Xiangli Tan
ABSTRACT
The acquirement of control points is an important step in the geometric correction of remote sensing image. In this paper, effect of the number and spatial pattern of control points on image correction accuracy was analyzed and the image distortion parameter was solved by using star control points (SCPs). The analysis indicates that the more stars is not always good for the accuracy of geometric correction. Hence, to achieve the optimal accuracy, a new method for the optimization of SCPs was studied in this paper. The core idea of this method is that taking the root mean square error (RMSE) as the key criterion to determine the SCPs and adopting the method of cross validation to determine which SCPs will be selected. If the percentage of the maximum correction error (MCE) in the whole image less than 2(decide on demand) pixels become larger, it shows that the method is effective. Finally, the percentage mentioned above increase from 78.49% to 92.83%. So, what we can conclude is that this method is an effective way which can obviously improve the accuracy of geometric correction of remote sensing image.
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Index Terms
- Star Control Points Optimization on Remote Sensing Image Geometric Rectification
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