共查询到20条相似文献,搜索用时 281 毫秒
1.
基于小波系数块能量分析的自适应数字水印算法 总被引:12,自引:0,他引:12
为增强水印的鲁棒性,提出一种基于小波变换的改进数字水印算法。该算法将宿主三级小波变换后的第三级细节子图分别分割成互不重叠的系数块,进而对各块能量进行统计分析以确定更适于水印嵌入的块,最后结合人类视觉系统的掩蔽特性,在所选块的最大系数上实现水印的自适应嵌入。理论分析与仿真结果表明应用本算法实现的水印具有更好的鲁棒性和不可见性。 相似文献
2.
3.
提出一种小波域基于块能量分析的数字水印算法。该算法将载体图像三级小波分解的第三级细节子图分为互不重叠的系数块,根据人眼对图像的纹理和边缘不敏感的视觉特性,选择能量较大的块系数嵌入有意义水印。实验结果表明:该算法嵌入的数字水印具有很好的隐蔽性,同时对JPEG压缩、叠加噪声、平滑滤波等攻击具有很好的鲁棒性。 相似文献
4.
提出了一种基于小波变换和混沌映射的数字图像置乱加密算法。先对数字图像进行小波分解,再对变换后的小波系数进行混沌置乱,最后对置乱后的系数矩阵进行逆小波变换得到加密图像。实验表明,该算法具有令人满意的安全性和置乱效果。 相似文献
5.
6.
一种带纠错编码的小波域自适应盲水印算法 总被引:1,自引:1,他引:0
文中提出了一种小波域自适应盲水印算法。该算法具有如下特点:(1)以图像局部相关特性为基础,采用块均值量化策略;(2)以人眼视觉掩蔽特性为基础,将小波系数块进行分类,不同类的块选取不同的量化步长,并且水印嵌入过程中块内系数的改变量自适应于系数本身大小;(3)利用纠错编码和混沌置乱对水印信息进行调制,以提高水印的鲁棒性。该算法在检测时不需要原始图像,实现了盲检测。实验结果表明,该方案能很好地抵抗JPEG压缩,叠加噪声,裁剪等攻击,具有良好的鲁棒性和透明性。 相似文献
7.
8.
为了克服常规的数字水印算法在嵌入水印信息时,造成图像一定程度的失真,提出了一种基于分段logistic混沌映射的零水印算法.在不对图像原始数据作任何修改的基础上,利用混沌算法对初始值极其敏感的特性来生成混沌序列,利用混沌序列来确定所选取的图像小波变换第三级细节部分小波系数的位置,提取相应位置上小波系数的特征生成图像的水印.实验结果表明,该算法针对压缩、噪声攻击、剪切攻击等具有较强的鲁棒性. 相似文献
9.
提出了一种基于数字全息和小波系数块能量分析的水印算法。待隐藏的水印图像通过在空域零扩展后再生成其傅里叶全息图,从而消除了再现后孪生像的混叠问题,然后将原宿主图像进行小波分解,把全息图嵌入在分块能量较大的小波系数中。仿真实验证明算法具有较好的透明性和鲁棒性。 相似文献
10.
提出了一种基于混沌映射的改进奇偶量化水印算法。算法首先使用混沌序列对待嵌入水印信号进行混沌调制,再经过散列处理的序列定位嵌入的图像块位置及小波系数坐标,运用奇偶量化法嵌入水印信号。在充分考虑了人类视觉系统掩蔽特性的基础上,根据图像本身性质调节量化步长的大小,从而保证了算法的自适应性。而且,考虑到离散小波变换的特性,嵌入水印的位置仅在图像的中频子带。实验结果证明,算法具有更高的不可见性和鲁棒性,可以抵抗较高的压缩攻击。 相似文献
11.
12.
地图匹配( MM)算法通过粒子滤波( PF)利用室内地图信息来抑制基于惯性传感器的室内定位系统的误差累计。利用区域生长( RG)算法结合当前步长和方向信息在地图上找到合理的落脚范围,并以此来判断粒子的有效性。这种方法能有效改善地图配准算法的实用性和计算复杂度。提出一种改进的零速度( ZV)检测算法能准确提取步伐信息,间接提升了零速度更新( ZUPT)算法和地图配准算法的精度。实验结果表明:该算法的定位误差小于1.0%,定位精度比单纯的航位推算( DR)算法平均提高了5.97%。 相似文献
13.
一、引言计算机仿真接口界面,随着计算机软硬件的不断提高也在快速地变化着。从其发展趋势中我们不难看出这一点:从早期的命令行提示编辑Command Line,到全屏幕菜单编辑(Menu based Editor),再到图形用户界面Graphic User In-terface(GUI),界面在不断追求如何更好地适应用户、与用户更直接地交互。其具体特点包括自然而又丰富的色彩、逼真而又完美的几何造型、柔和而又动听的环境声响、质感而又具有力反馈的实物等。这些人们所需要的真实感,一种技术是难以胜任的,它需要各种软、硬件技术的综合与集成。从目前的趋 相似文献
14.
This research investigates the impact of intellectual capital components on the competitive advantage in the Jordanian telecommunication companies. The empirical findings indicate that the relational capital and the structural capital have positive impact on competitive advantage. Both the relational capital and the structural capital account for 48.4% of the competitive advantage. It is unexpected to find that the human capital does not have a significant direct impact on competitive advantage. However, it is valid to state that the human capital indirectly and significantly influences competitive advantage as it is embedded in the relational capital. The effect of the relational capital on competitive advantage is moderated by gender and age. The effect is strongest among younger men. In the case of the structural capital its effect is moderated by gender only such that the effect is slightly stronger for females rather than males. 相似文献
15.
16.
S. Suja Priyadharsini 《Applied Soft Computing》2012,12(3):1131-1137
Electroencephalography (EEG) is the recording of electrical activity of neurons within the brain and is used for the evaluation of brain disorders. But, EEG signals are contaminated with various artifacts which make interpretation of EEGs clinically difficult. In this research paper, we use a soft-computing technique called ANFIS (Adaptive Neuro-Fuzzy Inference System) for the removal of EOG artifact, combined EOG and EMG artifact. Improvement in the output signal to noise ratio and minimum mean square error are used as the performance measures. The outputs of the proposed technique are compared with the outputs of techniques such as neural network, based on ADALINE (Adaptive Linear Neuron) and adaptive filtering method, which makes use of RLS (Recursive Least Squares) algorithm through wavelet transform (RLS-Wavelet). The obtained results show that the proposed method could significantly detect and suppress the artifacts. 相似文献
17.
The Prize-collecting Steiner Tree Problem (PCSTP) is a well-known problem in graph theory and combinatorial optimization. It has been successfully applied to solve real problems such as fiber-optic and gas distribution networks design. In this work, we concentrate on its application in biology to perform a functional analysis of genes. It is common to analyze large networks in genomics to infer a hidden knowledge. Due to the NP-hard characteristics of the PCSTP, it is computationally costly, if possible, to achieve exact solutions for such huge instances. Therefore, there is a need for fast and efficient matheuristic algorithms to explore and understand the concealed information in huge biological graphs. In this study, we propose a matheuristic method based on clustering algorithm. The main target of the method is to scale up the applicability of the currently available exact methods to large graph instances, without loosing too much on solution quality. The proposed matheuristic method is composed of a preprocessing procedures, a heuristic clustering algorithm and an exact solver for the PCSTP, applied on sub-graphs. We examine the performance of the proposed method on real-world benchmark instances from biology, and compare its results with those of the exact solver alone, without the heuristic clustering. We obtain solutions in shorter execution time and with negligible optimality gaps. This enables analyzing very large biological networks with the currently available exact solvers. 相似文献
18.
心电信号是典型的强噪声下的非平稳微弱信号,减小噪声的干扰对心电信号的分析有着十分重要的意义,因此,有效的滤波方法一直是该领域学者关注的热点问题。本文在基于小波变换心电信号分析研究基础上,针对小波去噪时分解只作用于低频部分,从而忽略了高频区域中一部分有用信号的问题,提出了一种采用改进小波包理论实现心电信号去噪的方法,利用小波包在消除信号噪声方面具有更为精确的局部分析能力的特点,采用了‘db4’小波和"最优基"选择的方法,对心电信号进行消噪。以MIT-BIH心电数据库中心律失常数据仿真实验,得到了较理想的去噪效果。对比该方法与小波滤波去噪,发现基于小波包的心电信号去噪具有更优良的去噪性能。 相似文献
19.
VoIP认证与计费的设计与实现 总被引:1,自引:0,他引:1
基于RADIUS的VoIP认证系统,采用分散受理、集中管理的接入认证管理体系,数据集中存放在认证中心(RADIUS服务器),用户身份认证由PC向网守发起,网守通过RADIUS协议向认证中心的认证服务器发起认证请求。这样,可以保证用户安全地使用网络资源,以确保用户身份的合法性。同时其落地话单经过处理,可进行计费及其它帐务处理。文中论述了RADIUS对VoIP的支持,提出了一个Gatekeeper与RADIUS结合的整体解决方案。 相似文献
20.
Wavelet-based envelope features with automatic EOG artifact removal: Application to single-trial EEG data 总被引:1,自引:0,他引:1
Wei-Yen Hsu Chao-Hung LinHsien-Jen Hsu Po-Hsun ChenI-Ru Chen 《Expert systems with applications》2012,39(3):2743-2749
In this study, we propose an analysis system for single-trial classification of electroencephalogram (EEG) data. Combined with automatic EOG artifact removal and wavelet-based amplitude modulation (AM) features, the support vector machine (SVM) classifier is applied to the classification of left finger lifting and resting. Automatic EOG artifact removal is proposed to eliminate the EOG artifacts automatically by means of independent component analysis (ICA) and correlation coefficient. The features are then extracted from the discrete wavelet transform (DWT) data by the AM method. Finally, the SVM is used for the discriminant of wavelet-based AM features. Compared with EEG data without EOG artifact removal, band power features and LDA classifier, the proposed system achieves promising results in classification accuracy. 相似文献