Automated RPCs Bias Compensation for KOMPSAT Imagery Using Orthoimage GCP Chips in Korea

Abstract

High-resolution satellite images, including KOMPSAT, WorldView-3, and Pléiades, are widely used for mapping and environmental monitoring. In particular, satellite images with high spatial resolution should have accurate location information to provide essential spatial information. To this end, most high-resolution satellite images files are provided with rational polynomial coefficients (RPCs) that can be used for the sensor modeling. However, the RPCs have an initial bias. Therefore, most satellite image platforms and researchers match satellite images using ground control points (GCPs) information and perform RPCs bias compensation of images using matching information. In Korea, an image-based GCP chip built using orthographic images is provided for the georegistration of various satellite images. In this manuscript, RPCs bias compensation of KOMPSAT-3A satellite images was performed using GCP chips, and then, the possibility of automation of RPCs bias compensation through GCP chip was analyzed. Image matching such as area-based and edge-based techniques were used, and the results of RPCs bias compensation using GCP chips were analyzed through experiments in various regions. The automated compensation in either area-based or edge-based matching performed well with within 1.5 pixel level of accuracy for test areas with various topographic features. However the forest area was challenging such that new GCP chips with rich feature information were required. In addition, edge-based matching could overcome large seasonal differences including snow cover.