Improved image denoising with adaptive nonlocal means (ANL-means) algorithm

IEEE Transactions on Consumer Electronics

Volumn 56, Issue 4, 2010, Pages 2623-2630

  Thaipanich, Tanaphol ^a   Oh, Byung Tae ^a   Wu, Ping Hao ^a   Xu, Daru ^a   Kuo, C C Jay ^a  

^a University of Southern California   (United States)

Author keywords

Adaptive nonlocal means; ANL means; AWGN; Image denoising; NL means; Nonlocal means

Indexed keywords

ANL-MEANS; AWGN; IMAGE DE-NOISING; NL-MEANS; NONLOCAL;

ALGORITHMS; BENCHMARKING; GAUSSIAN NOISE (ELECTRONIC); IMAGE PROCESSING; LAPLACE EQUATION; MATHEMATICAL OPERATORS; NOISE POLLUTION CONTROL; SINGULAR VALUE DECOMPOSITION; WHITE NOISE;

IMAGE MATCHING;

EID: 78651393914     PISSN: 00983063     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCE.2010.5681149     Document Type: Article

References (28)

1. A. Buades, B. Coll, and J. M. Morel, "A review of image denoising algorithms, with a new one," Multiscale Modeling and Simulation, vol. 4, no. 2, pp. 490-530, 2005.
2. M. C. Motwani, M. C. Gadiya, C. Rakhi, R. C. Motwani, and F. C. Harris, "Survey of image denoising techniques," Proc. of GSPx, Santa Clara, CA, USA, 2004.
3. M. Lindenbaum, M. Fischer, and A. M. Bruckstein, "On Gabor's contribution to image-enhancement," Pattern Recognition, vol. 27, pp.1-8, 1994.
4. H. Ibrahim, N.S.P. Kong, and T. F. Ng, "Simple adaptive median filter for the removal of impulse noise from highly corrupted images," IEEE Trans. on Consumer Electronics, Vol. 54, No. 4, pp. 1920-1927, 2005.
5. L. Wenbin, "Efficient removal of impulse noise from digital images," IEEE Trans. on Consumer Electronics, Vol. 52, No. 2, pp. 523-527, 2006.
6. A. Chambolle, "An algorithm for total variation minimization and applications," Journal of Mathmatical Imaging and Vision 20 (1-2): 89-97, 2004.
7. L. Rudin, S. Osher, and E. Fatemi, "Nonlinear total variation based noise removal algorithms," Physica D, 60: pp. 259-268, 1992.
8. S. Ghael, A. M. Sayeed, and R. G. Baraniuk, "Improved wavelet denoising via empirical Wiener filtering," Proc. SPIE, Wavelet Applications in Signal and Image Processing V, vol. 3169, pp. 389-399, Oct 1997.
9. D. L. Donoho, "De-noising by soft-thresholding", IEEE Trans. on Information Theory, vol.41, no.3, pp.613-627, May1995.
10. I. K. Fodor and C. Kamath, "Denoising through wavelet shrinkage: An empirical study", Center for applied science computing Lawrence Livermore National Laboratory, July 27, 2001.
11. J. Romberg, H. Choi, and R. G. Baraniuk, "Bayesian wavelet domain image modeling using hidden Markov models," IEEE Trans. on Image Processing, vol. 10, pp. 1056-1068, July 2001.
12. J. Kim, "Adaptive blocking artifact reduction using wavelet-based block analysis," IEEE Trans. on Consumer Electronics, Vol. 55, No. 2, pp. 933-940, 2008.
13. J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, "Image denoising using scale mixtures of Gaussians in the wavelet domain," IEEE Trans. on Image Processing, vol. 12, no. 11, pp. 1338-1351, 2003.
14. M. Lysaker, A. Lundervold, and X.-C. Taj, "Noise removal using fourthorder partial differential equations with applications to medical magnetic resonance images in space and time," IEEE Trans. on Image Processing, vol. 12, pp. 1579-1590, 2003.
15. A. Buades, B. Coll, and J. M. Morel, "A non local algorithm for image denoising," IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), vol. 2, 2005, pp. 60-65.
16. P. Chatterjee and P. Milanfar, "A generalization of non-local means via kernel regression," Proc. SPIE Conf. on Computational Imaging, San Jose, January 2008.
17. J. Dinesh Peter, V. K. Govindan, and A. T. Mathew, "Robust estimation approach for nonlocal-means denoising based on structurally similar patches," Int. J. Open Problems Compt. Math., vol. 2, no. 2, June 2009.
18. Y. L. Liu, J. Wang, X. Chen, Y. W. Guo, and Q. S. Peng, "A robust and fast non-local means algorithm for image denoising," Journal of Computer Science and Technology, Vol. 23, No. 2, pp. 270-279, 2008.
19. S. C. Tai and S. M. Yang, "A fast method for image noise estimation using Laplacian operator and adaptive edge detection," 3rd Int. Symposium on Communications, Control and Signal Processing, 2008 (ISCCSP 2008), pp. 1077-1081, Mar 2008.
20. R. Vignesh, B. T. Oh, and C.-C. J. Kuo, "Fast non-local means (NLM) computation with probabilistic early termination," IEEE Signal Processing Letters, Vol. 17, No. 3, pp. 277-280, March 2010.
21. J. Wang, Y. Guo, Y. Ying, Y. Liu, and Q. Peng, "Fast non-local algorithm for image denoising", IEEE Int. Conf. on Image Processing, pp. 1429-1432, 2006.
22. C. Kervrann and J. Boulanger, "Optimal spatial adaptation for patchbased image denoising," IEEE Trans. on Image Processing, Vol. 15, No. 10, pp. 2866-2878, 2006.
23. T. Thaipanich and C.-C. J. Kuo, "An adaptive nonlocal means scheme for medical image denoising," SPIE Medical Imaging, San Diego, CA, USA, February 2010.
24. T. Thaipanich, B. T. Oh, P.-H. Wu, and C.-C. J. Kuo, "Adaptive nonlocal means algorithm for image denoising," IEEE Int. Conf. on Consumer Electronics, Las, Vegas, NV, USA, January 2010.
25. D. H. Shin, R. H. Park, S. Yang, and J. H. Jung, "Block-based noise estimation using adaptive Gaussian filtering," IEEE Trans. on Consumer Electronics, Vol. 51, No. 1, pp. 218-226, 2005.
26. A. Bosco, A. Bruna, G. Messina, and G. Spampinato, "Fast method for noise level estimation and integrated noise reduction," IEEE Trans. on Consumer Electronics, Vol. 51 , No. 3, pp. 1028-1033, 2005.
27. S. W. Lee, V. Maik, J. Jang, J. Shin, and J. Paik, "Noise-adaptive spatiotemporal filter for real-time noise removal in low light level images," IEEE Trans. on Consumer Electronics, Vol. 51, No. 2, pp. 648-653, 2005.
28. J. Immerkær, "Fast noise variance estimation," Computer Vision and Image Understanding, Vol. 64, No. 2, pp. 300-302, Sep. 1996.