Automatic precision correction of satellite images using the GCP chips of lower resolution

Precision correction is the process of geometrically aligning images to a reference coordinate system using GCPs (Ground Control Points). Many application of remote sensing data, such as change detection, mapping, and environmental monitoring, rely on the accuracy of precision correction. However it is very time consuming, laborious and expensive process. In this research, we propose a new method for automatic precision correction of satellite images using the GCP chips collected from lower resolution satellite images to reduce or eliminate the number of GCPs required. Different Earth observation satellites provide the satellite images of different resolution, different swath and different position accuracy. In general, the satellite images of lower resolution have wider swath and vice versa. In that sense, if we can utilize the GCP chips collected from lower resolution satellite images to do precision correction of the higher resolution satellite images then the number of GCPs required to have a precisely corrected images of the same area would be reduced. In this experiment, we used GCP chips collected from Landsat-7 panchromatic images of 15 m resolutions to perform precision correction of the KOMPSAT-1 EOC images of 6.7 m resolutions. In this case, since Landsat-7 images provide higher positional accuracy of less than 250 m at the systematically corrected level (L1G) comparing about 2 km positional accuracy of KOMPSAT-1, GCPs collected from level 1G of Landsat-7 images can provide enough accuracy in certain applications. To utilize this approach easily, this study would be applied to the automatic precision correction method developed previously, which exploits the normalized cross correlation and the RANSAC (Random Sample Consensus) algorithm to removed the outliers of matching results. The initial result showed the possibility of using GCP chips of lower resolution to carry out precision correction in the frame of the automatic precision correction method utilizing RANSAC algorithm.