J. W. Goodman, Some fundamental properties of speckle, Journal Optical Society of America, vol.66, issue.11, 1976.

L. Denis, F. Tupin, J. Darbon, and M. Sigelle, Joint Regularization of Phase and Amplitude of InSAR Data: Application to 3D reconstruction, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.11, pp.3774-3785, 2009.
URL : https://hal.archives-ouvertes.fr/ujm-00404557

A. Achim, P. Tsakalides, and A. Bezerianos, SAR image denoising via Bayesian wavelet shrinkage based on heavy-tailed modeling, IEEE Trans. Geosci. Remote Sens, vol.41, issue.8, 2003.

A. Buades, B. Coll, and J. M. Morel, Image Denoising Methods . A New Nonlocal Principle, SIAM Review, vol.52, issue.1, 2010.

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, Image denoising by sparse 3-D transform-domain collaborative filtering, IEEE Trans. Image Process, vol.16, issue.8, 2007.

V. Duval, J. Aujol, and Y. Gousseau, A bias-variance approach for the non-local means, SIAM Journal of Imaging Science, pp.760-788, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00947885

A. Buades, M. Lebrun, and J. Morel, A non-local Bayesian image denoising algorithm, SIAM Journal on Imaging Science, 2013.

M. Aharon, M. Elad, and A. Buckstein, K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation, IEEE Transactions on Image Processing, 2006.

D. Zoran and Y. Weiss, From learning models of natural image patches to whole image restoration, 2011.

C. Deledalle, V. Duval, and J. Salmon, Non-local methods with shape-adaptive patches, Journal of Mathematical Imaging and Vision, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00536723

M. Lebrun, M. Colom, and J. Morel, The Noise Clinic: a Blind denoising Algorithm, Image Processing On Line, 2015.

P. Coupé, P. Hellier, C. Kervrann, and C. Barillot, Bayesian non local means-based speckle filtering, IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1291-1294, 2008.

C. Deledalle, L. Denis, and F. Tupin, Poisson NL-means: unsupervised non-local means for Poisson noise, ICIP, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00957982

.. Ch, L. Deledalle, F. Denis, and . Tupin, Iterative weighted maximum likelihood denoising with probabilistic patch-based weights, IEEE Transactions on Image Processing, vol.18, issue.12, 2009.

.. Ch, L. Deledalle, G. Denis, F. Poggi, L. Tupin et al., Exploiting Patch Similarity for SAR Image Processing, IEEE Signal Processing Magazine, 2014.

C. Deledalle, L. Denis, G. Ferraioli, V. Pascazio, G. Shirinzi et al., Very-High resolution and interferometric SAR: Markovian and patch-based non-local mathematical models, Mathematicals models for remote sensing image processing, pp.137-191, 2017.
URL : https://hal.archives-ouvertes.fr/ujm-01565508

.. Ch, L. Deledalle, F. Denis, and . Tupin, How to compare noisy patches? patch similarity beyond gaussian noise, International Journal of Computer Vision, 2012.

.. Ch, L. Deledalle, F. Denis, A. Tupin, M. Reigber et al., NL-SAR: a unified Non-Local framework for resolutionpreserving (Pol)(In)SAR denoising, IEEE Transactions on Geoscience and Remote Sensing, vol.53, issue.4, pp.2021-2038, 2015.

S. Parrilli, M. Poderico, C. V. Angelino, and L. Verdoliva, A Nonlocal SAR Image Denoising Algorithm Based on LLMMSE Wavelet Shrinkage, IEEE Trans. Geosci. Remote Sens, vol.50, issue.2, 2012.

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, Image denoising by sparse 3D transform-domain collaborative, IEEE Transactions on Image Processing, vol.16, issue.8, pp.2089-2095, 2007.

G. Ferraioli, B. Kanoun, V. Pascazio, and G. Shirinzi, SAR image restoration via a NL approach based on a KS test, IGARSS, 2018.

H. Zhong, Y. Li, and L. Jiao, SAR Image Despeckling Using Bayesian Nonlocal Means Filter With Sigma Preselection, IEEE Geosci. Remote Sens. Lett, vol.8, issue.4, 2011.

.. Ch, L. Deledalle, F. Denis, and . Tupin, NL-InSAR: Nonlocal interferogram estimation, IEEE Transactions on Geoscience and Remote Sensing, 2011.

G. Baier, C. Rossi, M. Lachaise, X. X. Zhu, and R. Bamler, Nonlocal InSAR Filter for High-Resolution DEM Generation from TanDEM-X Interferograms, 2018.

F. Sica, D. Cozzolino, X. X. Zhu, L. Verdoliva, and G. Poggi, InSAR-BM3D: A Nonlocal Filter for SAR Interferometric Phase Restoration, IEEE Transactions on Geoscience and Remote Sensing, 2018.

G. Ferraioli, .. Ch, L. Deledalle, F. Denis, and . Tupin, PARISAR: Patch-based estimation and regularized inversion for multi-baseline SAR interferometry, IEEE Transactions on Geoscience and Remote Sensing, vol.56, issue.3, pp.1626-1636, 2018.
URL : https://hal.archives-ouvertes.fr/ujm-01525973

H. Aghababaee, G. Ferraioli, G. Schirinzi, and M. Sahebi, The role of nonlocal estimation in sar tomographic imaging of volumetric media, IEEE Geoscience and Remote Sensing Letters, pp.1-5, 2018.

Y. Shi, X. X. Zhu, and R. Bamler, Nonlocal Compressive Sensing Based SAR Tomography, 2018.

O. Hondt, C. Lopez-martinez, S. Guillaso, and O. Hellwich, Non-Local Filtering Applied to 3D Reconstruction of Tomographic SAR Data, IEEE Transactions on Geoscience and Remote Sensing, 2018.

J. Chen, Y. Chen, W. An, Y. Cui, and J. Yang, Nonlocal filtering for polarimetric SAR data: A pretest approach, IEEE Trans. Geosci. Remote Sens, vol.49, issue.5, 2011.

L. Torres, S. J. Sant'anna, C. Da-costa-freitas, and A. C. Frery, Speckle reduction in polarimetric SAR imagery with stochastic distances and nonlocal means, Pattern Recognition, 2013.

G. Liu and H. Zhong, Nonlocal Means Filter for Polarimetric SAR Data Despeckling Based on Discriminative Similarity Measure, IEEE Geosci. Remote Sens. Lett, issue.99, 2013.

P. Shen, C. Wang, H. Gao, and J. Zhu, An Adaptive Nonlocal Mean Filter for PolSAR Data with Shape-Adaptive Patches Matching, Sensors, 2018.

X. Su, .. Ch, F. Deledalle, H. Tupin, and . Sun, Two-Step Multitemporal Nonlocal Means for Synthetic Aperture Radar Images, IEEE Transactions on Geoscience and Remote Sensing, 2014.

G. Chierchia, D. Cozzolino, G. Poggi, and L. Verdoliva, SAR image despeckling through convolutional neural networks, Geoscience and Remote Sensing Symposium (IGARSS, pp.5438-5441, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01710036

W. Zhao, C. Deledalle, L. Denis, H. Maitre, J. Nicolas et al., Ratio-based multi-temporal SAR images denoising, IEEE Transactions on Geoscience and Remote Sensing, 2018.

.. Ch, L. Deledalle, S. Denis, F. Tabti, and . Tupin, MuLoG, or How to apply Gaussian denoisers to multi-channel SAR speckle reduction?, IEEE Transactions on Image Processing, vol.26, issue.9, pp.4389-4403, 2017.

S. Vitale, D. Cozzolino, G. Scarpa, L. Verdoliva, and G. Poggi, Guided patch-wise non-local SAR despeckling, 2019.

R. Abergel, L. Denis, S. Ladjal, and F. Tupin, Subpixellic methods for sidelobes suppression and strong targets extraction in single look complex SAR images, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.11, issue.3, pp.759-776, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01570857

R. Abergel, L. Denis, F. Tupin, C. A. Deledalle, S. Ladjal et al., Resolution-preserving speckle reduction of SAR images: The benefits of speckle decorrelation and target extraction, IEEE, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02288071

P. Wang, H. Zhang, and . Patel, SAR image despeckling using a convolutional neural network, IEEE Signal Processing Letters, vol.24, issue.12, pp.1763-1767, 2017.

C. Cruz, A. Foi, V. Katkovnik, and K. Egazarian, Nonlocality reinforced convolutional neural networks for image denoising, 2018.

L. Denis, C. A. , and F. Tupin, From patches to deep learning: combining self-similarity and neural networks for SAR image despeckling, IEEE IGARSS (submitted), 2019.