Fourier变换为基础的偏移方法，将本来是实数的地震道转化为复数参加运算，导致了计算机内存的增加。本文把只有纯实数运算的Hartley变换引入到基于Fourier变换的偏移算法，再利用三维真振幅偏移单程波方程，结合Fourier变换与Hartley变换的内在关系，经过数学推理，具体导出了裂步Hartley变换真振幅偏移算子。与一般裂步Fourier法相比，裂步Hartley变换真振幅偏移算法既提高了计算效率又对球面扩散问题进行了振幅补偿。     

A blind image watermarking using multiresolution visibility map

A perceptual pyramid watermarking method is proposed. The key idea is to use the contrast sensitivity of the human visual system (HVS) to determine “invisible” regions where watermark energy can be adjusted providing an invisible and robust watermark. These invisibles regions are obtained by computing a “visibility map” at each level of the Gaussian pyramid (GP). The watermark is weighted by the local contrast and a global scaling factor. The embedding process is performed by modifying the values in some levels of the Laplacian Pyramid (LP) using the spread spectrum technique. Afterwards, the watermarked image can be constructed from the levels of the LP. For watermark detection, a blind detection scheme using the threshold-correlation based technique is proposed. Finally, the performances of the watermarking method are evaluated in terms of invisibility and robustness using some quality metrics and different attacks of Stirmark such as Gaussian noise, low-pass filtering, Jpeg compression and cropping. This evaluation is performed for the choice of some parameters of the watermarking system depending on performances such as invisibility and robustness. The design of our watermarking technique can finally be formulated as an optimisation problem where the objective is to guarantee a trade-off between invisibility and robustness.     

多重水印技术的模糊关系与应用

应用带参数整数小波变换,提出了一种多重水印技术。在图像中同时嵌入半透明数字水印和脆弱水印来达到良好的保护效果。通过构造模糊关系矩阵,实现了半透明水印的安全嵌入。引入R ijndae l加密算法,构造出H ash函数,实现了一种具有高敏感性能的脆弱水印。该技术在图像保护领域有广阔的应用前景。     

A novel digital image covert communication scheme based on generalized FCM in DCT domain

A novel covert communication method of digital image is presented, based on generalized fuzzy c-means clustering (GFCM), human visual system (HVS) and discrete cosine transform (DCT). Therefore, the original image blocks are classified into two classes according to specified characteristic parameters. So one block is suited for embedding security information, but the other block is not. Hence the appropriate blocks can be selected in an image to embed the security information by selectively modifying the middle-frequency part of the original image in conjunction with HVS and DCT. Furthermore the maximal information strength is fixed based to the frequency masking. Also to improve performances of the proposed algorithm, the security information is modulated into the chaotic modulation array. The simulation results show that we can remarkably extract the hiding security information and can achieve good robustness with common signal distortion or geometric distortion and the quality of the embedded image is guaranteed.     

Invertible chaotic fragile watermarking for robust image authentication

Fragile watermarking is a popular method for image authentication. In such schemes, a fragile signal that is sensitive to manipulations is embedded in the image, so that it becomes undetectable after any modification of the original work. Most algorithms focus either on the ability to retrieve the original work after watermark detection (invertibility) or on detecting which image parts have been altered (localization). Furthermore, the majority of fragile watermarking schemes suffer from robustness flaws. We propose a new technique that combines localization and invertibility. Moreover, watermark dependency on the original image and the non-linear watermark embedding procedure guarantees that no malicious attacks will manage to create information leaks.     

An efficient fractal image coding algorithm using unified feature and DCT

Fractal image compression is a promising technique to improve the efficiency of image storage and image transmission with high compression ratio, however, the huge time consumption for the fractal image coding is a great obstacle to the practical applications. In order to improve the fractal image coding, efficient fractal image coding algorithms using a special unified feature and a DCT coder are proposed in this paper. Firstly, based on a necessary condition to the best matching search rule during fractal image coding, the fast algorithm using a special unified feature (UFC) is addressed, and it can reduce the search space obviously and exclude most inappropriate matching subblocks before the best matching search. Secondly, on the basis of UFC algorithm, in order to improve the quality of the reconstructed image, a DCT coder is combined to construct a hybrid fractal image algorithm (DUFC). Experimental results show that the proposed algorithms can obtain good quality of the reconstructed images and need much less time than the baseline fractal coding algorithm.     

Gaussian DCT Coefficient Models

It has been known that the distribution of the discrete cosine transform (DCT) coefficients of most natural images follow a Laplace distribution. However, recent work has shown that the Laplace distribution may not be a good fit for certain type of images and that the Gaussian distribution will be a realistic model in such cases. Assuming this alternative model, we derive a comprehensive collection of formulas for the distribution of the actual DCT coefficient. The corresponding estimation procedures are derived by the method of moments and the method of maximum likelihood. Finally, the superior performance of the derived distributions over the Gaussian model is illustrated. It is expected that this work could serve as a useful reference and lead to improved modeling with respect to image analysis and image coding.     

A fractional partial differential equation based multiscale denoising model for texture image

Traditional integer‐order partial differential equation based image denoising approach can easily lead edge and complex texture detail blur, thus its denoising effect for texture image is always not well. To solve the problem, we propose to implement a fractional partial differential equation (FPDE) based denoising model for texture image by applying a novel mathematical method—fractional calculus to image processing from the view of system evolution. Previous studies show that fractional calculus has some unique properties that it can nonlinearly enhance complex texture detail in digital image processing, which is obvious different with integer‐order differential calculus. The goal of the modeling is to overcome the problems of the existed denoising approaches by utilizing the aforementioned properties of fractional differential calculus. Using classic definition and property of fractional differential calculus, we extend integer‐order steepest descent approach to fractional field to implement fractional steepest descent approach. Then, based on the earlier fractional formulas, a FPDE based multiscale denoising model for texture image is proposed and further analyze optimal parameters value for FPDE based denoising model. The experimental results prove that the ability for preserving high‐frequency edge and complex texture information of the proposed fractional denoising model are obviously superior to traditional integral based algorithms, as for texture detail rich images. Copyright © 2013 John Wiley & Sons, Ltd.     

Multiple-watermarking scheme based on improved chaotic maps

In this letter a new watermarking scheme for color image is proposed based on a family of the pair-coupled maps. Pair-coupled maps are employed to improve the security of watermarked image, and to encrypt the embedding position of the host image. Another map is also used to determine the pixel bit of host image for the watermark embedding. The purpose of this algorithm is to improve the shortcoming of watermarking such as small key space and low security. Due to the sensitivity to the initial conditions of the introduced pair-coupled maps, the security of the scheme is greatly improved.     

Digital watermarking scheme for colour remote sensing image based on quaternion wavelet transform and tensor decomposition

Digital watermarking is important for protecting the intellectual property of remote sensing images. Unlike watermarking in ordinary colour images, in colour remote sensing images, watermarking has an important requirement: robustness. In this paper, a robust nonblind watermarking scheme for colour remote sensing images, which considers both frequency and statistical pattern features, is constructed based on the quaternion wavelet transform (QWT) and tensor decomposition. Using the QWT, not only the abundant phase information can be used to preserve detailed host image features to improve the imperceptibility of the watermark, but also the frequency coefficients of the host image can provide a stable position to embed the watermark. To further strengthen the robustness, the global statistical feature structure acquired through the tensor Tucker decomposition is employed to distribute the watermark's energy among different colour bands. Because both the QWT frequency coefficients and the tensor decomposition global statistical feature structure are highly stable against external distortion, their integration yields the proposed scheme, which is robust to many image manipulations. A simulation experiment shows that our method can balance the trade‐off between imperceptibility and robustness and that it is more robust than the traditional QWT and discrete wavelet transform (DWT) methods under many different types of image manipulations.