Accuracy Evaluation of Rational Polynomial Coefficients Solution for Quickbird Imagery Based on Auxiliary Ground Control Points

Relative to the rigorous physical model, rational polynomial coefficient (RPC) has been adopted as an alternative common sensor model data for image Geometric correction exploitation. In this paper, based on collected QuickBird imagery in Shanghai region, the iterative least-squares solution with regularization(ILSR) is derived to determine the RPCs by using 50 fair distributed ground control points(GCPs)firstly. Two methods are then used to refine determined RPCs under different circumstance as: 1) when both the original and the additional GCPs are available, the RPCs will be recomputed using the batch iterative least-squares solution with regularization (BILSR) method; and 2) when only the new GCPs are available, incremental discrete Kalman filtering (IDKF) method has been described. Meanwhile, check points are used to evaluate their geo-positioning accuracy, and their comparison is conducted. Finally, some conclusion is then achieved when handing the high resolution imagery in metropolitan area.