LMMSE and MAP estimators for reduction of multiplicative noise in the nonsubsampled contourlet domain

Signal Processing

Volumn 89, Issue 10, 2009, Pages 1891-1901

  Argenti, Fabrizio ^a   Bianchi, Tiziano ^a   di Scarfizzi, Giovanni Martucci ^a   Alparone, Luciano ^a  

^a UNIVERSITY OF FLORENCE   (Italy)

Author keywords

Image denoising; MAP filtering; MMSE filtering; Multiplicative noise; Nonsubsampled contourlet transform (NSCT)

Indexed keywords

DE-NOISING; DE-NOISING ALGORITHM; FOURTH ORDER; GENERALIZED GAUSSIAN DISTRIBUTION; IMAGE DENOISING; LINEAR MINIMUM MEAN SQUARE ERRORS; MAP ESTIMATOR; MAXIMUM A POSTERIORI; MMSE FILTERING; MULTI-DIRECTIONAL; MULTIPLICATIVE NOISE; NONSEPARABLE; NONSTATIONARY; NONSUBSAMPLED CONTOURLET; NONSUBSAMPLED CONTOURLET TRANSFORM (NSCT); SIMULATION RESULT; VIABLE SOLUTIONS;

ESTIMATION; IMAGE PROCESSING; PHASE NOISE; SIGNAL RECEIVERS; WAVELET TRANSFORMS;

ALGORITHMS;

EID: 67349287349     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2009.03.028     Document Type: Article

References (31)

1. Tur M., Chin K.C., and Goodman J.W. When is speckle multiplicative?. Appl. Opt. 21 7 (1982) 1157-1159
2. Oliver C., and Quegan S. Understanding Synthetic Aperture Radar Images (1998), Artech House, Boston, MA
3. Touzi R. A review of speckle filtering in the context of estimation theory. IEEE Trans. Geosci. Remote Sensing 40 11 (2002) 2392-2404
4. Burckhardt C.B. Speckle in ultrasound B-mode scans. IEEE Trans. Sonics Ultras SU-25 1 (1978) 1-6
5. Wagner R.F., Smith S.W., Sandrik J.M., and Lopez H. Statistics of speckle in ultrasound B-scans. IEEE Trans. Sonics Ultras SU-30 3 (1983) 156-163
6. Kuan D.T., Sawchuk A.A., Strand T.C., and Chavel P. Adaptive noise smoothing filter for images with signal-dependent noise. IEEE Trans. Pattern Anal. Mach. Intell. 7 2 (1985) 165-177
7. Lopès A., Nezry E., Touzi R., and Laur H. Structure detection and statistical adaptive speckle filtering in SAR images. Int. J. Remote Sensing 14 9 (1993) 1735-1758
8. Walessa M., and Datcu M. Model-based despeckling and information extraction from SAR images. IEEE Trans. Geosci. Remote Sensing 38 5 (2000) 2258-2269
9. Foucher S., Bénié G.B., and Boucher J.-M. Multiscale MAP filtering of SAR images. IEEE Trans. Image Process. 10 1 (2001) 49-60
10. Argenti F., and Alparone L. Speckle removal from SAR images in the undecimated wavelet domain. IEEE Trans. Geosci. Remote Sensing 40 11 (2002) 2363-2374
11. Solbo S., and Eltoft T. Homomorphic wavelet-based statistical despeckling of SAR images. IEEE Trans. Geosci. Remote Sensing 42 4 (2004) 711-721
12. Argenti F., Bianchi T., and Alparone L. Multiresolution MAP despeckling of SAR images based on locally adaptive generalized Gaussian pdf modeling. IEEE Trans. Image Process. 15 11 (2006) 3385-3399
13. Argenti F., Torricelli G., and Alparone L. MMSE filtering of generalised signal-dependent noise in spatial and shift-invariant wavelet domains. Signal Process. 86 8 (2006) 2056-2066
14. Bianchi T., Argenti F., and Alparone L. Segmentation-based MAP despeckling of SAR images in the undecimated wavelet domain. IEEE Trans. Geosci. Remote Sensing 46 9 (2008) 2728-2742
15. Candès E.J., and Donoho D.L. Curvelets-a surprisingly effective nonadaptive representation for objects with edges. In: Cohen A., Rabut C., and Schumaker L. (Eds). Curve and Surface Fitting (1999), Vanderbilt University Press, Nashville, TN
16. Starck J.L., Candès E.J., and Donoho D.L. The curvelet transform for image denoising. IEEE Trans. Image Process. 11 6 (2002) 670-684
17. Do M.N., and Vetterli M. The contourlet transform: an efficient directional multiresolution image representation. IEEE Trans. Image Process. 14 12 (2005) 2091-2106
18. da Cunha A.L., Zhou J., and Do M.N. The nosubsampled contourlet transform: theory, design and applications. IEEE Trans. Image Process. 15 10 (2006) 3089-3101
19. Coifman R., and Donoho D.L. Translation-invariant de-noising. In: Antoniadis A. (Ed). Wavelets and Statistics, Lecture Notes (1995), Springer, Berlin, Heidelberg, New York
20. Po D.D.-Y., and Do M.N. Directional multiscale modeling of images using the contourlet transform. IEEE Trans. Image Process. 15 6 (2006) 1610-1620
21. Foucher S., Farage G., and Benie G.B. SAR image filtering based on the stationary contourlet transform. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (2006) 4021-4024
22. Eslami R., and Radha H. Translation-invariant contourlet transform and its application to image denoising. IEEE Trans. Image Process. 15 11 (2006) 3362-3374
23. Lu Y., and Do M.N. A new contourlet transform with sharp frequency localization. Proceedings of the IEEE International Conference on Image Processing (ICIP), Atlanta, GA (2006) 1629-1632
24. M.N. Do, Directional multiresolution image representations, Ph.D. Thesis, School of Computer and Communication Sciences, Swiss Federal Institute of Technology, Lausanne, Switzerland, 2001.
25. Burt P.J., and Adelson E.H. The Laplacian pyramid as a compact image code. IEEE Trans. Commun. 31 4 (1983) 532-540
26. Bamberger R.H., and Smith M.J.T. A filter bank for the directional decomposition of images: theory and design. IEEE Trans. Signal Process. 40 4 (1992) 882-893
27. Chang S.G., Yu B., and Vetterli M. Adaptive wavelet thresholding for image denoising and compression. IEEE Trans. Image Process. 9 9 (2000) 1532-1546
28. Shui P.-L. Image denoising algorithm via doubly local Wiener filtering with directional windows in wavelet domain. IEEE Signal Process. Lett. 12 10 (2005) 681-684
29. Shensa M.J. The discrete wavelet transform: wedding the à trous and Mallat algorithm. IEEE Trans. Signal Process. 40 10 (1992) 2464-2482
30. USC-SIPI image database. Available at: 〈http://sipi.usc.edu/database〉.
31. Kendall M.G., and Stuart A. The Advanced Theory of Statistics. vol. 1, fourth ed. (1977), Charles Griffin & Co., Ltd., London, UK