一种高效的移动IP注册协议

提出了一种安全、高效的具有匿名性的无证书公钥移动IP注册协议.新协议由于在签名过程中只使用了一个标量乘,验证过程中只使用了两个标量乘,并且没有对运算和模拟运算,因此比以前的方案效率更高.通过在新协议中重复使用初始值实现了MN与HA之间的重新同步;通过构造一个不断变化的临时账户TID来替代真实身份,真正实现了用户的匿名性;通过在通信实体的注册消息中附加随机数,抵御了重放攻击.性能分析和数值计算结果证明在提供相同级别安全性的基础上,该协议在注册时延和计算负载方面都优于现有的协议.尤其是本协议的注册延迟时间比WS Yap的减少了41.68 ms,比马华的减少了0.83 ms.     

增强现实中虚拟物体的投影注册算法研究

研究增强现实的关键技术之一的虚拟物体注册技术,使增强现实系统中的增强信息更具有真实感,结合三色基准注册技术,借助三维空间中的坐标系变换和立体投影变换算法,建立增强现实系统中虚拟物体投影注册模型,提出并推导增强现实系统的虚拟物体立体视觉投影注册算法,该算法能够很好地实现已知几何描述的虚拟物体从其自身坐标系到增强现实系统坐标系的转换,并能够生成具有视差的左右眼立体图像,本算法结合视点的三然基准算法完整地实现了用于增强现实的三维注册。     

基于深度学习的医学图像配准研究进展

图像配准是图像引导手术、图像融合、器官图谱生成、肿瘤和骨骼生长监测等临床任务应用的关键技术,也是一个极具挑战性的问题。近年来,深度学习技术对医学图像处理方法的研究产生重要的影响,在医学图像配准领域发展迅速。对使用深度学习技术实现医学图像配准的研究进行综述,首先按照深度学习模型将医学图像配准方法分为3类,包括监督、弱监督和无监督医学图像配准;然后分别介绍国内外研究进展,并总结这些研究方法的优缺点;在此基础上,阐述常用的深度学习配准框架以及评价标准,并总结常用的开源医学影像数据集;最后对深度学习技术在医学配准图像领域中存在的问题进行分析,展望未来发展的方向。     

基于旋转照明光的数字全息相干噪声抑制

提出一种数字全息相干噪声抑制方法。首先在照明光方位角给定的前提下,通过在极向平面内连续旋转照明光,实现在多角度照明条件下记录离轴数字全息图。然后对所获得的全息图分别重构,同时利用倾斜相差补偿算法和数字图像自相关配准方法分别补偿再现像的相位倾斜及横向偏移。最后将重构像进行非相干叠加,从而有效抑制再现像的相干噪声。实验结果及相关统计评价数据皆验证了该方法的有效性。     

基于对比度Harris的快速鲁棒图像配准算法

为进一步提高配准算法的鲁棒性、速度及自适应程度,提出了一种基于对比度Harris的快速鲁棒图像配准算法.依据中心像素与其邻域像素灰度值差异计算分块图像对比度,自适应地确定其角点检测的阈值,并通过灰度相似性剔除伪角点;在构建的尺度空间中检测角点,解决了Harris算法需凭经验手动设定阈值,所提取的角点分布不均匀,对尺度敏感且含有伪角点的问题;采用斜率和距离约束剔除粗匹配后的部分误配准点对,再通过随机抽样一致性(random sample consensus, RANSAC)进行精配准.实验结果表明,与4种同类配准算法相比,所提出的配准算法对于JPEG压缩、模糊、视角、光照及尺度变化图像都具有更好的鲁棒性,配准正确率更高,自适应性更强,且配准时间大幅减少.     

A two-tier location management mechanism for IMS

This paper proposed a two-tier location management mechanism(TTLM)by improving the currentregistration mechanism(CR)in IP Multimedia Subsystem(IMS).The TTLM includes the visited networkregistration and the home network registration,in which the visited network registration is responsible forre-registration in IMS.When subscriber roams,the location information of home network will be updatedby the visited network based on the change of user equipment(UE)' s IP address.Therefore the TTLMcan reduce the tim...     

基于空间自适应全变分的图像配准

通过引入空间自适应正则化参数,建立了离散的空间自适应全变分配准模型,并结合一阶泰勒展开式给出了有效的不动点求解方法.实验结果表明,由空间自适应全变分配准模型得到的图像的质量比全变分配准模型的更好,迭代时间更短.     

Automated Segmentation and Registration of Dermatological Images

During the last years, there has been a significant increase in the level of interest in image morphology, full-color image processing, image data compression, image recognition and knowledge based analysis systems for medical images. The present paper describes the implementation and tests the efficiency of algorithms dealing with the issues of segmentation and registration of digital images containing skin lesions. Those steps are considered of great importance in computer based characterization systems as they are responsible for the isolation of pathological findings and the matching of sequential images during follow-up studies in medical imaging. This revised version was published online in July 2006 with corrections to the Cover Date.     

Image registration with iterated local search

This contribution is devoted to the application of iterated local search to image registration, a very complex, real-world problem in the field of image processing. To do so, we first re-define this parameter estimation problem as a combinatorial optimization problem, then analyze the use of image-specific information to guide the search in the form of an heuristic function, and finally propose its solution by iterated local search. Our algorithm is tested by comparing its performance to that of two different baseline algorithms: iterative closest point, a well-known, image registration technique, a hybrid algorithm including the latter technique within a simulated annealing approach, a multi-start local search procedure, that allows us to check the influence of the search scheme considered in the problem solving, and a real coded genetic algorithm. Four different problem instances are tackled in the experimental study, resulting from two images and two transformations applied on them. Three parameter settings are analyzed in our approach in order to check three heuristic information scenarios where the heuristic is not used at all, is partially used or almost completely guides the search process, as well as two different number of iterations in the algorithms outer-inner loops. This work was partially supported by the Spanish Ministerio de Ciencia y Tecnología under project TIC2003-00877 (including FEDER fundings) and under Network HEUR TIC2002-10866-E.     

R型聚类分析在遥感信息和地球物理信息复合处理中的应用

本文通过计算机图像处理技术将新泰地区遥感信息和地球物理信息进行复合处理，复合处理的方式为ＫＬ变换，在ＫＬ变换各变量及分量的分析过程中，采用了Ｒ型聚类分析法，最后对处理的结果作了评价，为矿化带的寻找及成矿地质背景分析提供了线索