An automated fine registration of multisensor remote sensing imagery
Deniz Gerçek, Davut Çeşmecı, M. Kemal Güllü, Alp Ertürk, Sarp Ertürk · 2012
In this study we propose an automated fine registration of EO-1 Hyperion and IKONOS imagery. An intensity based registration that is area-based and pixelwise is performed to register given images of divergent spatial and spectral resolution. Two similarity measures that are commonplace in image registration; NCC and NMI, and an operation that is particular to image restoration; CTO is adopted as an error measure as a novelty in image registration. We are convinced with the performance and efficiency of CTO compared to other two common methods of intensity-based registration.