Multitemporal Speckle Reduction With Self-Supervised Deep Neural Networks

Autor: Ines Meraoumia, Emanuele Dalsasso, Loic Denis, Remy Abergel, Florence Tupin

Publikováno v: IEEE Transactions on Geoscience and Remote Sensing. 61:1-14

Speckle filtering is generally a prerequisite to the analysis of synthetic aperture radar (SAR) images. Tremendous progress has been achieved in the domain of single-image despeckling. Latest techniques rely on deep neural networks to restore the var

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d37f8d86fedf3b74275dac4f946f4ede
https://doi.org/10.1109/tgrs.2023.3237466

Fast strategies for multi-temporal speckle reduction of Sentinel-1 GRD images

Autor: Ines Meraoumia, Emanuele Dalsasso, Loic Denis, Florence Tupin

Reducing speckle and limiting the variations of the physical parameters in Synthetic Aperture Radar (SAR) images is often a key-step to fully exploit the potential of such data. Nowadays, deep learning approaches produce state of the art results in s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a36b30ea2cc8fce2f2ba5ea1cd171880
http://arxiv.org/abs/2207.11111

A review of deep-learning techniques for SAR image restoration

Autor: Emanuele Dalsasso, Florence Tupin, Loïc Denis

Publikováno v: IGARSS 2021
IGARSS 2021, Jul 2021, Bruxelles (virtual), Belgium
HAL
IGARSS

International audience; The speckle phenomenon remains a major hurdle for the analysis of SAR images. The development of speckle reduction methods closely follows methodological progress in the field of image restoration. The advent of deep neural ne

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1280d7c4ee6f19452d9579d5338d895
https://hal-ujm.archives-ouvertes.fr/ujm-03123042/file/main.pdf

How to handle spatial correlations in SAR despeckling? Resampling strategies and deep learning approaches

Autor: Emanuele Dalsasso, Loic Denis, Florence Tupin

Publikováno v: EUSAR 2021: 13th European Conference on Synthetic Aperture Radar
EUSAR 2021: 13th European Conference on Synthetic Aperture Radar, Mar 2021, Leipzig (virtual), Germany. pp.1-6
HAL

International audience; Speckle noise strongly affects Synthetic Aperture Radar (SAR) images, causing strong intensity fluctuations that make them difficult to analyze. Although many speckle reduction algorithms have been proposed, how to effectively

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::b3250accc9bb4e79b08b21627914cf33
https://hal.telecom-paris.fr/hal-02538046

SAR Image Despeckling by Deep Neural Networks: from a Pre-Trained Model to an End-to-End Training Strategy

Autor: Loïc Denis, Wen Yang, Florence Tupin, Xiangli Yang, Emanuele Dalsasso

Publikováno v: Remote Sensing
Remote Sensing, MDPI, 2020, 12 (16), pp.2636. ⟨10.3390/rs12162636⟩
Remote Sensing, Vol 12, Iss 2636, p 2636 (2020)
Remote Sensing; Volume 12; Issue 16; Pages: 2636

Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) images. Many different schemes have been proposed for the restoration of intensity SAR images. Among the different possible approaches, methods based on convolutional neural

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4ba0306052675849c7e0ad1475b8b75
https://hal.telecom-paris.fr/hal-02944565