activity
20182020
collaborators

6 papers

eess.IV2020

Multi-Objective CNN Based Algorithm for SAR Despeckling

Sergio Vitale, Giampaolo Ferraioli, Vito Pascazio

Deep learning (DL) in remote sensing has nowadays become an effective operative tool: it is largely used in applications such as change detection, image restoration, segmentation,…

eess.IV2020

Complexity Analysis of an Edge Preserving CNN SAR Despeckling Algorithm

Sergio Vitale, Giampaolo Ferraioli, Vito Pascazio

SAR images are affected by multiplicative noise that impairs their interpretations. In the last decades several methods for SAR denoising have been proposed and in the last years g…

eess.IV2020

Edge Preserving CNN SAR Despeckling Algorithm

Sergio Vitale, Giampaolo Ferraioli, Vito Pascazio

SAR despeckling is a key tool for Earth Observation. Interpretation of SAR images are impaired by speckle, a multiplicative noise related to interference of backscattering from the…

eess.IV2019

A Novel Cost Function for Despeckling using Convolutional Neural Networks

Giampaolo Ferraioli, Vito Pascazio, Sergio Vitale

Removing speckle noise from SAR images is still an open issue. It is well know that the interpretation of SAR images is very challenging and despeckling algorithms are necessary to…

cs.CV2019

A New Ratio Image Based CNN Algorithm For SAR Despeckling

Sergio Vitale, Giampaolo Ferraioli, Vito Pascazio

In SAR domain many application like classification, detection and segmentation are impaired by speckle. Hence, despeckling of SAR images is the key for scene understanding. Usually…

cs.CV2018

Guided patch-wise nonlocal SAR despeckling

Sergio Vitale, Davide Cozzolino, Giuseppe Scarpa +2

We propose a new method for SAR image despeckling which leverages information drawn from co-registered optical imagery. Filtering is performed by plain patch-wise nonlocal means, o…