Stochastic image denoising based on Markov-chain Monte Carlo sampling

Signal Processing

Volumn 91, Issue 8, 2011, Pages 2112-2120

  Wong, Alexander ^a   Mishra, Akshaya ^a   Zhang, Wen ^a   Fieguth, Paul ^a   Clausi, David A ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Image denoising; Markov chain Monte Carlo

Indexed keywords

ADDITIVE GAUSSIAN NOISE; BAYESIAN; DE-NOISING; IMAGE DE-NOISING; LEAST SQUARES PROBLEMS; MARKOV-CHAIN MONTE CARLO; MEAN STRUCTURAL SIMILARITY; NOISE STATISTICS; NOISY IMAGE; NON-PARAMETRIC; OBJECTIVE FUNCTIONS; PEAK SIGNAL-TO-NOISE RATIO; STOCHASTIC APPROACH;

COMPUTATIONAL COMPLEXITY; GAUSSIAN NOISE (ELECTRONIC); IMAGE PROCESSING; MONTE CARLO METHODS; SIGNAL TO NOISE RATIO; STOCHASTIC SYSTEMS;

NOISE POLLUTION CONTROL;

EID: 79955484402     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2011.03.021     Document Type: Article

References (31)

1. N. Wiener Extrapolation, Interpolation, and Smoothing of Stationary Time Series 1949 Wiley New York
2. L. Yaroslavsky Local adaptive image restoration and enhancement with the use of DFT and DCT in a running window Proceedings of Wavelet Applications in Signal and Image Processing IV, SPIE Proceedings Series vol. 2825 1996 1 13
3. J. Portilla, V. Strela, M. Wainwright, and E. Simoncelli Image denoising using scale mixtures of Gaussians in the wavelet domain IEEE Transactions on Image Processing 12 11 2003 1338 1351
4. Q. Li, and C. He Application of wavelet threshold to image de-noising Proceedings of Innovative Computing, Information and Control vol. 2 2006 693 696
5. H. Biao, J. Li-cheng, and L. Fang Image denoising based on ridgelet Proceedings of 6th International Conference on Signal Processing vol. 1 2002 780 783
6. F. Luisier, T. Blu, and M. Unser A new SURE approach to image denoising: interscale orthonormal wavelet thresholding IEEE Transactions on Image Processing 16 3 2007 593 606
7. D. Zhou, and W. Cheng Image denoising with an optimal threshold and neigbhouring window Pattern Recognition Letters 29 2008 1694 1697
8. M. Malfait, and D. Roose Wavelet-based image denoising using a Markov random field a priori model IEEE Transactions on Image Processing 6 1997 549 565
9. A. Pizurica, W. Philips, I. Lemahieu, and M. Acheroy A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising IEEE Transactions on Image Processing 11 2002 545 557
10. A. Foi, V. Katkovnik, and K. Egiazarian Pointwise shape-adaptive DCT for high-quality denoising and deblocking of grayscale and color Images IEEE Transactions on Image Processing 16 5 2007 1395 1411
11. M. Lindenbaum, M. Fischer, and A. Bruckstein On Gabor contribution to image-enhancement Pattern Recognition 27 1994 1 8
12. J. Lee Digital image enhancement and noise filtering by use of local statistics IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-2 1980 165 168
13. L. Rudin, and S. Osher Total variation based image restoration with free local constraints Proceedings of IEEE International Conference on Image Processing vol. 1 1994 31 35
14. S. Geman, and D. Geman Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-6 1984 721 741
15. J. Pryce, and A. Bruce Statistical mechanics of image restoration Journal of Physics A: Mathematical and General 28 3 1995 511 532
16. S. Greenberg, and D. Kogan Improved structure-adaptive anisotropic filter Pattern Recognition Letters 27 1 2006 59 65
17. C. Tomasi, and R. Manduchi Bilateral filtering for gray and color images Proceedings of IEEE International Conference on Computer Vision 1998 836 846
18. M. Elad On the origin of the bilateral filter and ways to improve it IEEE Transactions on Image Processing 11 10 2002 1141 1151
19. A. Wong Adaptive bilateral filtering of image signals using local phase characteristics Signal Processing 88 6 2008 1615 1619
20. W. Wong, A. Chung, and S. Yu Trilateral filtering for biomedical images Proceedings of IEEE International Symposium on Biomedical Imaging: Nano to Macro vol. 1 2004 820 823
21. M. Mahmoudi, and G. Sapiro Fast image and video denoising via nonlocal means of similar neighborhoods IEEE Signal Processing Letters 12 12 2005 839 842
22. A. Buades, B. Coll, and J. Morel Nonlocal image and movie denoising International Journal of Computer Vision 76 2 2008 123 139
23. J. Orchard, M. Ebrahimi, and A. Wong Efficient nonlocal-means denoising using the SVD Proceedings of IEEE International Conference on Image Processing 2008
24. K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian Image denoising by sparse 3D transform-domain collaborative filtering IEEE Transactions on Image Processing 16 8 2007 2080 2095
25. P. Fieguth Statistical Image Processing and Multidimensional Modeling first ed. 2010 Springer New York
26. J.S. Lee Speckle suppression and analysis for synthetic aperture radar Optical Engineering 25 5 1986 636 643
27. A.E. Lopes, E. Nezry, R. Touzi, and H. Laur Structure detection and adaptive speckle filtering in SAR images The International Journal of Remote Sensing 14 9 1993 1735 1758
28. W. Hastings Monte carlo sampling methods using Markov chains and their applications Biometrika 57 1 1970 97 109
29. S. Geman, and D. McClure Statistical methods for tomographic image reconstruction Bulletin of the International Statistical Institute LII-4 1987 5 21
30. M. Chen Importance-weighted marginal Bayesian posterior density estimation Journal of the American Statistical Association 89 427 1994 818 824
31. Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli Image quality assessment: from error visibility to structural similarity IEEE Transactions on Image Processing 13 4 2004 600 612