101 citations · 132 across the 2 of their papers we have counts for
2 papers
eess.IV2021★ 31 cited
Despeckling Polarimetric SAR Data Using a Multi-Stream Complex-Valued Fully Convolutional Network
Adugna G. Mullissa, Claudio Persello, Johannes Reiche
A Polarimetric Synthetic Aperture Radar (PolSAR) sensor is able to collect images in different polarization states, making it a rich source of information for target characterizati…
eess.IV2020★ 101 cited
deSpeckNet: Generalizing Deep Learning Based SAR Image Despeckling
Adugna G. Mullissa, Diego Marcos, Devis Tuia +2
Deep learning (DL) has proven to be a suitable approach for despeckling synthetic aperture radar (SAR) images. So far, most DL models are trained to reduce speckle that follows a p…