卫星多源信息贝叶斯融合方法研究

卫星在研制设计过程中存在大量不确定性因素,对卫星的可靠性及性能造成直接影响.如何实现复杂卫星系统的不确定性建模是目前亟需解决的问题,而多源分布信息融合是不确定性建模的关键.此外,在实际系统中,由于时间、成本的约束很难直接获得系统的分布信息.针对在系统信息缺失情况下如何实现卫星系统的多源信息融合问题,提出多层系统结构模块...     

合成孔径雷达图像解译技术探讨

首先对合成孔径雷达图像解译的研究背景及发展历程作了简单介绍，然后分别从斑点噪声抑制、边缘检测、区域分割、目标检测与识别等方面进行了分类探讨。指出新的解译技术应综合利用新特征、新信息和新的研究理论，开展多信息合作与融合机制的研究以及人工智能的应用。     

基于高可信体系安全锁协议算法研究

介绍了一个应用于多级数据库的安全两阶段锁协议算法。该算法通过将锁表分为多个密级，当锁冲突时高密级事务部分回滚的方式来避免在多级安全数据库中实施两阶段锁协议时的隐通道问题，同时为了应用于高可信体系，算法通过将事务管理器从可信模块中分离出来的方法来实现高可信体系中可信模块最小化的要求。本文给出了该协议的具体算法和实现结构，最后对协议的安全性和可串性作了分析。     

金属图像的自适应分割方法研究

针对金相图中分割问题,在分析对比传统的全局阈值分割方法的基础上,提出了一种自适应阈值分割方法。将原图像划分为若干子块,对每个子块利用最佳阈值的方法进行分割。实验表明,提出的方法简便易行,具有较好的鲁棒性和适应性;在完整、有效分割图像的同时,能够保留原始图像中的大量细节信息,对复杂背景图像的分割处理效果满意。本文研究为今后金相分析提供了可靠的依据。     

装备科研项目后评价指标体系及模型

为客观、科学地进行装备科研项目后评价提供理论分析和实践依据,在分析装备科研项目后评价特点的基础上,建立了装备科研项目后评价指标体系,确定了指标的权重,并采用多层次模糊综合评价法建立了装备科研项目后评价模型.(上接第713页)     

一个面向数据密集型网格的通信模型

在由多计算机集群构成的数据密集型网格环境下,为了解决通信峰值阶段的通 信冲突问题,提出了一个多级分组通信模型MGCM(Multi-level Grouping Communica tion Model)).给出了由多机群组成的数据密集型网格数据节点DGDN(Data-intensive Grid Data Node)和完全图通信等形式化定义.利用主动队列、被动队列机制,研究了单个机群内的分组通信算法GCA(Grouping Communication Algorithm)以及双机群内的计算机之间的完全图通信问题GCAD(Grouping Communication Algorithm in Double computer clusters). 基于网络距离机制、GCA和GCAD,设计了DGDN上的多级分组通信模型.理论分析和实践表明 ,该模型有效地解决了数据密集型网格环境下通信峰值所造成的并行计算效率低下的问题. 该模型适合于基于网格的数据密集型并行计算.      

Object-based representations of spatial images

Object based representations of image data enable new content-related functionalities while facilitating management of large image databases. Developing such representations for multi-date and multi-spectral images is one of the objectives of the second phase of the Alexandria Digital Library (ADL) project at UCSB. Image segmentation and image registration are two of the main issues that are to be addressed in creating localized image representations. We present in this paper some of the recent and current work by the ADL's image processing group on robust image segmentation, registration, and the use of image texture for content representation. Built upon these technologies are techniques for managing large repositories of data. A texture thesaurus assists in creating a semantic classification of image regions. An object-based representation is proposed to facilitate data storage, retrieval, analysis, and navigation.     

Similarities in Object and Event Segmentation: A Geometric Approach to Event Path Segmentation

Abstract

Events, like objects, can be decomposed into parts. Path, the spatiotemporal trajectory of an object during an event, is the most commonly labeled event feature across the world's languages, provides important social information, and is increasingly central to theories of general event segmentation. However, little is understood about how adults visually segment paths. We apply theories developed for object segmentation to help understand path segmentation. Overall subjects segmented equivalent object shapes and event paths in similar ways following patterns predicted by Singh and Hoffman's (2001) Singh, M. and Hoffman, D. D. 2001. “Parts-based representations of visual shape and implications for visual cognition.”. In From fragments to objects—Segmentation and grouping in vision Edited by: Shipley, T. F. and Kellman, P. J. 401–459. New York, NY: Elsevier Science..  [Google Scholar] geometric analysis of object parts. There were two notable differences between object and event segmentation: (1) event parsing occurred at points of negative curvature minima and positive curvature maxima as opposed to simply negative curvature minima; and (2) event parsing was more frequent and variable than object parsing. Implications of these results for event perception and categorization are discussed.     

Automatic extraction of lineaments based on wavelet edge detection and aided tracking by hillshade

Lineaments refer to the linear or curvilinear textures on remote sensing image, whose general spatial distribution characteristics are often the response of deep geological sturcture at the surface. Firstly, we use wavelet modulus maximum transformation to detect the edges with 4 scales on Landsat – 8 OLI B5 image and analyze their multi-scale characteristics. As the result, it is determined that the optimal scale of edge detection is 4, and the outline that consist of the edge pixels is roughly corresponding to the geological structure of mine area. Thus the incomplete lineaments have been extracted by using the 2D otsu algorithm. Secondly, the hillshade map generated based on DEM is processed to generate binarized linear shadow. Finally, the linear shadow is superimposed on the lineaments preliminarily extracted to obtain the optimized lineaments. Experiment results show that, based on the method, there are some deformation and displacement between the lineaments extracted and the actual geological structure, and it fail to effectively extract Qilinchang Fault, but lineaments are in good correspondence with Kuangshanchang Fault, Dongtou Fault and Niulan River Fault, which are basically in accord with the geological structure framework of the mine area.     

基于Gibbs-Markov随机场与连通聚类的SAR图像恢复

在传统的马尔可夫随机场(MRF)的图像建模方法基础上利用合成孔径雷达(SAR)图像的固有特性对Gibbs-MRF模型进行改进复原SAR图像,并进一步提出用数字形态学中连通性理论进行图像分割。在SAR图像像素空间的邻域内,估计最大后验概率(MAP)时引用Gamma分布代替传统的瑞利分布恢复数据,同时利用像素强度值相关性的连通模型将目标较好地提取出来。充分利用了SAR图像的数字形态信息和像素强度之间的相关性,得到了更好的分割效果。仿真实验说明本文方法是有效的。