Deep learning methods for synthetic aperture radar image despeckling: An overview of trends and perspectives

G Fracastoro, E Magli, G Poggi… - … and Remote Sensing …, 2021 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) images are affected by a spatially correlated and signal-
dependent noise called speckle, which is very severe and may hinder image exploitation …

SAR image despeckling using a convolutional neural network

P Wang, H Zhang, VM Patel - IEEE Signal Processing Letters, 2017 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) images are often contaminated by a multiplicative noise
known as speckle. Speckle makes the processing and interpretation of SAR images difficult …

Speckle2Void: Deep self-supervised SAR despeckling with blind-spot convolutional neural networks

AB Molini, D Valsesia, G Fracastoro… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Information extraction from synthetic aperture radar (SAR) images is heavily impaired by
speckle noise, and hence, despeckling is a crucial preliminary step in scene analysis …

MRDDANet: A multiscale residual dense dual attention network for SAR image denoising

S Liu, Y Lei, L Zhang, B Li, W Hu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Synthetic aperture radar (SAR), due to its inherent characteristics, will produce speckle
noise, which results in the deterioration of image quality, so the removal of speckle in SAR …

Multi-objective CNN-based algorithm for SAR despeckling

S Vitale, G Ferraioli, V Pascazio - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
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 …

SAR speckle removal using hybrid frequency modulations

S Liu, L Gao, Y Lei, M Wang, Q Hu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) images often interfere with speckle artifacts that have a great
impact on subsequent processing and analysis operations. To remove speckle artifacts, this …

A deep neural network based on prior driven and structural-preserving for SAR image despeckling

C Lin, C Qiu, H Jiang, L Zou - IEEE Journal of Selected Topics …, 2023 - ieeexplore.ieee.org
Remarkable effectiveness has been demonstrated by deep neural networks in the
despeckling task for synthetic aperture radar (SAR) images. However, blurring and loss of …

Nonlocal CNN SAR image despeckling

D Cozzolino, L Verdoliva, G Scarpa, G Poggi - Remote Sensing, 2020 - mdpi.com
We propose a new method for SAR image despeckling, which performs nonlocal filtering
with a deep learning engine. Nonlocal filtering has proven very effective for SAR …

Ratio-based multitemporal SAR images denoising: RABASAR

W Zhao, CA Deledalle, L Denis, H Maître… - … on Geoscience and …, 2019 - ieeexplore.ieee.org
In this paper, we propose a fast and efficient multitemporal despeckling method. The key
idea of the proposed approach is the use of the ratio image, provided by the ratio between …

SAR despeckling using multi-objective neural network trained with generic statistical samples

S Vitale, G Ferraioli, AC Frery… - … on Geoscience and …, 2023 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) images are impaired by the presence of speckles. Despite
the deep interest of scholars in the last decades, SAR image despeckling is still an open …