Wavelet domain denoising of single-band and multiband images adapted to the probability of the presence of features of interest

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5914, Issue , 2005, Pages 1-14

  Pižurica, Aleksandra ^a   Philips, Wilfried ^a   Scheunders, Paul ^b  

^a GHENT UNIVERSITY   (Belgium)

^b UNIVERSITY OF ANTWERP   (Belgium)

Author keywords

Bayesian estimation; Color; Multispectral images; Wavelets

Indexed keywords

COLOR; COLOR IMAGE PROCESSING; ESTIMATION; FEATURE EXTRACTION; PROBABILITY; SPURIOUS SIGNAL NOISE;

BAYESIAN ESTIMATION; MULTISPECTRAL IMAGES; WAVELETS;

WAVELET TRANSFORMS;

EID: 30844437485     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.619386     Document Type: Conference Paper

References (36)

1. I. Daubechies, Ten Lectures on Wavelets, Philadelphia: SIAM, 1992.
2. S. Mallat, A wavelet tour of signal processing, Academic Press, London, 1998.
3. M. Malfait and D. Roose, "Wavelet-based image denoising using a Markov random field a priori model," IEEE Trans. Image processing 6, pp. 549-565, Apr. 1997.
4. S. G. Chang, B. Yu, and M. Vetterli, "Spatially adaptive wavelet thresholding with context modeling for image denoising," in Proc. IEEE Internat. Conf. on Image Proc., (Chicago, IL, Oct. 1998.).
5. M. K. Mihçak, I. Kozintsev, K. Ramchandran, and P. Moulin, "Low-complexity image denoising based on statistical modeling of wavelet coefficients," IEEE Signal Proc. Lett. 6, pp. 300-303, Dec. 1999.
6. J. Romberg, H. Choi, and R. Baraniuk, "Bayesian tree structured image modeling using wavelet-domain hidden Markov models," IEEE Trans. Image Processing. 10(7), pp. 1056-1068, 2001.
7. L. Şendur and I. W. Selesnick, "Bivariate shrinkage with local variance estimation," IEEE Signal Proc. Letters 9, pp. 438-441, Dec. 2002.
8. A. Pižurica, W. Philips, I. Lemahieu, and M. Acheroy, "A versatile wavelet domain noise filtration technique for medical imaging," IEEE Trans. Medical Imaging 22, pp. 323-331, Mar. 2003.
9. J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, "Image denoising using Gaussian scale mixtures in the wavelet domain," IEEE Trans. Image Proc. 12, pp. 1338-1351, Nov. 2003.
10. E. J. Candes and D. L. Donoho, "Curvelets - a surprisingly effective nonadaptive representation for objects with edges," in Curves and Surfaces, e. a. L. L. Schumaker, ed., Vanderbilt University Press,Nashville, TN., 1999.
11. J. Starck, E. Candes, and D. Donoho, "The curvelet transform for image denoising," IEEE Trans. Image Proc. 11, pp. 670 -684, June 2002.
12. D. D. Y. Po and M. N. Do, "Directional multiscale modeling of images using the contourlet transform," IEEE Trans. Image Proc., 2005 (in press).
13. E. LePennec and S. Mallat, "Bandelet image approximation and compression," SIAM Journal of Multiscale Modeling and Simulation , 2005 (in press).
14. M. Katona, A. Pižurica, N. Teslić, V. Kovač ević, and W. Philips, "FPGA design and implementation of a wavelet-domain video denoising system," in Proc. Int'l Conf. Advanced Concepts for Intelligent Vision Systems ACIVS'05, (Antwerp, Belgium), Sept. 2005.
15. A. Fletcher, V. Goyal, and K. Ramchardan, "On multivariate estimation by thresholding," in Proc. of the IEEE Internat. Conf. on Image Proc. ICIP, (Barcelona, Spain), Sept. 2003.
16. P. Scheunders, "Wavelet thresholding of multivalued images," IEEE Trans. Image Proc. 13, pp. 475-483, Apr. 2004.
17. P. Scheunders and D. J., "Least squares interband denoising of color and multispectral images," in Proc. IEEE Internat. Conf. Image Proc. ICIP, (24-27 Oct, Singapore, 2004).
18. A. Benazza-Benyahia and J.-C. Pesquet, "Building robust wavelet estimators for multicomponent images using Steins' principle," IEEE Trans. Image Processing, 2005 (in press).
19. A. Pižurica and W. Philips, "Estimating probability of presence of a signal of interest in multiresolution single- and multiband image denoising," IEEE Trans. Image Processing (In press).
20. S. Mallat, "A theory for multiresolution signal decomposition: the wavelet representation," IEEE Trans. Pattern Anal. and Machine Intel. 11(7), pp. 674-693, 1989.
21. E. P. Simoncelli and E. H. Adelson, "Noise removal via Bayesian wavelet coring," in Proc. IEEE Internat. Conf. Image Proc. ICIP, (Lausanne, Switzerland, 1996).
22. M. Hansen and B. Yu, "Wavelet thresholding via MDL for natural images," IEEE Trans. Inform. Theory 46, pp. 1778-1788, Aug. 2000.
23. D. L. Donoho and I. M. Johnstone, "Adapting to unknown smoothness via wavelet shrinkage," J. Amer. Stat. Assoc. 90, pp. 1200-1224, Dec. 1995.
24. H. A. Chipman, E. D. Kolaczyk, and R. E. McCulloch, "Adaptive Bayesian wavelet shrinkage," J. of the Amer. Statist. Assoc 92, pp. 1413-1421, 1997.
25. F. Abramovich, T. Sapatinas, and B. Silverman, "Wavelet thresholding via a Bayesian approach," J. of the Royal Statist. Society B 60, pp. 725-749, 1998.
26. M. Clyde, G. Parmigiani, and B. Vidakovic, "Multiple shrinkage and subset selection in wavelets," Biometrika 85(2), pp. 391-401, 1998.
27. B. Vidakovic, "Wavelet-based nonparametric Bayes methods," in Practical Nonparametric and Semiparametric Bayesian Statistics, D. D. Dey, P. Mülller, and D. Sinha, eds., Lecture Notes in Statistics 133, pp. 133-155, Springer Verlag, New York, 1998.
28. I. Johnstone and B. Silverman, "Empirical Bayes selection of wavelet thresholds," Annals of Statistics 33, 2005 (in press).
29. M. Jansen, Noise Reduction by Wavelet Thresholding, Springer-Verlag, New York, 2001.
30. A. Pižurica, W. Philips, I. Lemahieu, and M. Acheroy, "A joint inter- and intrascale statistical model for wavelet based Bayesian image denoising," IEEE Trans. Image Proc 11, pp. 545-557, May 2002.
31. D. Middleton and R. Esposito, "Simultaneous optimum detection and estimation of signals in noise," IEEE Trans. Inform. Theory 14, pp. 434-443, May 1968.
32. S. G. Chang, B. Yu, and M. Vetterli, "Adaptive wavelet thresholding for image denoising and compression," IEEE Trans. Image Proc. 9, pp. 1532-1546, Sept. 2000.
33. A. Pižurica and W. Philips, "On least squares estimators under Bernoulli-Laplacian priors," Technical Report 09/05, Ghent University, 2005 (available at: http://telin.ugent.be/~sanja).
34. J. Kalifa and S. Mallat, "Minimax restoration and deconvolution," in Bayesian Inference in Wavelet-Based Models, P. Müller and B. Vidakovic, eds., Lecture Notes in Statistics, pp. 115-138, Springer Verlag, 1999.
35. B. Corner, R. Narajanan, and S. Reichenbach, "Noise estimation in remote sensing imagery using data masking," Internat. J. Remote Sensing 24(4), pp. 689-702, 2003.
36. M. Abrams and S. Cain, "Sampling, radiometry and image reconstruction for polar and geostationary meteorological remote sensing systems," in Proc. SPIE, Image Reconstruction from Incomplete Data II, P. Bone, M. Fiddy, and R. Milane, eds., 4792, pp. 207-215.