| 遥感影像并行处理的数据划分及其路径优化算法 |
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| 引用本文： | 方雷,姚申君,包航成,康俊峰,刘婷.遥感影像并行处理的数据划分及其路径优化算法[J].测绘学报,2019,48(5):572-582. |
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| 作者姓名： | 方雷 姚申君 包航成 康俊峰 刘婷 |
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| 作者单位： | 复旦大学环境科学与工程系,上海,200438;华东师范大学地理科学学院,上海,200241;金华市规划与地理信息中心,浙江 金华,321000;江西理工大学建筑与测绘工程学院,江西 赣州,341000;杭州师范大学理学院,浙江 杭州,311121 |
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| 基金项目： | 国家重点研发计划（2016YFC0803105）；国家自然科学基金（41301423） |
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| 摘 要： | 研究了一种基于数据划分的遥感影像并行处理的路径优化算法,用于解决将并行技术应用于海量遥感影像分布式存储和处理领域时其处理模型所具有的多路可达性所引起的路径动态、最优选择问题。在栅格数据可分解性分析及并行模型数据态、元素、相对信息量和映射等8个基本定义和6个性质的基础上,给出并行处理一般数学模型。以该模型为基础获得在一般并行处理情况下,以平均计算代价变量的比值作为控制横向并行与纵向并行选择方式的标志,并进一步给出四叉树索引并行生成、基于四叉树的目标检测并行处理等具体示例。最后,通过试验验证了算法的有效性,分析了算法的特点及影响因素。
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| 关 键 词： | 并行 遥感影像 数据生成 最优路径 地理信息系统 |
| 收稿时间： | 2016-10-20 |
| 修稿时间： | 2018-08-22 |
An algorithm for optimizing routing of remote sensing image parallel processing based on data partitioning |
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| FANG Lei,YAO Shenjun,BAO Hangcheng,KANG Junfeng,LIU Ting.An algorithm for optimizing routing of remote sensing image parallel processing based on data partitioning[J].Acta Geodaetica et Cartographica Sinica,2019,48(5):572-582. |
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| Authors: | FANG Lei YAO Shenjun BAO Hangcheng KANG Junfeng LIU Ting |
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| Institution: | 1. Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China;2. School of Geography, East China Normal University, Shanghai 200241, China;3. Jinhua Planning and Geomatics Center, Jinhua 321000, China;4. School of Architectural and Surveying and Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China;5. College of Science, Hangzhou Normal University, Hangzhou 311121, China |
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| Abstract: | Parallel processing technologies have been widely applied to remote sensing images processing. While previous research has developed many parallel algorithms for processing images, few studies have been focused on synchronous parallel processing for multiple computing tasks when one copy of remote sensing image has many redundant backups under the cloud computing environment. To bridge the research gap, this research proposes a routing optimization algorithm for parallel processing of remote sensing image. Based on data segmentation, the method is developed to solve the dynamic routing optimization problem when applying the parallel technology to remote sensing image distributed storage and processing. Following the introduction of 8 definitions (e.g. model data state, model elements, relative information quantity and matrix mapping) and 6 properties (e.g. directed, transitive, reproductive, multi-dimensional properties), a mathematical model is proposed. Under the framework, the ratio of average computation costs is used as the flag to control horizontal or vertical parallel processing. In addition, typical examples such as quadtree index generation, and quadtree-based target detection are presented for illustrating the application of our model on parallel processing. Finally, through the experiments, we verify the effectiveness of the algorithm, discussing the characteristics and influential factors of the algorithm. |
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| Keywords: | parallel remote sensing image data generation optimal path GIS |
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