Adaptive Noise Variance Estimation in BayesShrink

IEEE Signal Processing Letters

Volumn 17, Issue 1, 2010, Pages 12-15

  Hashemi, Masoud ^a   Beheshti, Soosan ^a  

^a RYERSON UNIVERSITY   (Canada)

Author keywords

BayesShrink image denoising; Median Absolute Deviation (MAD); noise variance estimation

Indexed keywords

EID: 85008010158     PISSN: 10709908     EISSN: 15582361     Source Type: Journal    
DOI: 10.1109/LSP.2009.2030856     Document Type: Article

References (14)

1. J. Chen, J. Benesty, Y. Huang, and S. Doclo, “New insights into the noise reduction Wiener filter,” IEEE Trans. Audio, Speech, Lang. Process., vol. 14, no. 4, pp. 1218–1234, Jul. 2006.
2. S. G. Chang, B. Yu, and M. Vetterli, “Adaptive wavelet thresholding for image denoising and compression,” IEEE Trans. Image Process., vol. 9, no. 9, pp. 1532–1546, Sep. 2000.
3. S. G. Chang, Y. Bin, and M. Vetterli, “Spatially adaptive wavelet thresholding with context modeling for image denoising,” IEEE Trans. Image Process., vol. 9, no. 9, pp. 1522–1531, Sept. 2000.
4. D. L. Donoho and I. M. Johnstone “Ideal spatial adaption via wavelet shrinkage,” Biometrika, vol. 81, pp. 425–455, 1994.
5. D. L. Donoho and I. M. Johnstone “Adapting to unknown smoothness via wavelet shrinkage,” J. Amer. Statist. Assoc., vol. 90, pp. 1200–1224, 1995.
6. J. Han and L. Xu, “A new method for variance estimation of white noise corrupting a signal,” in Instrumentation and Measurement Technology Conf., 2006 IMTC 2006, Apr. 2006, pp. 1447–1451.
7. S. Beheshti and M. A. Dahleh, “A new information-theoretic approach to signal denoising and best basis selection,” IEEE Trans. Signal Processing, vol. 53, no. 10, pp. 3613–3624, Oct. 2005.
8. B. Jiang, W. Wang, and X. Gao, “Polynomial-based noise variance estimation for MIMO-SCBT systems,” IEEE Signal Process. Lett., vol. 16, no. 6, pp. 497–500, June 2009.
9. D. Makovoz, “Noise variance estimation in signal processing,” in IEEE Int. Symp. Signal Processing and Information Technology, Aug. 2006, pp. 364–369.
10. Y. Rui, M. Li, X. Zhang, L. Tang, and S. Feng, “A noise variance optimization method for 2 x 1-Dimensional Wiener filtered channel estimation,” in IEEE Wireless Communications and Networking Conference, 2007. WCNC 2007, Mar. 2007, pp. 232–236.
11. N. N. Kachouie and P. Fieguth, “A combined Bayesshrinkwavelet-Ridgelet technique for image denoising,” in IEEE Int. Conf. Multimedia and Expo 2006, Jul. 2006, pp. 1917–1920.
12. N. Nezamoddini-Kachouie and P. Fieguth, “A Gabor based technique for image denoising,” in Can. Conf. Electrical and Computer Engineering, May 2005, pp. 980–983.
13. Z. Hou and T. S. Koh, “Wavelet shrinkage prefiltering for Brain tissue segmentation,” in 27th Annu. Int. Conf. Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005, Jan. 2006, pp. 1604–1606.
14. T. Blu and F. Luisier, “The SURE-LET approach to image denoising,” IEEE Trans. Image Process., vol. 16, no. 11, pp. 2778–2786, Nov. 2007.