基于边缘检测和四点插值细分的SAR图像去噪

针对SAR图像相干斑滤波中存在的降低相干斑与有效保持细节信息这一矛盾,提出了一种基于四点插值细分的SAR图像去噪的新算法,将四点插值细分规则运用到图像去噪中,并与边缘检测相结合。先用canny算子提取图像边缘,进而通过四点插值细分方法分别对边缘图像和原始图像进行去噪,然后再对边缘信息进行边缘信息的重构,得到新的去噪图像。并通过等效视数、边缘保持指数等评价指标对去噪结果进行了评价。实验结果表明,与其他去噪方法相比,该算法在有效地去噪的同时,可有效地保留图像的边缘信息,具有较好的去噪结果。     

基于小波变换的多阈值图像去噪改进方法

图像去噪就是在保留图像边缘及其他特征的基础上去除噪声,小波变换域的阈值去噪方法是图像去噪众多方法中最有效的方法之一,本文对多阈值图像去噪方法进行了改进,得到一种新的图像多阈值图像去噪方法,实验证明该方法可以有效地提高图像去噪效果。     

改进的曲率滤波强噪声图像去噪方法

目的 医学影像获取和视频监控过程中会出现一些恶劣环境,导致图像有许多强噪声斑点,质量较差。在处理强噪声图像时,传统的基于变分模型的算法,因需要计算高阶偏微分方程,计算复杂且收敛较慢;而隐式使用图像曲率信息的曲率滤波模型,在处理强噪声图像时,又存在去噪不完全的缺陷。为了克服这些缺陷,在保持图像边缘和细节特征的同时去除图像的强噪声,实现快速去噪,提出了一种改进的曲率滤波算法。方法 本文算法在隐式计算曲率时,通过半窗三角切平面和最小三角切平面的组合,用投影算子代替传统曲率滤波的最小三角切平面投影算子,并根据强噪声图像存在强噪声斑点的特征,修正正则能量函数,增添局部方差的正则能量,使得正则项的约束更加合理,提高了算法的去噪性能,从而达到增强去噪能力和保护图像边缘与细节的目的。结果 针对多种不同强度的混合噪声图像对本文算法性能进行测试,并与传统的基于变分法的去噪算法（ROF）和曲率滤波去噪等算法进行去噪效果对比,同时使用峰值信噪比（PSNR）和结构相似性（SSIM）作为滤波算法性能的客观评价指标。本文算法在对强噪声图像去噪处理时,能够有效地保持图像的边缘和细节特征,具备较好的PSNR和SSIM,在PSNR上比ROF模型和曲率滤波算法分别平均提高1.67 dB和2.93 dB,SSIM分别平均提高0.29和0.26。由于采用了隐式计算图像曲率,算法的处理速度与曲率滤波算法相近。结论 根据强噪声图像噪声特征对曲率滤波算法进行优化,改进投影算子和能量函数正则项,使得曲率滤波算法能够更好地适用于强噪声图像,实验结果表明,该方法与传统的变分法相比,对强噪声图像去噪效果显著。     

非线性扩散图像去噪中的耦合自适应保真项研究

讨论了一种基于非线性扩散方程的图像去噪方法.在讨论了图像去噪的3个基本要求的基础上,总结了平均曲率运动去噪模型和总变差去噪模型中利用保真项的不足.将利用图像的局部信息构造的自适应保真项引入到方向扩散去噪模型中,克服了原有方法在耦合保真项上的不足,使新的非线性扩散去噪模型能够在有效地去除噪声的同时很好地保持目标尖角、边缘等重要的几何结构.实验结果表明,耦合自适应保真项的扩散方程能够很好地保持图像中目标的几何结构,同时具有良好的去噪能力.     

基于二维经验模态和均值滤波的图像去噪方法

提出了一种新的图像去噪方法。此方法通过二维经验模态（BEMD）将噪声图像分解为一系列不同频带的子图像。对低频近似图像保持不变,对高频细节图像采用不同的模板进行均值滤波,最后将低频近似图像和均值滤波后的图像合成为去噪后的图像。实验结果表明该方法在滤除图像噪声的同时,又能较好地保留图像的边缘细节,其滤波效果优于单一的BEMD图像去噪和均值滤波图像去噪以及小波变换和均值滤波图像去噪方法。     

一种边缘保持的医学图像去噪方法

医学图像去噪在图像处理中占有重要地位,对获取的医学图像进行去噪是进一步分析和计算的基础.将一维经验模式分解方法扩展到二维,提出了基于二维经验模式分解的医学图像边缘保持去噪方法.该方法先将图像进行经验模式分解,得到内蕴模式分量IMF和剩余分量,图像的噪声及边缘信息主要集中在IMF中;然后再将IMF进行经验模式分解,得到IMF的高频分量和剩余分量;最后将两次分解的剩余分量叠加,得到边缘保持的去噪图像.实验结果表明,处理后的图像较传统的医学图像去噪方法有明显的改善,在有效去噪的同时增强了边缘保护的能力.     

小波阈值图像去噪研究与应用

目前,对于图像去噪的理论和应用都已基本完善,但是对于保留图像边缘的图像去噪的研究仍然有很多学者专家在研究。小波域阈值图像去噪是能够保留图像边缘及其他特征的去噪方法之一。本文系统地研究了最常用的几种小波阈值去噪方法及阈值函数,然后在MATLAB环境下对几种小波阈值方法进行了试验,最后对各种阈值去噪方法的去噪效果进行了比较。     

基于分数阶Riemann-Liouville积分的图像去噪

为了在获得更好去噪性能的同时更多地保留图像纹理信息,介绍了分数阶Riemann-Liouville(R-L)积分算子在信号滤波中的作用,将分数阶R-L积分理论引入到数字图像去噪中,并利用阶梯逼近方法来实现数值计算。模型通过设定微小的积分阶次来构建相应的图像去噪掩模,由此实现噪声图像的局部微调,并利用迭代的思想来控制模型的去噪强度,从而获得较好的图像去噪效果。实验结果表明,基于分数阶R-L积分的图像去噪算法较传统的去噪方法不仅可以提高图像的信噪比(SNR),所提出的算法去噪后图像的信噪比为18.3497dB,较传统去噪方法最低也提升了大约4%,而且可以更好地保留图像的弱边缘和纹理等细节信息。     

改进的二阶总广义变分图像去噪算法

为了有效地去除含噪图像中的噪声,克服总变分（TV）去噪易于导致阶梯效应的缺陷,提出了一种改进的二阶总广义变分（TGV）的图像去噪方法。介绍了二阶TGV的理论基础,在二阶TGV中引入了各向异性扩散张量,利用张量函数引导扩散,获得了新的去噪模型,最后提出了一种扩展了的原始-对偶算法对新模型进行数值求解。新模型充分结合了二阶TGV作为正则项自动平衡了一阶和二阶导数项,以及张量函数的各向异性扩散,有效突出边缘结构的特性。实验结果表明,该方法在有效地去除含噪图像中噪声的同时,避免了阶梯效应,增强了对原始图像中边缘结构的保持。     

一种混合曲率流图像除噪方法

基于几何曲线(曲面)演化的图像除噪和恢复是图像处理领域中的一个研究热点.本文利用几何和非线性扩散理论分析最大最小曲率流曲线演化方程,提出结合边缘信息的开关函数控制曲线(曲面)演化的混合曲率流图像除噪模型.实验证明,与其它除噪模型比较,该模型能更好解决曲线演化模型在对图像除噪时边缘保护和噪声去除的问题,提高曲线演化模型的图像除噪能力,并改善图像的可视性.     

A low complexity real-time Internet traffic flows neuro-fuzzy classifier

Traffic flow classification to identify applications and activity of users is widely studied both to understand privacy threats and to support network functions such as usage policies and QoS. For those needs, real time classification is required and classifier’s complexity is as important as accuracy, especially given the increasing link speeds also in the access section of the network. We propose the application of a highly efficient classification system, specifically Min–Max neuro-fuzzy networks trained by PARC algorithm, and compare it with popular classification systems, by considering traffic data sets collected in different epochs and places. We show that Min–Max networks achieve high accuracy, in line with the best performing algorithms on Weka (SVM, Random Tree, Random Forest). The required classification model complexity is much lower with Min–Max networks with respect to the other models, enabling the implementation of effective classification algorithms in real time on inexpensive platforms.     

数据流管理系统中Max、Min聚集算子的示例概要算法

Max和Min是数据流管理系统中重要聚集算子。应用基于滑动窗口下的示例概要法在实时数据流场景下计算Max和Min。在本方法中不需要保存所有落入滑动窗口中数据元组,这意味着可以极大地减小存储空间。由于存储元组的减少,系统的处理时间也显著地减少。实验结果表明基于滑动窗口的示例概要法显著降低了时间和空间的开销。     

Two new fast heuristics for mapping parallel applications on cloud computing

In this paper two new heuristics, named Min–min-C and Max–min-C, are proposed able to provide near-optimal solutions to the mapping of parallel applications, modeled as Task Interaction Graphs, on computational clouds. The aim of these heuristics is to determine mapping solutions which allow exploiting at best the available cloud resources to execute such applications concurrently with the other cloud services.Differently from their originating Min–min and Max–min models, the two introduced heuristics take also communications into account. Their effectiveness is assessed on a set of artificial mapping problems differing in applications and in node working conditions. The analysis, carried out also by means of statistical tests, reveals the robustness of the two algorithms proposed in coping with the mapping of small- and medium-sized high performance computing applications on non-dedicated cloud nodes.     

An upper （lower） bound for Max （Min） CSP

The random constraint satisfaction problem(CSP)instances generated by Model RB have been widely used in the field of CSP and have some nice features.In this paper,we consider two optimization versions of CSP,i.e.,the maximum constraint satisfaction problem(Max-CSP)and the minimum satisfaction problem(Min-CSP)of Model RB.The problem of the Max-CSP is how to find an assignment to all the variables such that the maximum number of constraints are satisfied and the problem of Min-CSP is how to find an assignment to all the variables such that the minimum number of constraints are satisfied.We use the first moment method to prove that when r2α(1/p-1)(or p2α/(2α+r)),an upper bound of Max-CSP can be derived.Similarly,we can prove that when r2α(1/p-1)(or p2α/(2α+r)),a lower bound of Min-CSP can be derived.     

传感器网络中基于域的聚集算法

聚集运算是传感器网络查询处理中最重要的一个运算。提出了一种基于域聚簇的网内聚集算法PIA。在PIA中,首先结合传感器网络的节点特性和位置信息,提出了一种基于域的分布式数据汇聚模型,把传感器网络按域划分来构建连通核,查询只需在连通核中寻径,因而能明显降低寻径时间复杂度并且具有更好的分布性。在PIA中,核心节点把当前路径中的Max和Min值传送到节点上,如果节点的值不符合要求就放弃本次传送,因而能够明显减少数据的传送次数,从而达到节省能量的目的。理论分析和实验表明该算法较传统算法在节省能量上有较好的表现。     

Distributed and resilient localization algorithm for Swarm Robotic Systems

Many applications of Swarm Robotic Systems (SRSs) require each robot to be able to discover its own position. To provide such capability, some localization methods have been proposed, in which the positions of the robots are estimated based on a set of reference nodes in the swarm. In this paper, a distributed and resilient localization algorithm is proposed based on the BSA–MMA algorithm, which uses the Backtracking Search Algorithm (BSA) and the Min–Max Area (MMA) confidence factor. It is designed in a novel four-stage approach, where a new method, called Multi-hop Collaborative Min–Max Localization (MCMM), is included to improve the resilience in case of failures during the recognition of the reference nodes. The results, obtained with real Kilobot robots, show 28–36% of performance improvement obtained by the MCMM. Also, it is shown that the final result of the localization process is better when the MCMM is executed than if it is not executed. The experiments outcomes demonstrate that the novel four-stage approach and the use of the MCMM algorithm represents a progress in the design of distributed localization algorithms for SRS, especially with regard to its resilience.     

Comparing language operations

A procedure for comparing language operations is formulated and used to study some general algebraic properties of such operations as well as the interrelationships of some specific well known operations. The comparison scheme is used to partition the family of all language operations into a collection of equivalence classes that forms an upper semilattice, When full semi-AFL operations are used as a basis of comparison, the Min and Max operations are shown to be in the same class as relative complementation and reside above the class containing Kleene closure. This gives the result that any complementation closed full semi-AFL is a full AFL closed under Min and Max.This paper was supported in part by the National Science Foundation under grant GJ-803 and in part by the U.S. Army Research Office.     

Probability logic and optimization SAT: The PSAT and CPA models

Both probabilistic satisfiability (PSAT) and the check of coherence of probability assessment (CPA) can be considered as probabilistic counterparts of the classical propositional satisfiability problem (SAT). Actually, CPA turns out to be a particular case of PSAT; in this paper, we compare the computational complexity of these two problems for some classes of instances. First, we point out the relations between these probabilistic problems and two well known optimization counterparts of SAT, namely Max SAT and Min SAT. We then prove that Max SAT with unrestricted weights is NP-hard for the class of graph formulas, where Min SAT can be solved in polynomial time. In light of the aforementioned relations, we conclude that PSAT is NP-complete for ideal formulas, where CPA can be solved in linear time.     

Calculation of internal viscous flows in axisymmetric ducts at moderate to high reynolds numbers

A formal procedure is presented for parabolizing the Navier-Stokes equations for two dimensional internal flows in artitrary ducts with streamline curvature and streamline divergence. This procedure consists of constructing an orthogonal coordinate system from the potential flow solution and parabolizing the corresponding Navier-Stokes equations using the thin channel approximation. Theoretical arguments based on the fundamental existence theorem and numerical examples are used to demonstrate the validity of this procedure. A new method using conformal mapping based on the Schwartz-Christoffel transformation is presented which obtains the solution of the inverse potential flow problem in a direct manner. A numerical solution algorithm based on the two point box scheme is presented for solving the viscous flow equations. This method is shown to be accurate and stable for flows at moderate to high Reynolds numbers over a wide range of conditions.     

基于上下文词语同现向量的词语相似度计算

词语的语义相似度是词语间语义相似紧密的一种数量化表示。提出一种词语的语义相似度计算方法 ,利用上下文词语同现向量来描述词语的语义知识 ,在此基础上 ,使用 min/ max的方法计算词语之间的语义相似度。实验结果表明 ,该方法能够比较准确地反映词语之间的语义关系 ,为词语间的语义关系提供一种有效度量。