Speckle noise reduction

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Speckle noise reduction: a review – Ph. Courmontagne 20 Bibliography [Jean, 2006] F. Jean, SHADOWS, by Ixsea, a real-time Synthetic Aperture Sonar system, Electronic Proceedings of OCEANS 2006 - Asia Pacific, Singapore, May 2006. [Walessa, 2000] M. Walessa and M. Datcu, Model-Based Despeckling and Information Extraction from SAR Images, IEEE Transactions on Geoscience and Remote Sensing, Vol. 38 (2000), No 5, pp. 2258-2269. [Achim, 2005] A. Achim, E. Kuruoglu and J. Zerubia, SAR Image Filtering Based on the Heavy-Tailed Rayleigh Model, Research Report, INRIA, N° 5493, February 2005, FRANCE. [Pitas, 1990] I. Pitas & A.N. Venetsanopoulos, Nonlinear digital filters, Kluwer Academic Publishers, 1990 [Nieminen, 1986] A. Nieminen, P. Heinonen and Y. Neuvo, 2-D Multilevel FIR-median hybrid filters, Acoustics, Speech and Signal Processing, IEEE International Conference on ICASSP’86, 11, 1986. [Lee, 1981] J.S. Lee, Speckle analysis and smoothing of synthetic aperture radar images, Computer graphics and image processing, n. 17, 1981, pp 24-32 [Lee, 1986] J.S. Lee, Speckle suppression and analysis for synthetic aperture radar images, Optical engineering, vol 25 n. 5, 1986, pp 636-643 [Lu, 1996] Y.H. Lu, S.Y. Tan, T.S. Yeo, W.E. Ng, I. Lim and C.B. Zhang, Adaptive Filtering algorithms for SAR speckle reduction, Geoscience and Remote Sensing Symposium, IGARSS’96, 1 , 1996. [Lopes, 1990] A. Lopes, R. Touzi, E. Nezry, Adaptive speckle filters and Scene heterogeneity, IEEE Transaction on Geoscience and Remote Sensing, Vol. 28, No 6, pp. 992-1000, Nov. 1990. [Lee, 1980] J.-S. Lee, Digital image enhancement and noise filtering by use of local statistics, IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-2, pp. 165-168, 1980. [Kuan, 1985] D. T. Kuan, A. A. Sawchuk, T. C. Strand, P. Chavel, Adaptative noise smoothing filter for images with signaldependent noise, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 7, No 2, pp. 165-177, March 1985. [Kuan, 1987] D. T. Kuan, A. A. Sawchuk, T. C. Strand, P. Chavel, Adaptative restoration of images with speckle, IEEE Transactions Acoustic, Speech, Signal Processing, Vol. 35, No 3, pp. 373-383, March 1987.
Speckle noise reduction: a review – Ph. Courmontagne 21 Bibliography [Frost, 1982] V.S. Frost, J.A. Stiles, K.S. Shanmugan, J.C. Holtzman, A model for radar images and its application to adaptive digital filtering of multiplicative noise, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 4, No 2, pp. 157-166, March 1982. [Pomalaza-Raez, 1984] C. A. Pomalaza-Raez et C. D. McGillem, An adaptive non linear edge preserving filter, IEEE Trans. on Acoustics Speech Signal Processing, Vol. 32, No3, pp. 571-576, 1984. [Perona, 1990] P. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion, IEEE Trans. On Pattern Analysis and Machine Intelligence, Vol.12 n.7, 1980, pp 629-639 [Issa, 1996] I. Issa, Ph. Bolon, Adaptative weighted dalpha filter, Proc. EUSIPCO’96, Trieste, Italy, september 1996, pp.1921- 1924 [Courmontagne, 2007] Ph. Courmontagne, SAS images denoising: the jointly use of an autoadaptive mean filter and the stochastic matched filter, Electronic Proceedings of OCEANS’07 Aberdeen, June 2007. [Buades, 2005] A. Buades, B. Coll and J.M. Morel, A non-local algorithm for image denoising, computer Vision and Pattern Recognition, 2, 60-65, 2005 [Holdschneider, 1989] M. Holdschneider, R. Kronland-Martinet, J. Morlet and P. Tchamitchian, A real time algorithm for the Signal Analysis with the help of the wavelet transform, in Wavelets. ed. J.M. Combes et al. Springer-Verlag Berlin, 1989, pp.286-297. [Mallat, 1989] S. Mallat, A Theory for Multiresolution Signal Decomposition: The Wavelet Representation, Proc. IEEE Trans on Pattern Anal. and Math. intel., Vol. 11 (1989), No 7, pp. 674-693. [Donoho, 1993] D.L. Donoho and I.M. Johnstone, Adapting to unknown smoothness via wavelet shrinkage, technical report, Stanford University ([Online] Available: http://www-stat.stanford.edu/_donoho/reports.html), 1993. [Candes, 1998] E.J. Candes, Ridgelets: Theory and Applications, PhD Thesis, Stanford University, 1998 [Starck, 2002] J.L. Starck, E. Candes, and D.L. Donoho, The Curvelet Transform for Image Denoising, IEEE Transactions on Image Processing , 11, 6, pp. 670-684, 2002. [Mallet, 2006] J. Mallet and P. Courmontagne, A new wavelet thresholding approach for SAS images denoising, OCEANS’06, Boston, September 2006.
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