SAR image despeckling through convolutional neural networks
In this paper we investigate the use of discriminative model learning through Convolutional
Neural Networks (CNNs) for SAR image despeckling. The network uses a residual learning …
Neural Networks (CNNs) for SAR image despeckling. The network uses a residual learning …
Learning a dilated residual network for SAR image despeckling
In this paper, to break the limit of the traditional linear models for synthetic aperture radar
(SAR) image despeckling, we propose a novel deep learning approach by learning a non …
(SAR) image despeckling, we propose a novel deep learning approach by learning a non …
Synthetic aperture radar image and its despeckling using variational methods: A Review of recent trends
Synthetic aperture radar (SAR) has drawn significant interest from the remote sensing
community due to its ability to provide high-resolution images irrespective of weather and …
community due to its ability to provide high-resolution images irrespective of weather and …
[图书][B] Remote sensing image fusion: A practical guide
C Pohl, J Van Genderen - 2016 - taylorfrancis.com
Remote Sensing Image Fusion: A Practical Guide gives an introduction to remote sensing
image fusion providing an overview on the sensors and applications. It describes data …
image fusion providing an overview on the sensors and applications. It describes data …
Unassisted quantitative evaluation of despeckling filters
SAR (Synthetic Aperture Radar) imaging plays a central role in Remote Sensing due to,
among other important features, its ability to provide high-resolution, day-and-night and …
among other important features, its ability to provide high-resolution, day-and-night and …
Multitemporal SAR image despeckling based on block-matching and collaborative filtering
We propose a despeckling algorithm for multitemporal synthetic aperture radar (SAR)
images based on the concepts of block-matching and collaborative filtering. It relies on the …
images based on the concepts of block-matching and collaborative filtering. It relies on the …
Speckle noise removal in SAR images using Multi-Objective PSO (MOPSO) algorithm
R Sivaranjani, SMM Roomi, M Senthilarasi - Applied Soft Computing, 2019 - Elsevier
SAR images are inherently affected by speckle noise, and although attempts made earlier to
remove speckle succeeded, there is still the challenge of preserving the edges of images …
remove speckle succeeded, there is still the challenge of preserving the edges of images …
Despeckling SAR images with Log-Yeo-Johnson transformation and conditional diffusion models
Y Ma, P Ke, H Aghababaei, L Chang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Satellite images of synthetic aperture radar (SAR) sensors are contaminated by speckles
from the coherent imaging mechanism. Although removing or mitigating speckle has been a …
from the coherent imaging mechanism. Although removing or mitigating speckle has been a …
A Comparative Assessment of Machine-Learning Techniques for Forest Degradation Caused by Selective Logging in an Amazon Region Using Multitemporal X-Band …
The near-real-time detection of selective logging in tropical forests is essential to support
actions for reducing CO2 emissions and for monitoring timber extraction from forest …
actions for reducing CO2 emissions and for monitoring timber extraction from forest …
Super-Resolution of SAR Images with Speckle Noise Based on Combination of Cubature Kalman Filter and Low-Rank Approximation
X Luo, R Bao, Z Liu, S Zhu, Q Liu - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this article, two novel methods for synthetic aperture radar (SAR) image super-resolution
(SR) are proposed. The main challenge for SAR image SR reconstruction is speckle noise …
(SR) are proposed. The main challenge for SAR image SR reconstruction is speckle noise …