Sar Image Despeckling
10 papers with code • 0 benchmarks • 0 datasets
Despeckling is the task of suppressing speckle from Synthetic Aperture Radar (SAR) acquisitions.
Image credits: GRD Sentinel-1 SAR image despeckled with SAR2SAR-GRD
Benchmarks
These leaderboards are used to track progress in Sar Image Despeckling
Latest papers with no code
PolMERLIN: Self-Supervised Polarimetric Complex SAR Image Despeckling with Masked Networks
However, existing methods deal solely with single-polarization images and cannot handle the multi-polarization images captured by modern satellites.
SAR Despeckling via Regional Denoising Diffusion Probabilistic Model
Speckle noise poses a significant challenge in maintaining the quality of synthetic aperture radar (SAR) images, so SAR despeckling techniques have drawn increasing attention.
A Self-supervised SAR Image Despeckling Strategy Based on Parameter-sharing Convolutional Neural Networks
The training image pairs are generated by the sub-sampler from real-word SAR image to estimate the noise distribution.
Deep Learning Methods For Synthetic Aperture Radar Image Despeckling: An Overview Of Trends And Perspectives
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 Based on Convolutional Denoising Autoencoder
In this paper, the limited scale of dataset make a efficient exploration by using convolutioal denoising autoencoder (C-DAE) to reconstruct the speckle-free SAR images.
Blind SAR Image Despeckling Using Self-Supervised Dense Dilated Convolutional Neural Network
The synthetic and real-data experiments demonstrate that proposed BDSS can achieve despeckling effectively while maintaining well features such as edges, point targets, and radiometric.
SAR Image Despeckling Using Quadratic-Linear Approximated L1-Norm
Speckle noise, inherent in synthetic aperture radar (SAR) images, degrades the performance of the various SAR image analysis tasks.
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.
Sar image despeckling based on nonlocal similarity sparse decomposition
This method combines the nonlocal self-similarity partition and a proposed modified sparse decomposition.
Systholic Boolean Orthonormalizer Network in Wavelet Domain for SAR Image Despeckling
We describe a novel method for removing speckle (in wavelet domain) of unknown variance from SAR images.
