An Error-Based Block Adjustment Method for Multi-Angle Satellite Imagery Without Ground Control Points

Geo-positioning accuracy improvement is one of the most important step of remote sensing image preprocessing. Traditional methods require a large number of ground control points(GCPs) which consuming lots of manpower and financial resources. With the resolution up to 0.8m, the original geo-positioning accuracy of the Chinese Gaofen(GF-2) multi-angle imagery is about 90m which means a limited application in geometric processing. In this paper, we propose a new method to improve the geometric performance of the multi-angle satellite imagery based on the geometric error sources of this experimental dataset without GCPs. Under the condition of weak intersection of our test dataset, we use a DEM-assisted approach to acquire a more accurate initial position accuracy of all tie points, and all extracted data is clustered by the Density based spatial clustering of applications with noise(DBSCAN) algorithm in order to eliminate points or impages with large positioning error automatically. Then, the error-based block adjustment model are proposed and investigated to improved the geometric performance of the experimental dataset. Based on our proposed method, 142 multi-angle GF-2 satellite images covering the western Beijing area are experimented and the root mean square error(RMSE) of the geometric accuracy is improved up to about 12m in plane and 6m in height, which shows a significantly improvement in geo-positioning accuracy of these multi-angle GF-2 remote sensing imagery.