Abstract : Synthetic aperture radar (SAR) and optical satellite image registration is a field that developed in the last decades and gave rise to a great number of approaches. The registration process is composed of several steps: feature definition, feature comparison and optimization of a geometric transformation between the images. Feature definition can be done using simple traditional filtering or more complex deep learning (DL) methods. In this paper, two traditional approaches and a DL approach are compared. One can then wonder if the complexity of DL is worth to address the registration task. The aim of this paper is to quantitatively compare approaches rooted in distinct methodological areas on two common datasets with different resolutions. The comparison suggests that, although more complex, the DL approach is more precise than traditional methods.
https://hal.telecom-paris.fr/hal-03325418 Contributor : Florence TupinConnect in order to contact the contributor Submitted on : Tuesday, August 24, 2021 - 5:23:05 PM Last modification on : Tuesday, October 19, 2021 - 11:15:17 AM Long-term archiving on: : Friday, November 26, 2021 - 9:22:52 AM
Béatrice Pinel-Puysségur, Luca Maggiolo, Michel Roux, Nicolas Gasnier, David Solarna, et al.. EXPERIMENTAL COMPARISON OF REGISTRATION METHODS FOR MULTISENSOR SAR-OPTICAL DATA. IGARSS, 2021, Bruxelles, Belgium. ⟨hal-03325418⟩