摘要
针对影像密集匹配得到的分块DSM数据,本文提出了一种顾及重叠区地形变化的DSM镶嵌线智能提取算法。该方法利用DSM数据重叠区的高程偏差构建重叠区域的差值影像和差分影像,将经过去噪、拉伸和反向计算的差值影像和差分影像做融合处理。针对融合数据采用基于最小生成树的最优路径搜索方法,提取最优镶嵌线。试验结果表明,使用本算法提取的镶嵌线能有效避开高程差异大的凸出地物,保证地物的完整性,能够解决DSM数据镶嵌过程中镶嵌线的自动选择问题。该方法有效减少了传统镶嵌方法带来的误差,可靠性和稳定性较高。
For the digital surface model data obtained by image dense matching,an intelligent seamline extraction algorithm considering the topographic changes in the overlapping area is proposed.This method uses the elevation deviation of the DSM data overlapping area to construct the difference images.It is fusion processing between difference images and the difference images after denoising,stretching and reverse calculation.For the fusion data,the optimal path search method based on the minimum spanning tree is used to extract the optimal seamline.The experimental results show that our seamline extracted can avoid the protruding ground objects effectively with large elevation differences and ensure the integrity of the ground objects.This method can solve the problem of automatic seamline selection in the process of mosaicking DSM data.The method effectively reduces the errors brought by the traditional mosaic method,and has high reliability and stability.
作者
高亚萍
王艳
刘春菊
王琪
吴霞仙
GAO Yaping;WANG Yan;LIU Chunju;WANG Qi;WU Xiaxian(Zhejiang Academy of Surveying and Mapping,Hangzhou 310023,China)
出处
《测绘通报》
CSCD
北大核心
2023年第3期22-26,共5页
Bulletin of Surveying and Mapping
基金
浙江省测绘科学技术研究院院长科研基金(DFP2021C0503)。
关键词
数字地表模型
镶嵌线智能提取
地形变化
最小生成树
路径搜索
digital surface model
intelligent seamline extraction
topographic changes
minimum spanning tree
path search
