Accuracy Analysis of Polynomial RFM Adjustment Models for Worldview-1 Imagery

In this paper, the specifications of WorldView-1 and its payloads are introduced, and seven polynomial adjustment models used to improve the vendor-provided Rational Function Model (RFM) accuracy are discussed in detail. WorldView-1 images of mountainous area of Yunnan Province are used to test the correction accuracy of these adjustment models. Results show that the accuracy of seven modes is similar when using well-distributed GCPs with high accuracy and the planimetry RMS errors are better than 1.6 pixels (0.9 meter). The correction accuracy of different polynomial RFM adjustment models using sparse, badly-distributed GCPs is analyzed in this paper. Results show that with the degradation of GCPs accuracy, the accuracy of independent check points(ICPs) using zero order polynomial adjustment model remains stable, while that of one order and two order polynomial adjustment models degrade distinctly. Experiments show that zero-order polynomial RFM adjustment is the simplest, most adaptive and has highest accuracy for WorldView-1 image, and it is recommended to be used in difficult area mapping with sparse or badly-distributed GCPs.