Reliable Subpixel Ground Control Point Estimation Algorithm Using Vector Roads

Abstract

This letter proposes a novel algorithm for reliable and accurate ground control point (GCP) estimation, which uses vector road network data as a reference. Roads are detected in satellite images, and road patches are used as a template, which is matched against the vector road data by using a nonlinear criterion based on the distance transform. The proposed approach is compared with the standard correlation-based template matching in terms of the reliability and accuracy of localization on a test set of five RapidEye images with 380 reference control points. The experiments demonstrate superior reliability with respect to the size of the search window and the variable image acquisition conditions. While the subpixel accuracy is achieved by the cross-correlation method over the search area up to 20% of the template size, the proposed method achieves comparable accuracy over a search area that is ten times larger than the template image.