Mutual information optimization based dynamic log-polar image registration

Log-polar transformation(LPT)is widely used in image registration due to its scale and rotation invariant properties.Through LPT,rotation and scale transformation can be made into translation displacement in log-polar coordinates,and phase correlation technique can be used to get the displacement.In LPT based image registration,constant samples in digitalization processing produce less precise and effective results.Thus,dynamic log-polar transformation(DLPT)is used in this paper.DLPT is a method that generates several sample sets in axes to produce several results and only the effective results are used to get the final results by using statistical approach.Therefore,DLPT can get more precise and effective transformation results than the conventional LPT.Mutual information(MI)is a similarity measure to align two images and has been used in image registration for a long time.An optimal transform for image registration can be obtained by maximizing MI between the two images.Image registration based on MI is robust in noisy,occlusion and illumination changing circumstance.In this paper,we study image registration using MI and DLPT.Experiments with digitalizing images and with real image datasets are performed,and the experimental results show that the combination of MI with DLPT is an effective and precise method for image registration.     

基于点特征和边缘特征的无人机影像配准方法

为解决变形较大的无人机影像配准问题,提出了点特征和边缘特征相结合的配准方法.用尺度不变特征变换(SIFT)算法提取点特征,完成影像的初步配准,并通过多项式函数对影像进行粗校正.在此基础上提取影像的边缘特征信息,根据距离相似性对边缘特征信息进行配准;依据色彩能量差筛选点特征信息配准结果和边缘特征信息配准结果,采用小面元微分校正的方法对变形影像进行校正.实验结果表明:提出的配准方法能够弥补点特征配准方法和边缘特征配准方法的不足,其配准的鲁棒性提高10%左右,可以较好地完成变形较大的无人机影像配准.      

Hierarchical Non-linear Image Registration Integrating Deformable Segmentation

IntroductionSegmentation and registration are two impor-tant problems in the field of medical image analy-sis. Traditionally, solutions have been developedfor each of these two problems in relative isolationfrom the other, but with increasing dependence onthe existence of a solution for the other. For exam-ple, model-based segmentation methods[1,2]need toregister individual data sets to a common frame ofreference, so that statistics about the models canbe gathered to guide the evolution of the…     

Algorithm based on morphological component analysis and scale-invariant feature transform for image registration

In this paper, we proposed a registration method by combining the morphological component analysis (MCA) and scale-invariant feature transform (SIFT) algorithm. This method uses the perception dictionaries, and combines the Basis-Pursuit algorithm and the Total-Variation regularization scheme to extract the cartoon part containing basic geometrical information from the original image, and is stable and unsusceptible to noise interference. Then a smaller number of the distinctive key points will be obtained by using the SIFT algorithm based on the cartoon part of the original image. Matching the key points by the constrained Euclidean distance, we will obtain a more correct and robust matching result. The experimental results show that the geometrical transform parameters inferred by the matched key points based on MCA+SIFT registration method are more exact than the ones based on the direct SIFT algorithm.     

基于贝叶斯决策的航空影像自动配准

为消除像点投影差对航空影像目标监测中影像配准的影响,提出了一种基于贝叶斯决策理论的像点投影差消除方法.该方法通过推导分析像点投影差的分布规律及其对影像配准的影响,设置训练样本区,提取大量特征匹配对,计算得到投影差分布参数,并基于贝叶斯决策理论构建了像点投影差消除准则.为验证其有效性,选用KIT AIS影像数据进行了实验,比较分析了投影差消除前后的配准影像结果.分析结果显示,消除后差分视觉效果得到改善,信息熵减小10%,表明本文方法可有效提高航空影像配准的精度.      

基于互信息快速算法的多模医学图像配准

互信息作为相似性测度在多模医学图像配准领域得到了广泛应用,具有高精度和稳健的特点.但频繁的互信息计算降低了配准效率,同时对两幅图像重叠区域比较敏感.采用归一化互信息为测度,降低互信息计算中灰度级的快速算法,通过多模CT/MRI配准实验证明,可以在确保配准精度的同时缩短时间提高配准效率.     

基于NSCT变换的红外与可见光图像融合方法

针对小波变换不能很好地表达图像边缘信息，NSCT变换对图像细节信息表达缺失的问题，本文提出了一种改进的基于NSCT变换的图像融合方法．首先将经过预处理和配准后的红外图像和可见光图像进行NSCT变换，得到各个源图像的低频和高频系数，然后对分解后的低频系数采用小波变换的融合规则进行融合处理，高频系数则采用基于特征的区域能量的融合规则进行融合处理，最后对融合后的系数进行NSCT反变换得到融合图像．仿真实验表明，采用改进的NSCT融合方法对红外与可见光图像的融合有良好的效果，图像更清晰，信息更全面．     

基于共轭梯度的大尺度医学图像非刚性配准算法

人体胸腹腔中大量非刚性软组织器官由于呼吸、脏器蠕动和体位变动等会产生大尺度非线性形变,粘性流体配准将图像的形变模拟为流体的流动过程而适宜于大的形变.针对粘性流体配准算法应用超松驰迭代求解离散化偏微分方程组耗时量大,且其最优松驰参数难以获得的问题,使用基于不需要预先估计参数的共轭梯度迭代求解形变参数,实现粘性流体配准.该方法所需存储量小,且具有步收敛性、稳定性高的优点,实验证明该方法在不损失配准精度的前提下提高了配准速度.     

Deformable Registration of MR Brains with Best Features

Introduction Deformable registration is very important formedical image analysis and so far various methodshave been proposed in decades[1-4]. HAMMER reg-istration algorithm[5]defines an attribute vector in-cluding intensity, edge type, and geometric mo-ment invariants as a signature of each point, to re-duce ambiguity in correspondence matching duringthe image registration. Another characteristic ofHAMMER is the hierarchical matching mecha-nism, which helps avoid the warping being trapped…     

航空影像的几何校正研究与实现

航空侦察在军事上有着重要的地位,文中研究了航空影像的斜像校正.利用GPS实地采集地面控制点,采用多项式和双线性插值法对机上采集的图像进行了几何校正.校正后的图像可用于图像配准、融合和目标识别.     

基于目的层预约的改进型粒子群电梯群控调度策略

针对单一粒子群算法的派梯策略优化运算过程中容易陷入局部极值点的状况,结合模拟退火理论,提出一种改进型的粒子群电梯群控派梯策略,应用到目的层预约的电梯群控系统中.通过仿真和对比试验可知,基于目的层预约的电梯群控系统能有效地提高服务的各项指标,改进型的粒子群电梯群控调度策略可有效减小乘客候梯时间和电梯启停次数,改善电梯运行性能.     

点云数据配准算法的研究

点云配准是点云数据处理的关键,直接影响最后合成结果和模型精度。目前,点云配准方法普遍存在对配准数据初始位姿要求高的缺点。将点云配准分为两个阶段：第一阶段是基于同名点配准,即粗配准,采用人机交互式,配准过程耗时短,节约时间;第二阶段是精配准,在粗配准后,依据最小二乘原理,用间接平差思想,通过最近点迭代算法对点云数据快速配准,并采用目标点集中、目标点坐标与转入目标点集中的点坐标中误差为指标,评价配准精度。进行粗配准的精配准不仅速度快、耗时短,并且可以避免因局部收敛而带来的局部最小问题。试验表明该方法有效可行。     

Kinect-based automatic spatial registration framework for neurosurgical navigation

As image-guided navigation plays an important the pre-operative images with the intra-operative patient role in neurosurgery, the spatial registration mapping position becomes crucial for a high accurate surgi- cal output. Conventional landmark-based registration requires expensive and time-consuming logistic support. Surface-based registration is a plausible alternative due to its simplicity and efficacy. In this paper, we propose a comprehensive framework for surface-based registration in neurosurgical navigation, where Kinect is used to auto- matically acquire patient＇s facial surface in a real time manner. Coherent point drift （CPD） algorithm is employed to register the facial surface with pre-operative images （e.g., computed tomography （CT） or magnetic resonance imaging （MRI）） using a coarse-to-fine scheme. The spatial registration results of 6 volunteers demonstrate that the proposed framework has potential for clinical use.     

Multi-band Image Registration Method Based on Fourier Transform

This paper presented a registration method based on Fourier transform for multi-band images which is involved in translation and small rotation. Although different band images differ a lot in the intensity and features,they contain certain common information which we can exploit. A model was given that the multi-band images have linear correlations under the least-square sense. It is proved that the coefficients have no effect on the registration progress if two images have linear correlations. Finally, the steps of the registration method were proposed. The experiments show that the model is reasonable and the results are satisfying.     

高职院校图书馆采编工作实践与探索

采编工作是对图书馆资源进行整合与调配的重要基础工作,对图书馆的馆藏质量、馆藏结构起着关键性的作用。针对高职院校图书馆采编工作的现状,就如何优化图书采编工作流程,提高采编工作的质量与效率,提升高职院校图书馆的整体工作水平进行了探索。     

一种基于稀疏表达和光流的目标跟踪方法

提出一种将稀疏表达技术融入到传统光流算法的目标跟踪方法.首先使用FAST和Harris算法在视频序列的每一帧中为光流算法采集运动目标的特征点,之后光流算法基于后向跟踪-形心配准的方法对跟踪目标完成粗略定位.在当前帧的粗略定位处应用仿射变换产生N个候选区域.最后应用稀疏表达技术判断出与原始目标匹配率最高的仿射变换区域做为最终目标跟踪区域.实验结果表明,该算法既能较好地适应目标的外观变化,又具有较强的抗遮挡能力,鲁棒性强.     

随机向量的独立性

给出了随机向量相互独立性和条件独立性的两个结论,将３个随机变量的相互独立性和条件独立性推广到随机向量的相互独立性与条件独立性。指出了如果３个随机向量两两条件独立,由３个随机向量亦一定相互独立;且若３个随机向量的函数两两条件独立,则３个随机向量的函数亦相互独立。     

基于一面两孔特征的点云配准方法

为了提高零件在扫描检测过程中点云与设计模型的配准精度,提出了一种基于一面两孔特征的点云配准方法.该方法粗配准以零件的平面/圆柱孔特征为对象,使设计模型和点云的局部坐标系重合,并通过改进ICP算法求解点云与设计模型最近点的距离最小平方和实现精配准.由于配准区域和最近点的计算方法不同,精配准进一步分为全域和特征域配准两种类型.全域精配准以距点云最近的设计模型三角网格点或投影点为最近点,适合于毛坯件;特征域精配准则通过求解点云在平面/圆柱孔特征上的投影点为最近点,适合于成品件.试验及计算结果表明:全域配准的配准精度随表面离散点距离的减小而提高, 当离散点距离达到1.50 mm时,其配准精度已经达到0.15 mm,基本满足工程应用要求.当配准精度相同时,配准效率较其它方法提高10%~20%.      

基于最佳指数因子的自适应权值图像融合

依据现有的多波段遥感影像的融合方法和多波段图像融合效果的客观评价准则,提出了基于最佳指数因子的自适应权值图像融合算法.最后,结合互联网卫星数据,给出了实验结果.结果表明,该方法为研究人员提供一个较佳的融合后影像.     

基于相似度的图像变形效果的客观度量方法

给出了评价图像变形效果的新方法.首先,计算中间帧之间的相似度,由这些相似度值生成一条曲线;然后,在图像计算机动画领域首次提出图像变形真实感度的概念.它通过计算曲线与坐标轴,曲线插值点处的曲率和其他一些衡量标准得到.试验表明,它是一有效的度量图像变形效果的客观方法.