A Review on SAR Image and its Despeckling

P Singh, M Diwakar, A Shankar, R Shree… - … Methods in Engineering, 2021 - Springer
The method of speckle reduction is widely used in synthetic aperture radar (SAR) imagery
over the last three decades. The SAR images are inherently speckled in nature. Speckle …

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 …

Deep feature correlation learning for multi-modal remote sensing image registration

D Quan, S Wang, Y Gu, R Lei, B Yang… - … on Geoscience and …, 2022 - ieeexplore.ieee.org
Deep descriptors have advantages over handcrafted descriptors on local image patch
matching. However, due to the complex imaging mechanism of remote sensing images and …

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 …

A comprehensive survey of machine learning applied to radar signal processing

P Lang, X Fu, M Martorella, J Dong, R Qin… - arXiv preprint arXiv …, 2020 - arxiv.org
Modern radar systems have high requirements in terms of accuracy, robustness and real-
time capability when operating on increasingly complex electromagnetic environments …

Review on nontraditional perspectives of synthetic aperture radar image despeckling

P Singh, A Shankar, M Diwakar - Journal of Electronic Imaging, 2023 - spiedigitallibrary.org
Synthetic aperture radar (SAR) image despeckling is a preprocessing method. SAR images
are, by default, noisy in nature. The kind of noise found in SAR images is called speckle …

Augmented noise learning framework for enhancing medical image denoising

S Rai, JS Bhatt, SK Patra - IEEE Access, 2021 - ieeexplore.ieee.org
Deep learning attempts medical image denoising either by directly learning the noise
present or via first learning the image content. We observe that residual learning (RL) often …

Residual in residual scaling networks for polarimetric SAR image despeckling

H Lin, K Jin, J Yin, J Yang, T Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Speckle reduction is a longstanding topic for polarimetric synthetic aperture radar (PolSAR)
images. In this article, we propose a novel end-to-end PolSAR image despeckling …

An unsupervised deep learning framework for medical image denoising

S Rai, JS Bhatt, SK Patra - arXiv preprint arXiv:2103.06575, 2021 - arxiv.org
Medical image acquisition is often intervented by unwanted noise that corrupts the
information content. This paper introduces an unsupervised medical image denoising …

Performance evaluation of DFT based speckle reduction framework for synthetic aperture radar (SAR) images at different frequencies and image regions

V Jain, S Shitole, M Rahman - Remote Sensing Applications: Society and …, 2023 - Elsevier
Abstract Polarimetric Synthetic Aperture Radar (PolSAR) images are widely used for remote
sensing and geoscience applications. However, the coherent processing of radar signals in …