A. Buades, B. Coll, and J. M. , A Review of Image Denoising Algorithms, with a New One, Multiscale Modeling & Simulation, vol.4, issue.2, pp.490-530, 2005.
DOI : 10.1137/040616024

URL : https://hal.archives-ouvertes.fr/hal-00271141

S. P. Awate and R. T. Whitaker, Unsupervised, information-theoretic, adaptive image filtering for image restoration, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.3, pp.364-376, 2006.
DOI : 10.1109/TPAMI.2006.64

C. Kervrann, J. Boulanger, and P. Coupé, Bayesian Non-local Means Filter, Image Redundancy and Adaptive Dictionaries for Noise Removal, Proc. Conf. Scale-Space and Variational Meth. (SSVM' 07), pp.520-532, 2007.
DOI : 10.1007/978-3-540-72823-8_45

URL : https://hal.archives-ouvertes.fr/hal-00645444

T. Loupas, W. Mcdicken, and P. Allan, An adaptive weighted median filter for speckle suppression in medical ultrasonic images, IEEE Transactions on Circuits and Systems, vol.36, issue.1, pp.129-135, 1989.
DOI : 10.1109/31.16577

J. S. Lee, Digital Image Enhancement and Noise Filtering by Use of Local Statistics, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.2, issue.2, pp.165-168, 1980.
DOI : 10.1109/TPAMI.1980.4766994

V. Frost, J. Stiles, K. Shanmugan, and J. Holtzman, A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.4, issue.2, pp.157-65, 1982.
DOI : 10.1109/TPAMI.1982.4767223

D. Kuan, A. Sawchuck, T. Strand, and P. Chavel, Adaptive Noise Smoothing Filter for Images with Signal-Dependent Noise, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.7, issue.2, pp.165-177, 1985.
DOI : 10.1109/TPAMI.1985.4767641

A. Lopes, R. Touzi, and E. Nezry, Adaptive speckle filters and scene heterogeneity, IEEE Transactions on Geoscience and Remote Sensing, vol.28, issue.6, pp.992-1000, 1990.
DOI : 10.1109/36.62623

M. Karaman, M. A. Kutay, and G. Bozdagi, An adaptive speckle suppression filter for medical ultrasonic imaging, IEEE Transactions on Medical Imaging, vol.14, issue.2, pp.283-292, 1995.
DOI : 10.1109/42.387710

E. Kofidis, S. Theodoridis, C. Kotropoulos, and I. Pitas, Nonlinear adaptive filters for speckle suppression in ultrasonic images, Signal Processing, vol.52, issue.3, pp.357-72, 1996.
DOI : 10.1016/0165-1684(96)00070-9

J. M. Park, W. J. Song, and W. A. Pearlman, Speckle filtering of SAR images based on adaptive windowing, IEE Proceedings - Vision, Image, and Signal Processing, vol.146, issue.4, pp.191-197, 1999.
DOI : 10.1049/ip-vis:19990550

P. C. Tay, S. T. Acton, and J. A. Hossack, A Stochastic Approach to Ultrasound Despeckling, 3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006., pp.221-224, 2006.
DOI : 10.1109/ISBI.2006.1624892

T. C. Aysal and K. E. Barner, Rayleigh-Maximum-Likelihood Filtering for Speckle Reduction of Ultrasound Images, IEEE Transactions on Medical Imaging, vol.26, issue.5, pp.712-727, 2007.
DOI : 10.1109/TMI.2007.895484

P. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.12, issue.7, pp.629-639, 1990.
DOI : 10.1109/34.56205

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

L. Rudin, S. Osher, and E. Fatemi, Nonlinear total variation based noise removal algorithms, Physica D: Nonlinear Phenomena, vol.60, issue.1-4, pp.259-268, 1992.
DOI : 10.1016/0167-2789(92)90242-F

Y. Yu and S. T. Acton, Speckle reducing anisotropic diffusion, IEEE Transactions on Image Processing, vol.11, issue.11, pp.1260-1270, 2002.

Y. Yu, J. A. Molloy, and S. T. Acton, Three-dimensional speckle reducing anisotropic diffusion, Signals, Systems and Computers Conference Record of the Thirty-Seventh Asilomar Conference on, p.1987, 1991.

K. Z. Abd-elmoniem, A. B. Youssef, and Y. M. Kadah, Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion, IEEE Transactions on Biomedical Engineering, vol.49, issue.9, pp.997-1014, 2002.
DOI : 10.1109/TBME.2002.1028423

K. Krissian, C. F. Westin, R. Kikinis, and K. G. Vosburgh, Oriented Speckle Reducing Anisotropic Diffusion, IEEE Transactions on Image Processing, vol.16, issue.5, pp.1412-1424, 2007.
DOI : 10.1109/TIP.2007.891803

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

C. Sheng, Y. Xin, Y. Liping, and S. Kun, Total Variation-Based Speckle Reduction Using Multi-grid Algorithm for Ultrasound Images, ICIAP: international conference on image analysis and processing, pp.245-252, 2005.
DOI : 10.1007/11553595_30

D. Donoho and I. Johnstone, Ideal spatial adaptation by wavelet shrinkage, Biometrika, vol.81, issue.3, pp.425-455, 1994.
DOI : 10.1093/biomet/81.3.425

D. Donoho, De-noising by soft-thresholding, IEEE Transactions on Information Theory, vol.41, issue.3, pp.613-627, 1995.
DOI : 10.1109/18.382009

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

R. Coifman and D. Donoho, Translation-Invariant De-Noising, Lecture Notes in Statistics: Wavelets and Statistics, pp.125-150, 1995.
DOI : 10.1007/978-1-4612-2544-7_9

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

J. E. Odegard, H. Guo, M. Lang, C. S. Burrus, R. O. Wells et al., Wavelet based SAR speckle reduction and image compression, SPIE Proc. on Algorithms for Synthetic Aperture, pp.259-271, 1995.
DOI : 10.1117/12.210843

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

L. Gagnon and D. F. Smaili, <title>Speckle noise reduction of airborne SAR images with symmetric Daubechies wavelets</title>, Signal and Data Processing of Small Targets 1996, pp.14-24, 1996.
DOI : 10.1117/12.241168

X. Zong, A. F. Laine, and E. A. Geiser, Speckle reduction and contrast enhancement of echocardiograms via multiscale nonlinear processing, IEEE Transactions on Medical Imaging, vol.17, issue.4, pp.532-540, 1998.
DOI : 10.1109/42.730398

A. Pizurica, A. M. Wink, E. Vansteenkiste, W. Philips, and J. Roerdink, A Review of Wavelet Denoising in MRI and Ultrasound Brain Imaging, Current Medical Imaging Reviews, vol.2, issue.2, pp.247-260, 2006.
DOI : 10.2174/157340506776930665

A. Achim, A. Bezerianos, P. Tsakalides, S. Foucher, G. B. Benie et al., Novel Bayesian multiscale method for speckle removal in medical ultrasound images, IEEE Transactions on Medical Imaging, vol.20, issue.8, pp.772-783, 2001.
DOI : 10.1109/42.938245

S. Gupta, R. C. Chauhan, and S. C. Saxena, Locally adaptive wavelet domain Bayesian processor for denoising medical ultrasound images using Speckle modelling based on Rayleigh distribution, IEE Proceedings - Vision, Image, and Signal Processing, vol.152, issue.1, pp.129-135, 2005.
DOI : 10.1049/ip-vis:20050975

M. I. Bhuiyan, M. N. Omair, and . Swamy, New Spatially Adaptive Wavelet-based Method for the Despeckling of Medical Ultrasound Images, 2007 IEEE International Symposium on Circuits and Systems, pp.2347-2350, 2007.
DOI : 10.1109/ISCAS.2007.378859

Z. Yang and M. D. Fox, Speckle Reduction and Structure Enhancement by Multichannel Median Boosted Anisotropic Diffusion, EURASIP Journal on Advances in Signal Processing, vol.2004, issue.16, pp.2492-2502, 2004.
DOI : 10.1155/S1110865704402091

URL : http://doi.org/10.1155/s1110865704402091

O. Acosta, H. Frimmel, A. Fenster, and S. Ourselin, FILTERING AND RESTORATION OF STRUCTURES IN 3D ULTRASOUND IMAGES, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.888-891, 2007.
DOI : 10.1109/ISBI.2007.356995

F. Zhang, Y. M. Yoo, L. M. Koh, and Y. Kim, Nonlinear Diffusion in Laplacian Pyramid Domain for Ultrasonic Speckle Reduction, IEEE Transactions on Medical Imaging, vol.26, issue.2, pp.200-211, 2007.
DOI : 10.1109/TMI.2006.889735

B. Aiazzi, L. Alparone, and S. Baronti, Multiresolution local-statistics speckle filtering based on a ratio Laplacian pyramid, IEEE Transactions on Geoscience and Remote Sensing, vol.36, issue.5, pp.1466-1476, 1998.
DOI : 10.1109/36.718850

X. Hao, S. Gao, and X. Gao, A novel multiscale nonlinear thresholding method for ultrasonic speckle suppressing, IEEE Transactions on Medical Imaging, vol.18, issue.9, pp.787-794, 1999.

A. Ogier, P. Hellier, and C. Barillot, Restoration of 3D medical images with total variation scheme on wavelet domains (TVW), Medical Imaging 2006: Image Processing, 2006.
DOI : 10.1117/12.651235

URL : https://hal.archives-ouvertes.fr/inria-00001159

M. Elad, On the origin of the bilateral filter and ways to improve it, IEEE Transactions on Image Processing, vol.11, issue.10, pp.1141-1151, 2002.
DOI : 10.1109/TIP.2002.801126

C. Kervrann and J. Boulanger, Optimal Spatial Adaptation for Patch-Based Image Denoising, IEEE Transactions on Image Processing, vol.15, issue.10, 2006.
DOI : 10.1109/TIP.2006.877529

S. Kindermann, S. Osher, and P. W. Jones, Deblurring and Denoising of Images by Nonlocal Functionals, Multiscale Modeling & Simulation, vol.4, issue.4, pp.1091-1115, 2005.
DOI : 10.1137/050622249

H. Q. Luong, A. Ledda, and W. Philips, Non-Local Image Interpolation, 2006 International Conference on Image Processing, pp.693-696, 2006.
DOI : 10.1109/ICIP.2006.312429

T. Brox and D. Cremers, Iterated Nonlocal Means for Texture Restoration, Proc. International Conference on Scale Space and Variational Methods in Computer Vision, ser, 2007.
DOI : 10.1007/978-3-540-72823-8_2

C. Kervrann and J. Boulanger, Local Adaptivity to Variable Smoothness for Exemplar-Based Image Regularization and Representation, International Journal of Computer Vision, vol.27, issue.2, pp.11263-11270, 2008.
DOI : 10.1007/s11263-007-0096-2

P. Coupé, P. Yger, S. Prima, P. Hellier, C. Kervrann et al., An Optimized Blockwise Nonlocal Means Denoising Filter for 3-D Magnetic Resonance Images, IEEE Transactions on Medical Imaging, vol.27, issue.4, pp.425-441, 2008.
DOI : 10.1109/TMI.2007.906087

Z. Tao, H. D. Tagare, and J. D. Beaty, Evaluation of four probability distribution models for speckle in clinical cardiac ultrasound images, IEEE Transactions on Medical Imaging, vol.25, issue.11, pp.1483-1491, 2006.

G. Slabaugh, G. Unal, T. Fang, and M. Wels, Ultrasound-Specific Segmentation via Decorrelation and Statistical Region-Based Active Contours, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), pp.45-53, 2006.
DOI : 10.1109/CVPR.2006.318

URL : http://openaccess.city.ac.uk/6079/1/Ultrasound%20specific.pdf

K. Krissian, K. Vosburgh, R. Kikinis, and C. Westin, Speckle-constrained anisotropic diffusion for ultrasound images, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005.

F. Argenti and G. Torricelli, Speckle Suppression in Ultrasonic Images Based on Undecimated Wavelets, EURASIP Journal on Advances in Signal Processing, vol.2003, issue.5, pp.470-478, 2003.
DOI : 10.1155/S1110865703211136

M. P. Wachowiak, A. S. Elmaghraby, R. Smolíkova, and J. M. Zurada, Classification and estimation of ultrasound speckle noise with neural networks, Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering, pp.245-252, 2000.
DOI : 10.1109/BIBE.2000.889614

D. Sakrison, On the Role of the Observer and a Distortion Measure in Image Transmission, IEEE Transactions on Communications, vol.25, issue.11, pp.1251-1267, 1977.
DOI : 10.1109/TCOM.1977.1093773

J. A. Jensen, Field: A program for simulating ultrasound systems, Medical & Biological Engineering & Computing, vol.34, pp.351-353, 1996.

P. Coupé, P. Hellier, X. Morandi, and C. Barillot, Probe trajectory interpolation for 3D reconstruction of freehand ultrasound, Medical Image Analysis, vol.11, issue.6, pp.604-615, 2007.
DOI : 10.1016/j.media.2007.05.002

F. Godtliebsen, E. Spjotvoll, and J. S. Marron, A nonlinear gaussian filter applied to images with discontinuities, Journal of Nonparametric Statistics, vol.10, issue.1, pp.21-43, 1997.
DOI : 10.2307/2288922