A Feature-Based Approach to Automated Registration of Remotely Sensed Images

In this paper, a new automatic control point selection and matching technique for satellite image registration is proposed. This technique exploits the invariant relations between regions of a reference and a sensed image, respectively. It involves an edge-based selection of the most distinctive control points in the reference image. The search for the corresponding control points in the sensed image is based on local similarity detection by means of template matching according to a combined invariants-based similarity measure. The final transformation of the sensed image according to the selected control points is performed by using the thin-plate spline (TPS) interpolation. The proposed technique has been successfully applied to register multitemporal SPOT images from urban and agricultural areas. The experimental results demonstrate the efficiency and accuracy of the algorithm which have outperformed manual registration in terms of root mean square error at the control points