顾及空间邻接关系的无人机影像匹配并行算法

doi:10.3969/j.issn.0255-8297.2017.06.011

应用科学学报 ›› 2017, Vol. 35 ›› Issue (6): 775-785.doi: 10.3969/j.issn.0255-8297.2017.06.011

顾及空间邻接关系的无人机影像匹配并行算法

张春森¹, 仇振国¹, 郭丙轩², 肖雄武², 朱师欢¹

1. 西安科技大学测绘科学与技术学院, 西安 710054;
2. 武汉大学测绘遥感信息工程国家重点实验室, 武汉 430079

收稿日期:2016-11-27 修回日期:2016-12-30 出版日期:2017-11-30 发布日期:2017-11-30
作者简介:张春森,教授,研究方向:数字摄影测量与遥感应用,E-mail:zhchunsen@aliyun.com
基金资助:
国家重点研发计划基金（No.2016YFB0502200）；国家自然科学基金（No.41127901）资助

Parallel Algorithm of UAV Image Match Considering Spatial Contiguity

ZHANG Chun-sen¹, QIU Zhen-guo¹, GUO Bing-xuan², XIAO Xiong-wu², ZHU Shi-huan¹

1. College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China;
2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Received:2016-11-27 Revised:2016-12-30 Online:2017-11-30 Published:2017-11-30

摘要/Abstract

摘要：

为解决无人机（unmaned aerial vehicle，UAV）影像匹配并行算法的负载均衡和特征数据传输问题，提出一种顾及空间邻接关系的影像匹配并行算法，旨在不降低原有匹配精度的前提下，最大限度地提高影像匹配效率.在特征提取阶段，根据影像空间邻接关系完成各对应节点的初始任务划分，随后进行稍细粒度的二次划分，以确定最终的特征提取任务.在任务调度时，根据计算节点的状态优先分配对应节点的任务.对应节点的任务全部分配完毕再分配其他节点对应的任务.在匹配阶段，首先根据特征提取任务划分匹配任务，然后根据特征提取任务的节点编号划定对应于每一节点的匹配任务单元，使用相同的任务调度方法完成整个测区的影像匹配.对一套有1 463幅UAV影像的典型数据进行实验，结果表明该算法不但能实现并行系统的负载平衡，还能减小特征数据的传输量，从而显著提高影像匹配效率.

关键词: 特征数据传输量, 空间邻接关系, 无人机影像匹配, 影像匹配效率, 负载平衡

Abstract:

To deal with the problem of load balancing and feature data transmission in parallel algorithms of unmaned aerial vehicle (UAV) image match, aparallel algorithm for image match considering spatial contiguity is proposed. In the feature extraction phase, initial task partition is carried out according to spatial contiguity between images. The final feature extraction task is determined by performing a fine-grain second partition based on the initial partition. In task scheduling, corresponding tasks are assigned according to the computational node state, after which other tasks are assigned. In the image matching phase, matching tasks are assigned first according to the feature extraction tasks. Matching task unit of each node is confirmed by the node number of the feature extraction task. The same method is applied to image match in the whole measured area. Experiments on a typical data set including 1 463 UAV images show that the algorithm can realize load balancing of the parallel system and reduce the amount of feature data transmission,thus significantly improving efficiency of image match.

Key words: spatial contiguity relations, amount of feature data transmission, UAV image match, image match efficiency, load balancing

中图分类号:

TP311.5

张春森, 仇振国, 郭丙轩, 肖雄武, 朱师欢. 顾及空间邻接关系的无人机影像匹配并行算法[J]. 应用科学学报, 2017, 35(6): 775-785.

ZHANG Chun-sen, QIU Zhen-guo, GUO Bing-xuan, XIAO Xiong-wu, ZHU Shi-huan. Parallel Algorithm of UAV Image Match Considering Spatial Contiguity[J]. Journal of Applied Sciences, 2017, 35(6): 775-785.

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顾及空间邻接关系的无人机影像匹配并行算法

Parallel Algorithm of UAV Image Match Considering Spatial Contiguity

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