An efficient multi-stage hyper-spectral aerial image registration technique in the presence of differential spatial and temporal sensor uncertainty with application to large critical infrastructures & key resources (CIKR) surveillance
Image registration has wide applications in remote sensing, medicine, cartography, and computer vision. This paper describes a method for aerial image registration, which is based on joint feature-spatial spaces, curve matching, and template matching. The entire algorithm consists of (i) segmentation and region representation, (ii) region matching based on joint feature-spatial space, (iii) transformation model estimation based on curve matching and template matching, and (iv) image transformation. Experiment results show the effectiveness of this algorithm.