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.

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

BARAZZETTI, LUIGI;SCAIONI, MARCO;GIANINETTO, MARCO
2014

Abstract

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/884965
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