返回
A WTLS-Based Method for Remote Sensing Imagery Registration
DOI:10.1109/TGRS.2014.2318705.png)
摘要
En 中文
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.
Keyword:
Adaptive weight scheme
image registration
unequal accuracy
weighted total least squares (WTLS)
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
8.6
论文数:
2.2W
被引数:
10.7W
机构
引用论文
Immunohistochemical Detection of Retroviral—P15E—Related Material in Carcinomas of the Head and Neck
RANDOM SAMPLE CONSENSUS - A PARADIGM FOR MODEL-FITTING WITH APPLICATIONS TO IMAGE-ANALYSIS AND AUTOMATED CARTOGRAPHY随机样本共识-模型拟合的范例,可应用于图像分析和自动制图

