Precise Sensor Orientation of High-Resolution Satellite Imagery With the Strip Constraint

Abstract

To achieve precise sensor orientation of high- resolution satellite imagery (HRSI), ground control points (GCPs) or height models are necessary to remove biases in orientation parameters. However, measuring GCPs is costly, laborious, and time consuming. We cannot even acquire well-defined GCPs in some areas. In this paper, a strip constraint model is established according to the geometric invariance that the biases of image points remain the same in dividing a strip image into standard images. Based on the rational function model and the strip constraint model, a feasible sensor orientation approach for HRSI with the strip constraint is presented. Through the use of the strip constraint, the bias compensation parameters of each standard image in the strip can be solved simultaneously with sparse GCPs. This approach remains effective even when the intermediate standard images in the strip are unavailable. Experimental results of the three ZiYuan-3 data sets show that two GCPs in the first image and two GCPs in the last image are sufficient for the sensor orientation of all the standard images in the strip. An orientation accuracy that is better than 1.1 pixels can be achieved in each standard image. Moreover, the inconsistent errors of tie points between adjacent standard images can also be reduced to less than 0.1 pixel. This result can guarantee that the generated complete digital orthophoto map of the whole strip is geometrically seamless.