Automatic co-registration of satellite time series via least squares adjustment

Image-to-image co-registration is a fundamental task during data processing of satellite time series. This paper presents a new multi-image co-registration algorithm that simultaneously seeks for corresponding points in all the images of a sequence. Image co-registration parameters are then computed on the basis of a global adjustment. The implemented algorithm provides sub-pixel accuracy, similar to that achievable with interactive measurements, but it is also able to register also images which do not directly share common features with the master. Results for a (i) synthetic dataset and a (ii) real complex multi-temporal series made up of 13 Landsat-4/TM and Landsat-5/TM images collected over a period of 30 years are illustrated and discussed. The implemented algorithm has been proved to be atmospheric resistant and quite robust against land cover changes, cloud cover, and snow.