面向高层地物的异源高分遥感影像配准方法  

Registration method for multi-source high resolution remote sensing image based on high-rise objects

作　　者：王非凡 徐炜 陈晓辉[2,3] 王帅[4] 王驿飞 王超[2,3,4] Wang Feifan;Xu Wei;Chen Xiaohui;Wang Shuai;Wang Yifei;Wang Chao(Changwang School of Honors,Nanjing University of Information Science&Technology,Nanjing 210044,China;Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering,China Three Gorges University,Yichang 443002,China;China Yichang Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering,China Three Gorges University,Yichang 443002,China;School of Electronic&Information Engineering,Nanjing University of Information Science&Technology,Nanjing 210044,China)

机构地区：[1]南京信息工程大学长望学院,南京210044 [2]三峡大学湖北省水电工程智能视觉监测重点实验室,宜昌443002 [3]三峡大学水电工程智能视觉监测宜昌市重点实验室,宜昌443002 [4]南京信息工程大学电子与信息工程学院,南京210044

出　　处：《电子测量技术》2021年第16期156-167,共12页Electronic Measurement Technology

基　　金：三峡大学湖北省水电工程智能视觉监测重点实验室开放基金(2020SDSJ05);水电工程智能视觉监测湖北省重点实验室建设中央引导地方科技发展专项(2019ZYYD007)项目资助。

摘　　要：由于传感器成像通常存在较大差异,异源高分辨率遥感影像配准面临着更加突出的局部变形问题。特别是城市中高层地物的相对视差偏移更加显著,从而在空间变换中产生严重的非线性误差。为此,提出了一种面向高层地物的异源高分遥感影像配准方法。首先,通过开展阴影检测并结合影像分割,实现对高层地物的筛选。在此基础之上,提出了一种基于相位一致性的阈值自适应特征点提取策略,以提升高层地物中特征点数量与特征点整体分布均匀性。其次,通过引入阴影面积加权特征向量距离,以排除阴影对同名点对匹配干扰。最后,针对同名点对设计了一种变换误差自适应惩罚因子,以降低高层地物上空间变化差异对映射方程的影响权重。通过对多组异源高分遥感影像的配准实验表明,所提出方法的总体配准精度和均方根误差分别可达88.9%和1.481。Because of the great difference of sensor imaging,the registration of high-resolution remote sensing image is faced with more prominent local deformation problem.In particular,the relative parallax offset of high-rise objects in the city is more significant,which leads to serious nonlinear error in spatial transformation.Therefore,proposes a registration method for multi-source high resolution remote-sensing image based on high-rise objects.Firstly,through shadow detection and image segmentation,the high-rise objects are screened.On this basis,a threshold adaptive feature point extraction strategy based on phase consistency is proposed,in order to improve the number of feature points in high-rise objects and their overall distribution uniformity.Secondly,the distance of feature vector weighted by shadow area is introduced to eliminate the interference of shadow on feature point matching.Finally,an adaptive penalty factor of transformation error is designed to reduce the influence of high-rise objects’spatial variation on affine equation.Through the registration experiments on groups of multi-source high resolution remote sensing images,it is found that the registration accuracy and root mean square error of the proposed method can reach 88.9%and 1.481 respectively.

关 键 词：图像配准 异源遥感影像 阴影检测 高层地物筛选 加权特征向量距离 自适应惩罚因子 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]