Image denoising with Gaussian mixture model

Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008

Volumn 3, Issue , 2008, Pages 339-343

  Cao, Yang ^a   Luo, Yupin ^a   Yang, Shiyuan ^a  

^a TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CANNING; CLUSTER ANALYSIS; COMMUNICATION CHANNELS (INFORMATION THEORY); ERROR ANALYSIS; ESTIMATION; FOOD ADDITIVES; IMAGE PROCESSING; IMAGE SEGMENTATION; MAGNETOSTRICTIVE DEVICES; OBJECT RECOGNITION; RANDOM VARIABLES; SIGNAL PROCESSING; TRELLIS CODES;

DISTRIBUTION PARAMETERS; EXPECTATION-MAXIMIZATION; GAUSSIAN MIXTURE MODEL; IMAGE DE-NOISING; IMAGE PATCHES; IMAGE SIGNALS; INTERNATIONAL CONGRESSES; MINIMUM MEAN-SQUARE ERROR ESTIMATION;

PARAMETER ESTIMATION;

EID: 52149095652     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CISP.2008.312     Document Type: Conference Paper

References (8)

1. A. Buades, B. Coll, and J.-M. Morel. A non-local algorithm for image denoising. volume II of IEEE CVPR, pages 60-65, San Diego, CA, United States, 2005. Institute of Electrical and Electronics Engineers Computer Society, Piscataway, NJ 08855-1331, United States.
2. T. Chan, S. Esedoglu, F. Park, and A. Yip. Recent developments in total variation image restoration. In N. Paragios, Y. Chen, and O. Faugeras, editors, Mathematical Models in Computer Vision: The Handbook. Springer Verlag, 2005.
3. A. Elmzoughi, A. Benazza-Benyahia, and J. Pesquet. An interscale multivariate statistical model for map multicomponent image denoising in the wavelet transform domain. In Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on, volume 2, pages 45-48, 2005.
4. A. B. Hamza, H. Krim, and G. B. Unal. Unifying probabilistic and variational estimation. Signal Processing Magazine, IEEE, 19(5):37, 2002. 1053-5888.
5. Z. Lei, P. Bao, and W. Xiaolin. Multiscale lmmse-based image denoising with optimal wavelet selection. Circuits and Systems for Video Technology, IEEE Transactions on, 15(4):469-481, 2005.
6. D. D. Muresan and T. W. Parks. Adaptive principal components and image denoising. volume 1 of IEEE International Conference on Image Processing, pages 101-104, Barcelona, Spain, 2003. Institute of Electrical and Electronics Engineers Computer Society.
7. L. I. Rudin, S. Osher, and E. Fatemi. Nonlinear total variation based noise removal algorithms. Physica D: Nonlinear Phenomena, 60(1-4):259, 1992.
8. T. Weissman, E. Ordentlich, G. Seroussi, S. Verdu, and M. J. Weinberger. Universal discrete denoising: known channel. Information Theory, IEEE Transactions on, 51(1):5-28, 2005.