Commenced in January 2007
Paper Count: 30184
Denoising based on Wavelets and Deblurring via Self-Organizing Map for Synthetic Aperture Radar Images
Authors: Mario Mastriani
Abstract:This work deals with unsupervised image deblurring. We present a new deblurring procedure on images provided by lowresolution synthetic aperture radar (SAR) or simply by multimedia in presence of multiplicative (speckle) or additive noise, respectively. The method we propose is defined as a two-step process. First, we use an original technique for noise reduction in wavelet domain. Then, the learning of a Kohonen self-organizing map (SOM) is performed directly on the denoised image to take out it the blur. This technique has been successfully applied to real SAR images, and the simulation results are presented to demonstrate the effectiveness of the proposed algorithms.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1059729Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1366
 H. C. Andrews and B. R. Hunt, Digital Image Restoration. New York: Prentice-Hall, 1977.
 H.S. Tan. (2001, October). Denoising of Noise Speckle in Radar Image.
[Online]. Available: http://innovexpo.itee.uq.edu.au/2001/projects/s804294/thesis.pdf
 H. Guo, J.E. Odegard, M. Lang, R.A. Gopinath, I. Selesnick, and C.S. Burrus, "Speckle reduction via wavelet shrinkage with application to SAR based ATD/R," Technical Report CML TR94-02, CML, Rice University, Houston, 1994.
 D.L. Donoho and I.M. Johnstone, "Adapting to unknown smoothness via wavelet shrinkage," Journal of the American Statistical Association, vol. 90, no. 432, pp. 1200-1224, 1995.
 S.G. Chang, B. Yu, and M. Vetterli, "Adaptive wavelet thresholding for image denoising and compression," IEEE Transactions on Image Processing, vol. 9, no. 9, pp.1532-1546, September 2000.
 F. Argenti and L. Alparone, "Speckle removal from SAR images in the undecimated wavelet domain," IEEE Trans. Geosci. Remote Sensing, vol. 40, pp. 2363-2374, Nov. 2002.
 L. Sendur and I. W. Selesnick, "Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency," IEEE Trans. Signal Processing, vol. 50, pp. 2744-2756, Nov. 2002.
 L. Sendur and I. W. Selesnick, "Bivariate shrinkage with local variance estimation," IEEE Signal Processing Letters, vol. 9, pp. 438-441, Dec. 2002.
 L. Sendur and I. W. Selesnick, "A bivariate shrinkage function for wavelet-based denoising," in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing (ICASSP), Orlando, May 13-17, 2002.
 K.C. Yao, M. Mignotte, C. Collet, P. Galerne, G. Burel, "Unsupervised segmentation using a self-organizing map and a noise model estimation in sonar imagery," Pattern Recognition, 33, pp.1575-1584, 2000.
 R. Nakagaki, and A.K. Katsaggelos, "A VQ-Based Blind Image Restoration Algorithm," IEEE Trans. on Image Process., vol. 12, No. 9, Sept. 2003.
 J.K. Paik, and A.K. Katsaggelos, "Image Restoration Using a Modified Hopfield Network," IEEE Trans. on Image Process., vol. 1, No. 1, Jan. 1992.
 M. Mastriani y A. Giraldez, "Smoothing of coefficients in wavelet domain for speckle reduction in Synthetic Aperture Radar images," ICGST International Journal on Graphics, Vision and Image Processing (GVIP), Volume 6, 2005. Online available: http://www.icgst.com/gvip/v6/P1150517003.pdf
 Y. Yu, and S.T. Acton, "Speckle Reducing Anisotropic Diffusion," IEEE Trans. on Image Processing, vol. 11, no. 11, pp.1260-1270, 2002.
 H. Xie, L. E. Pierce, and F. T. Ulaby, "Statistical properties of logarithmically transformed speckle," IEEE Trans. Geosci. Remote Sensing, vol. 40, pp. 721-727, Mar. 2002.
 J. W. Goodman, "Some fundamental properties of speckle," Journal Optics Society of America, 66:1145-1150, 1976.
 D. Field, "Relations between the statistics of natural images and the response properties of cortical cells," J. Opt. Soc. Amer. A, vol. 4, no. 12, pp. 2379-2394, 1987.
 E. Simoncelli, "Statistical models for images: Compression, restoration and synthesis," in Proc. 31st Asilomar Conf. Signals, Syst., Comput., Nov. 1997, pp. 673-678.
 V. Strela, J. Portilla, and E. Simoncelli, "Image denoising using a local Gaussian scale mixture model in the wavelet domain," in Proc. SPIE 45th Annu. Meet., 2000.
 J. R. Sveinsson and J. A. Benediktsson, "Speckle reduction and enhancement of SAR images in the wavelet domain," in Proc. of Geoscience and Remote Sensing Symposium IGARSS '96, vol.1, pp.63-66, May 1996.
 A. K. Jain, "Fundamentals of Digital Image Processing", Englewood Cliffs, NJ, 1989.
 M. Mastriani and A. Giraldez, "Enhanced Directional Smoothing Algorithm for Edge-Preserving Smoothing of Synthetic-Aperture Radar Images," Journal of Measurement Science Review, vol 4, no. 3, pp.1-11, 2004.
 T. Kohonen, Self Organizing Maps, Springer, Berlin, 1995.
 A. K. Katsaggelos, Ed., "Springer series in information sciences," in Digital Image Restoration. Heidelberg, Germany: Springer-Verlag, 1991, vol. 23.
 M. R. Banham and A. K. Katsaggelos, "Digital image restoration," IEEE Signal Processing Mag., vol. 14, pp. 24-41, Mar. 1997.
 M. Effros, P. A. Chou, and R. M. Gray, "Weighted universal image compression," IEEE Trans. Image Processing, vol. 8, pp. 1317- 1329, Oct. 1999.
 A. K. Katsaggelos, J. Biemond, R.W. Schafer, and R. M. Mersereau, "A regularized iterative image restoration algorithm," IEEE Trans. Acoust, Speech, Signal Processing, vol. 5, pp. 619-634, Apr. 1996.