摘要
影像匹配是数字摄影测量和计算机视觉领域的关键问题。本文主要研究基于Delaunay三角网约束下的稳健影像匹配方法。首先利用Delaunay三角网对随机初始匹配点进行组织,构建分布均匀、结构稳定的局部连接关系;其次利用线段描述子和空间角度顺序建立了局部辐射和几何约束模型,并将粗差剔除问题转换为分析Delaunay三角网和对应匹配图的相似性问题;然后利用对应三角形局部约束实现匹配扩展;最后在分层策略和交叉验证策略下实现稳健影像匹配。利用3组数据集进行大量的匹配试验,结果表明本文的匹配算法即使在高外点率下依然能够实现稳健粗差剔除,得到高精度的影像匹配结果。
Image matching is an important issue in the fields of photogrammetry and computer vision.This study exploits the usage of Delaunay triangulation for reliable image matching.First,randomly located initial matches are organized by using Delaunay triangulation,and neighboring connection relationships are established evenly and stably.Second,local photometric and geometric constraints are constructed based on the line descriptor and spatial angular order,which converts the problem of removing outliers to that of analyzing the similarity of the Delaunay triangulation and its corresponding graph.Third,a match expansion operation is implemented based on the local geometric constraint deduced from two corresponding triangles.Finally,a reliable image matching method is proposed with the assistant of the hierarchical elimination and cross-checking strategies.The proposed algorithm is verified by using three datasets,and the results demonstrate that even with high outlier ratios the proposed method can reliably remove false matches and provide match results with high precision.
作者
姜三
江万寿
JIANG San;JIANG Wanshou(School of Computer Science, China University of Geosciences, Wuhan 430074, China;State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China;Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430072, China)
出处
《测绘学报》
EI
CSCD
北大核心
2020年第3期322-333,共12页
Acta Geodaetica et Cartographica Sinica
基金
国家自然科学基金(U1711266)~~
