Abdelsayed S.

Alfred Stein

Chenghu Zhou

Consortium, OpenGIS

Dowman I.

Gong D. C.

Jianghong Ma

Qin X. W.

Tao C. V.

Tianjun Wu

Wansbeek T.

Xian Guo

Yang X.

Yong Ge

Yongze Song

Yongzhao Wei

The rational function model (RFM) is widely applied to orthorectification of aerial and satellite imagery. This article proposes a new method named Ortho-WTLS to solve the RFM in remote-sensing imagery orthorectification. Based on a weighted total least squares (WTLS) estimator, the proposed method allows one to handle coordinates of ground control points (GCPs) that contain errors and are of unequal accuracies. This situation occurs, e.g. if GCPs are automatically selected. In the proposed model, first, the relationship of two linearization methods for an RFM with errors contained in GCPs is investigated and results in a hybrid linearization. Next, based on WTLS, RFM coefficients are estimated with an iterative computation function. Finally, the performance of the Ortho-WTLS method thus obtained is investigated using simulated images and remotely sensed images by collecting GCPs with varying errors. Experimental results show that the Ortho-WTLS method achieves a more robust estimation of model parameters and a higher orthorectification accuracy when compared with standard LS-based RFM estimation. We conclude that the quality of GCPs has a large impact on the accuracy and that an increasing number of low-precision GCPs may lead to a decrease in orthorectification quality

Ge, Yong

Wei, Yongzhao

Song, Yongze

Wu, Tianjun

Stein, Alfred

Guo, Xian

Zhou, Chenghu

Ma, Jianghong

University of Twente Research Information

English

A WTLS-based rational function model for orthorectification of remote-sensing imagery

A WTLS-based rational function model for orthorectification of remote-sensing imagery

Abstract

Similar works

Full text

Available Versions

University of Twente Research Information

espace@Curtin

Crossref

NARCIS