Geometric correction of GF-1 satellite images based on block adjustment of rational polynomial model

Abstract: GF-1 satellite was launched successfully in April 2013, and its wide field view (WFV) images have been widely applied in agricultural remote sensing monitoring practice in China. To obtain high precision of image positioning, the paper proposes a correction method for acquiring higher geometric positioning precision based on block adjustment method to correct rational polynomial coefficients (RPC) of high resolution WFV. A business process including adjustment model construction, adjustment parameter calculation and geometric registration based on reference images has been formed. Firstly, affine transformation relation among images, namely, a block adjustment model, has been built based on the relationship between the RPC parameter image points and ground points; secondly, initial value of connection points is identified, and combined with a few ground control points, the affine transformation coefficients of various images are calculated so as to conduct the image block adjustment. Meanwhile, orthoimage is produced based on adjustment results and DEM (digital elevation model), and the correction result with sub-pixel accuracy is achieved. The calculation of adjustment parameters is achieved through 2 steps. The first step is to identify the initial value of the connection point. By utilizing one degree term of RPC model, the plane coordinates of the connection points are iterated and updated, till they converge to a stable state. The elevation values are extracted from DEM; the second is to identify affine transformation parameters. The updated connection points with a few ground control points are entered into block adjustment model to establish error equation. The elevation values acquired from DEM are taken as a constraint condition, and the relevance between plane coordinates and elevations is eliminated to ensure that the block adjustment model works. Meanwhile, the unknown variable is calculated by using the point-by-point elimination method. The block adjustment results under 3 different conditions of mixed terrain, plain area and mountainous area show that, the adjustment results of whole connection points have a relative higher positioning precision, with the errors of 0.3046, 0.4674 and 0.3365 pixels respectively at the row direction, and with the errors of 0.3677, 0.2849 and 0.2889 pixels respectively at the column direction; block adjustments with a few control points have very high absolute positioning precision, with the errors of 0.3648, 0.5041 and 0.3605 pixels respectively at the row direction, and with the errors of 0.4954, 0.4039 and 0.6323 pixels respectively at the column direction. Finally, under the support of base control map of agriculture application, the geometric registration of raw images, RPC correction images, and images after block adjustment is conducted, and the geometric correction precision under different input image conditions is analyzed. Only images after block adjustment have reached correction precision of sub-pixel. The errors at the row direction under 3 conditions of mixed terrain, plain area and mountainous area are 0.6857, 0.6664 and 1.0646 pixels respectively, and those at the column direction are 0.4342, 0.4696 and 0.5609 pixels respectively, indicating that the research method proposed by this paper can achieve accurate geometric correction under the condition of a few control points, though there is no significant improvement compared with the precision before geometric correction. After comparing the DEM with different resolutions in the model, we find that the precision of DEM affects the correction result. Applying higher resolution in mountainous areas can achieve better positioning precision. The above results show that this method can effectively improve the geometric correction precision of WFV images of CF-1 satellite, and it has been preliminarily applied in the operation of agriculture remote sensing monitoring.