OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Editor: Stephen A. Burns
  • Vol. 23, Iss. 6 — Jun. 1, 2006
  • pp: 1269–1281

Scene estimation from speckled synthetic aperture radar imagery: Markov-random-field approach

Ousseini Lankoande, Majeed M. Hayat, and Balu Santhanam  »View Author Affiliations

JOSA A, Vol. 23, Issue 6, pp. 1269-1281 (2006)

View Full Text Article

Enhanced HTML    Acrobat PDF (1440 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



A novel Markov-random-field model for speckled synthetic aperture radar (SAR) imagery is derived according to the physical, spatial statistical properties of speckle noise in coherent imaging. A convex Gibbs energy function for speckled images is derived and utilized to perform speckle-compensating image estimation. The image estimation is formed by computing the conditional expectation of the noisy image at each pixel given its neighbors, which is further expressed in terms of the derived Gibbs energy function. The efficacy of the proposed technique, in terms of reducing speckle noise while preserving spatial resolution, is studied by using both real and simulated SAR imagery. Using a number of commonly used metrics, the performance of the proposed technique is shown to surpass that of existing speckle-noise-filtering methods such as the Gamma MAP, the modified Lee, and the enhanced Frost.

© 2006 Optical Society of America

OCIS Codes
(030.0030) Coherence and statistical optics : Coherence and statistical optics
(100.0100) Image processing : Image processing
(110.0110) Imaging systems : Imaging systems
(280.0280) Remote sensing and sensors : Remote sensing and sensors

ToC Category:
Atmospheric and Oceanic Optics

Original Manuscript: June 1, 2005
Revised Manuscript: November 21, 2005
Manuscript Accepted: December 18, 2005

Ousseini Lankoande, Majeed M. Hayat, and Balu Santhanam, "Scene estimation from speckled synthetic aperture radar imagery: Markov-random-field approach," J. Opt. Soc. Am. A 23, 1269-1281 (2006)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. G. Franceschetti and R. Lanari, Synthetic Aperture Radar Processing (CRC Press, 1999).
  2. A. Doerry and F. Dickey, "Synthetic aperture radar," Opt. Photon. News, November 2004, pp. 28-33.
  3. F. T. Ulaby, R. K. Moore, and A. K. Fung, Radar Remote Sensing and Surface Scattering and Emission Theory, Vol. 2 of Microwave Remote Sensing: Active and Passive (Addison-Wesley, 1982).
  4. F. Ulaby, F. Kouyate, B. Brisco, and T. Williams, "Texture information in SAR images," IEEE Trans. Geosci. Remote Sens. 24, 235-245 (1986). [CrossRef]
  5. J. Lee, "Speckle analysis and smoothing of synthetic aperture radar images," Comput. Graph. Image Process. 17, 24-32 (1981). [CrossRef]
  6. A. Lopes, R. Touzi, and E. Nezry, "Adaptive speckle filters and scene heterogeneity," IEEE Trans. Geosci. Remote Sens. 28, 992-1000 (1990). [CrossRef]
  7. T. R. Crimmins, "Geometric filter for speckle reduction," Appl. Opt. 24, 1438-1443 (1985). [CrossRef] [PubMed]
  8. D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, "Adaptive noise smoothing filter for images with signal-dependent noise," IEEE Trans. Pattern Anal. Mach. Intell. TPAMI-7, 165-177 (1985). [CrossRef]
  9. 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 Trans. Pattern Anal. Mach. Intell. PAMI-4, 157-165 (1982). [CrossRef]
  10. A. Achim, P. Tsakalides, and A. Bezerianos, "SAR image denoising via Bayesian wavelet shrinkage based on heavy tailed modeling," IEEE Trans. Geosci. Remote Sens. 41, 1773-1784 (2003). [CrossRef]
  11. F. Argenti and L. Alparone, "Speckle removal from SAR images in the undecimated wavelet domain," IEEE Trans. Geosci. Remote Sens. 40, 2363-2374 (2002). [CrossRef]
  12. C. Oliver and S. Quegan, Understanding Synthetic Aperture Radar Images (SciTech, 2004).
  13. H. Xie, L. Pierce, and F. Ulaby, "SAR speckle reduction using wavelet denoising and Markov random field modeling," IEEE Trans. Geosci. Remote Sens. 40, 2196-2212 (2002). [CrossRef]
  14. R. Touzi, "A review of speckle filtering in the context of estimation theory," IEEE Trans. Geosci. Remote Sens. 40, 2392-2404 (2002). [CrossRef]
  15. O. Lankoande, M. M. Hayat, and B. Santhanam, "Speckle reduction of SAR images using a physically based Markov random field model and simulated annealing," in Algorithms for Synthetic Aperture Radar Imagery XII, F.G.Zelnio and F.D.Garber, eds., Proc. SPIE 5808, 210-221 (2005).
  16. O. Lankoande, M. M. Hayat, and B. Santhanam, "Speckle modeling and reduction in synthetic aperture radar imagery," in Proceedings of the IEEE International Conference on Image Processing (IEEE, 2005), Vol. 3, pp. 317-320.
  17. O. Lankoande, M. M. Hayat, and B. Santhanam, "Segmentation of SAR images based on Markov random field model," in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (IEEE, 2005), pp. 2956-2961. [CrossRef]
  18. J. Dainty, Topics in Applied Physics: Laser Speckle and Related Phenomena (Springer-Verlag, 1984).
  19. J. Goodman, Statistical Optics (Wiley-Interscience, 1985).
  20. R. Keys, "Cubic convolution interpolation for digital image processing," IEEE Trans. Acoust. Speech Signal Process. ASSP-29, 1153-1160 (1981). [CrossRef]
  21. S. Quegan, "Interpolation and sampling in SAR images," IEEE Trans. Geosci. Remote Sens. 28, 641-646 (1990). [CrossRef]
  22. J. Besag, "Spatial interaction and the statistical analysis of lattice systems," J. R. Stat. Soc. Ser. B. Methodol. 6, 192-236 (1974).
  23. R. Kinderman and J. Snell, Markov Random Fields and Their Applications (American Mathematical Society,1980). [CrossRef]
  24. M. Tawarmalani and N. V. Sahinidis, "A polyhedral branch-and-cut approach to global optimization," Math. Program. 103, 225-249 (2005). [CrossRef]
  25. C. Maheshwari, A. Neumaier, and H. Schichl, "Convexity and concavity detection," Tech. Rep., Universitat Wien, A-1010 Vienna, Austria (July 2003), http://www.mat.univie.ac.at/~herman/papers.html.
  26. Courtesy of Armin Doerry at Sandia National Laboratories, awdoerr@sandia.gov (personal communication, October 25, 2004).
  27. S. Tsunoda, F. Pace, J. Stence, M. Woodring, W. H. Hensley, A. Doerry, and B. Walker, "Lynx: a high-resolution synthetic aperture radar," in Radar Sensor Technology IV, R.Trebits and J.L.Kurtz, eds., Proc. SPIE 3704, 20-27 (1999).
  28. Courtesy of David G. Long, Brigham Young University, Director of the Center for Remote Sensing, 459 Clyde Building, Provo, Utah 84602, http://www.cers.byu.edu/ (personal communication, October 20, 2005).
  29. Australian Government, "JERS SAR processing levels" (November 2005), http://www.ga.gov.au/acres/prodlowbarser/jerslowbarlev.htm.
  30. Australian Government, "ERS SAR Processing Levels" (November 2005), http://www.ga.gov.au/acres/prodlowbarser/erslowbarlevs.htm.
  31. B. Scheuchl, D. Flett, G. Staples, G. Davidson, and I. Cumming, "Preliminary classification results of simulated RADARSAT-2 polarimetric sea ice data," presented at the Workshop on Applications of SAR Polarimetry and Polarimetric Interferometry, ESA/ESRIN, Frascati, Italy (January 14-16, 2003).
  32. F. Sattar, L. Floreby, G. Salomonsson, and B. Lovstrom, "Image enhancement based on a nonlinear multiscale method," IEEE Trans. Image Process. 6, 888-895 (1997). [CrossRef] [PubMed]
  33. A. Achim, A. Bezerianos, and P. Tsakalides, "Wavelet-based ultrasound image denoising using an alpha-stable prior probability model," in Proceedings of the IEEE International Conference on Image Processing (IEEE, 2001), Vol. 2, pp. 221-224.
  34. S. Gupta, R. C. Chauhan, and S. C. Sexana, "Wavelet-based statistical approach for speckle reduction in medical ultrasound images," Med. Biol. Eng. Comput. 42, 189-192 (2004). [CrossRef] [PubMed]
  35. 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, A.Aldroubi, A.F.Laine, and M.A.Unser, eds., Proc. SPIE 3169, 80-91 (1997).
  36. J. R. Sveinsson and J. A. Benediktsson, "Almost translation invariant wavelet transformations for speckle reduction of SAR images," IEEE Trans. Geosci. Remote Sens. 41, 2404-2408 (2003). [CrossRef]
  37. N. Metropolis, A. Rosenbluth, M. Rosenbluth, A. Teller, and E. Teller, "Equations of state calculations by fast computing machines," J. Chem. Phys. 21, 1087-1092 (1953). [CrossRef]
  38. Carnegie Mellon University, Vision and Autonomous Systems Center's Image Database, "Parks and Roads," (Nov. 2005), http://vasci.ri.cmu.edu//idb/html/stereo/houseof/index.html.
  39. Y. S. Chow and H. Teicher, Probability Theory (Springer-Verlag, 1997). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited