Digital Government: Very Large Scale Multidimensional Data Management and Retrieval for USGS and NIMA Imagery

EIA-9983430Zhang，爱东纽约州立大学水牛数字政府：USGS和NIMA图像的超大规模多维数据管理和检索该项目将进行研究，以管理和检索由合作伙伴政府机构(美国地质调查局(USGS)和国家成像和测绘局(NIMA))持有的多维数据。在这类应用中，分布在偏远地点的地理图像数据库必须在其他地点可用，以便进行数据检索。随着基于内容的图像数据检索的到来，传统的数据库设计和查询检索方法将不再适用于开发分布式图像检索系统，本研究的目的是探索新的方法来支持在Internet上高效地访问集成的地理图像数据库。这些方法将为分布式地理图像检索系统的设计奠定基础。与设计这种综合有关的技术挑战是在图像数据库的基础上建立元级系统。具体的研究目标是：(1)识别地理图像的多尺度表示(多维)方法；(2)研究能够检测任意形状的多维图像数据聚类的新方法；(3)构建元数据模型，描述集成系统向相关数据库进行可视化查询所需的元数据；(4)发展基于元数据的数据库选择方法的理论基础；(5)设计新的视觉查询处理方法，融合从视觉数据内容中提取的异质特征。在项目期间，USGS和NIMA将提供所有必要的图像数据集及其类别。在项目期结束时，将在USGS和NIMA两个地点传播一个系统。通过上述研究活动，将为设计分布在互联网上的分布式多维数据提供基本的认识和新的技术支持，并将作为其他政府机构(如NASA)开发分布式图像数据库系统的模板得到广泛应用。实验结果可用于建立有效的基准来评估分布式图像数据检索系统的性能。

EIA-9983430Zhang, AidongSUNY BuffaloDigital Government: Very Large Scale Multidimensional Data Management and Retrieval for USGS and NIMA ImageryThis project will conduct research on managing and retrieving multidimensional data held by partner government agencies (the United States Geological Survey (USGS) and the National Imaging and Mapping Agency (NIMA)). In such applications, geographic image databases distributed at remote locations must be made available at other locations for purpose of data retrieval. With the advent of content-based retrieval of image data, traditional methods for database design and query search will not be suitable in developing distributed image retrieval systems.The objective of the proposed research is to investigate novel approaches to supporting effective and efficient access to the integrated geographic image databases over the Internet. These approaches will establish a foundation for the design of distributed geographic image retrieval systems. The technical challenge relating to the design of such integration is the creation of meta-level system on top of the image databases. The specific research goals are : (1) identify multi-scale representation (multidimensional) methods for geographic images, (2) investigate novel clustering approaches that can detect clusters of arbitrary shape of multidimensional image data, (3) construct a metadata model that formulates the metadata that are needed for the integrated system to direct a visual query to relevant databases, (4) develop the theoretical foundation of database selection approaches based on the metadata, and (5) design novel visual query processing approaches that integrate heterogeneous features extracted from the content of visual data.During the project period, USGS and NIMA will provide all necessary imagery data sets and their categories. A system will be disseminated at both USGS and NIMA sites at the end of the project period. Through the above research activities, the fundamental understanding and novel techniques will be provided to support the design of distributed volume of multidimensional data distributed over the Internet and will find broad applications as a template for the development of distributed image database system in other government agencies, such as NASA. The experimental results to be generated can be used to establish effective benchmarks for assessing the performance of distributed image data retrieval systems.