Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2013, Article ID 197159, 9 pages
http://dx.doi.org/10.1155/2013/197159
Research Article

SAR Image Despeckling with Adaptive Multiscale Products Based on Directionlet Transform

School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China

Received 23 August 2013; Accepted 17 October 2013

Academic Editor: Shuping He

Copyright © 2013 Yixiang Lu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. W. Goodman, “Some fundamental properties of speckle,” Journal of the Optical Society of America, vol. 66, no. 11, pp. 1145–1150, 1976. View at Publisher · View at Google Scholar
  2. V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. 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, no. 2, pp. 157–166, 1982. View at Publisher · View at Google Scholar
  3. D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, “Adaptive noise smoothing filter for images with signal-dependent noise,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 7, no. 2, pp. 165–177, 1985. View at Publisher · View at Google Scholar
  4. J. S. Lee, “Digital image enhancement and noise filtering by use of local statistics,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 2, no. 2, pp. 165–168, 1980. View at Google Scholar · View at Scopus
  5. M. R. Azimi-Sadjadi and S. Bannour, “Two-dimensional adaptive block Kalman filtering of SAR imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 29, no. 5, pp. 742–753, 1991. View at Publisher · View at Google Scholar · View at Scopus
  6. A. Baraldi and F. Parmiggiani, “A refined gamma MAP SAR speckle filter with improved geometrical adaptivity,” IEEE Transactions on Geoscience and Remote Sensing, vol. 33, no. 5, pp. 1245–1257, 1995. View at Publisher · View at Google Scholar · View at Scopus
  7. H. Xie, L. E. Pierce, and F. T. Ulaby, “SAR speckle reduction using wavelet denoising and Markov random field modeling,” IEEE Transactions on Geoscience and Remote Sensing, vol. 40, no. 10, pp. 2196–2212, 2002. View at Publisher · View at Google Scholar · View at Scopus
  8. F. Argenti and L. Alparone, “Speckle removal from SAR images in the undecimated wavelet domain,” IEEE Transactions on Geoscience and Remote Sensing, vol. 40, no. 11, pp. 2363–2374, 2002. View at Publisher · View at Google Scholar · View at Scopus
  9. M. Dai, C. Peng, A. K. Chan, and D. Loguinov, “Bayesian wavelet shrinkage with edge detection for SAR image despeckling,” IEEE Transactions on Geoscience and Remote Sensing, vol. 42, no. 8, pp. 1642–1648, 2004. View at Publisher · View at Google Scholar · View at Scopus
  10. L. Gagnon and A. Jouan, “Speckle filtering of SAR images: a comparative study between complex-wavelet-based and standard filters,” in Wavelet Applications in Signal and Image Processing V, vol. 3169 of Proceedings of the SPIE, pp. 80–91, San Diego, Calif, USA, July, 1997. View at Publisher · View at Google Scholar
  11. Z.-F. Zhou and P.-L. Shui, “Contourlet-based image denoising algorithm using directional windows,” Electronics Letters, vol. 43, no. 2, pp. 92–93, 2007. View at Publisher · View at Google Scholar · View at Scopus
  12. F. Argenti, T. Bianchi, A. Lapini, and L. Alparone, “Simplified MAP despeckling based on Laplacian-Gaussian modeling of undecimated wavelet coefficients,” in Proceedings of the 19th European Signal Processing Conference (EUSIPCO '11), pp. 1140–1144, Barcelona, Spain, Aughust, 2011. View at Publisher · View at Google Scholar
  13. S. He and F. Liu, “Robust peak-to-peak filtering for Markov jump systems,” Signal Processing, vol. 90, no. 2, pp. 513–522, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  14. S. He and F. Liu, “Robust stabilization of stochastic Markovian jumping systems via proportional-integral control,” Signal Processing, vol. 91, no. 11, pp. 2478–2486, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  15. H. Shen, X. Huang, J. Zhou, and Z. Wang, “Global exponential estimates for uncertain Markovian jump neural networks with reaction-diffusion terms,” Nonlinear Dynamics, vol. 69, no. 1-2, pp. 473–486, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  16. Q. Gao, Y. Lu, D. Sun, Z. L. Sun, and D. Zhang, “Directionlet-based denoising of SAR images using a Cauchy model,” Signal Processing, vol. 93, no. 5, pp. 1056–1063, 2013. View at Publisher · View at Google Scholar
  17. C. Oliver and S. Quegan, Understanding Synthetic Aperture Radar Images, SciTech, Raleigh, NC, USA, 2004.
  18. V. Anastassopoulos, G. A. Lampropoulos, A. Drosopoulos, and M. Key, “High resolution radar clutter statistics,” IEEE Transactions on Aerospace and Electronic Systems, vol. 35, no. 1, pp. 43–60, 1999. View at Publisher · View at Google Scholar · View at Scopus
  19. H. H. Arsenault and G. April, “Properties of speckle integrated with a finite aperture and logarithmically transformed,” Journal of the Optical Society of America, vol. 66, no. 11, pp. 1160–1163, 1976. View at Publisher · View at Google Scholar
  20. A. Achim, P. Tsakalides, and A. Bezerianos, “SAR image denoising via Bayesian wavelet shrinkage based on heavy-tailed modeling,” IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 8, pp. 1773–1784, 2003. View at Publisher · View at Google Scholar · View at Scopus
  21. V. Velisavljevic, B. Beferull-Lozano, M. Vetterli, and P. L. Dragotti, “Approximation power of directionlets,” in Proceedings of the IEEE, International Conference on Image Processing, (ICIP '05), vol. 1, pp. 1–741, Genova, Italy, September, 2005. View at Publisher · View at Google Scholar · View at Scopus
  22. V. Velisavljevic, B. Beferull-Lozano, M. Vetterli, and P. L. Dragotti, “Directionlets: anisotropic multidirectional representation with separable filtering,” IEEE Transactions on Image Processing, vol. 15, no. 7, pp. 1916–1933, 2006. View at Publisher · View at Google Scholar · View at Scopus
  23. J. H. Conway and N. J. A. Sloane, Sphere Packings, Lattices and Groups, vol. 290, Springer, New York, NY, USA, 1998.
  24. X. Zhang and X. Jing, “Image denoising in contourlet domain based on a normal inverse Gaussian prior,” Digital Signal Processing, vol. 20, no. 5, pp. 1439–1446, 2010. View at Publisher · View at Google Scholar
  25. S. Mallat and S. Zhong, “Characterization of signals from multiscale edges,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 7, pp. 710–732, 1992. View at Publisher · View at Google Scholar
  26. Y. Meyer, Wavelets and Operators, vol. 37 of Cambridge Studies in Advanced Mathematics, Cambridge University Press, Cambridge, UK, 1993.
  27. P. Bao and L. Zhang, “Noise reduction for magnetic resonance images via adaptive multiscale products thresholding,” IEEE Transactions on Medical Imaging, vol. 22, no. 9, pp. 1089–1099, 2003. View at Publisher · View at Google Scholar · View at Scopus
  28. H.-Y. Gao, “Wavelet shrinkage denoising using the non-negative garrote,” Journal of Computational and Graphical Statistics, vol. 7, no. 4, pp. 469–488, 1998. View at Google Scholar · View at Scopus
  29. M. K. Simon, Probability Distributions Involving Gaussian Random Variables: A Handbook for Engineers, Scientists and Mathematicians, Springer, New York, NY, USA, 2006.
  30. D. Pastor and F.-X. Socheleau, “Robust estimation of noise standard deviation in presence of signals with unknown distributions and occurrences,” IEEE Transactions on Signal Processing, vol. 60, no. 4, pp. 1545–1555, 2012. View at Publisher · View at Google Scholar · View at Scopus
  31. F. Sattar, L. Floreby, G. Salomonsson, and B. Lövström, “Image enhancement based on a nonlinear multiscale method,” IEEE Transactions on Image Processing, vol. 6, no. 6, pp. 888–895, 1997. View at Publisher · View at Google Scholar · View at Scopus
  32. M. Walessa and M. Datcu, “Model-based despeckling and information extraction from SAR images,” IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 5, pp. 2258–2269, 2000. View at Publisher · View at Google Scholar · View at Scopus