A WTLS-Based Method for Remote Sensing Imagery Registration
A WTLS-Based Method for Remote Sensing Imagery Registration
复制标题
DOI：
10.1109/tgrs.2014.2318705
复制
发表时间：
2015
影响因子：
8.2
通讯作者：
Tianjun Wu;Y. Ge;Jianghao Wang;A. Stein;Yongze Song;Yunyan Du;Jianghong Ma
中科院分区：
文献类型：
--
作者：
Tianjun Wu;Y. Ge;Jianghao Wang;A. Stein;Yongze Song;Yunyan Du;Jianghong Ma
针对图像配准中控制点坐标精度不等的问题，提出了一种基于加权总体最小二乘（WTLS）的图像配准方法。通过仿真实验，使用不同的坐标误差的估计器的性能进行了研究。普通最小二乘（LS），总LS（TLS），缩放TLS，加权LS估计的比较。一种新的自适应权重确定方案被应用于遥感图像的实验。通过从不同空间分辨率的多幅参考图像中采集具有不同误差大小的CP，验证了该配准方法的实用性和有效性。本文的结论是，基于WTLS的迭代重加权TLS方法实现了更强大的估计模型参数和更高的配准精度，如果异方差误差发生在参考CP和目标CP的坐标。
This paper introduces a weighted total least squares (WTLS)-based estimator into image registration to deal with the coordinates of control points (CPs) that are of unequal accuracy. The performance of the estimator is investigated by means of simulation experiments using different coordinate errors. Comparisons with ordinary least squares (LS), total LS (TLS), scaled TLS, and weighted LS estimators are made. A novel adaptive weight determination scheme is applied to experiments with remotely sensed images. These illustrate the practicability and effectiveness of the proposed registration method by collecting CPs with different-sized errors from multiple reference images with different spatial resolutions. This paper concludes that the WTLS-based iteratively reweighted TLS method achieves a more robust estimation of model parameters and higher registration accuracy if heteroscedastic errors occur in both the coordinates of reference CPs and target CPs.