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Abstract
This paper explores the geometric performance of integration of aerial and QuickBird images. Different integration scenarios with different bias compensation schemes in the image space were studied, and the results showed that the introduction of the aerial images can improve the geopositioning accuracy of the QuickBird images to close to the aerial pixel level. In addition, methods of correcting biases in the object space were tested, and the results revealed the disadvantage of the bias compensation in the object space. An experiment was conducted for mapping ground objects such as inland rivers, buildings, and roads using the proposed integration method.
Acknowledgements
The work described in this paper was substantially supported by the National Natural Science Foundation of China (Project No.40771174), High-tech Research and Development Program of China (Project No. 2007AA12Z178 and 2009AA12Z131), Foundation of Shanghai Dawn Scholarship and Rising-star Program (Project No. 07SG24 and 08QH14022).