標題: Bias Compensation in a Rigorous Sensor Model and Rational Function Model for High-Resolution Satellite Images
作者: Teo, Tee-Ann
土木工程學系
Department of Civil Engineering
公開日期: 1-Dec-2011
摘要: This paper presents three bias-compensated models for the geometric correction of high-resolution satellite images. The proposed models include the bias-compensated rigorous sensor model (RSM) in the orbital space, the bias-compensated RSM in the image space, and the bias-compensated rational function model (RFM) in the image space. The RSM and RSM use the on-board data and sensor-oriented rational polynomial coefficients (RPCs) provided in imagery metadata respectively. Test images include Quick Bird, World View-1, and World View-2 Basic images. Experimental results indicate that the bias-compensated RSM using the zero order polynomials function in the orbital space provides higher accuracy. A comparison of the bias-compensated RSM and RFM in the image space shows that these models behave similarly, and the Maximum difference in root-mean-square error is less than 0.1 m. These results show that all the proposed methods obtain accuracy of better than 1 pixel, except for the translation in the image space.
URI: http://hdl.handle.net/11536/14914
ISSN: 0099-1112
期刊: PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
Volume: 77
Issue: 12
起始頁: 1211
結束頁: 1220
Appears in Collections:Articles