Modelling for registration of remotely sensed imagery when reference control points contain error

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	Modelling for registration of remotely sensed imagery when reference control points contain error
	Ge Yong
	2006
关键词	Image processing Least squares approximations Mathematical models Measurement errors Regression analysis
英文摘要	Reference control points (RCPs) used in establishing the regression model in the registration or geometric correction of remote sensing images are generally assumed to be "perfect". That is, the RCPs, as explanatory variables in the regression equation, are accurate and the coordinates of their locations have no errors. Thus ordinary least squares (OLS) estimator has been applied extensively to the registration or geometric correction of remotely sensed data. However, this assumption is often invalid in practice because RCPs always contain errors. Moreover, the errors are actually one of the main sources which lower the accuracy of geometric correction of an uncorrected image. Under this situation, the OLS estimator is biased. It cannot handle explanatory variables with errors and cannot propagate appropriately errors from the RCPs to the corrected image. Therefore, it is essential to develop new feasible methods to overcome such a problem. This paper introduces a consistent adjusted least squares (CALS) estimator and proposes relaxed consistent adjusted least squares (RCALS) estimator, with the latter being more general and flexible, for geometric correction or registration. These estimators have good capability in correcting errors contained in the RCPs, and in propagating appropriately errors of the RCPs to the corrected image with and without prior information. The objective of the CALS and proposed RCALS estimators is to improve the accuracy of measurement value by weakening the measurement errors. The conceptual arguments are substantiated by a real remotely sensed data. Compared to the OLS estimator, the CALS and RCALS estimators give a superior overall performance in estimating the regression coefficients and variance of measurement errors. © Science in China Press 2006.
出处	Science in China, Series D: Earth Sciences
卷	49 期:7 页:739-746
收录类别	EI
语种	英语
内容类型	EI期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/24903]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Ge Yong. Modelling for registration of remotely sensed imagery when reference control points contain error. 2006.