Image Denoising Using Wavelets: Application in Medical Imaging - Advances in Heuristic Signal Processing and Applications - page 307

13. Donoho, D.L., Johnstone, I.M.: Ideal spatial adaptation by wavelet shrinkage. Biometrika 81 ,
425-455 (1994)
14. Chesneau, C., Fadili, M.J., Starck, J.L.: Stein block thresholding for image denoising. Appl.
Comput. Harmon. Anal. 28 , 67-88 (2009)
15. Dupe, F.X., Fadili, M.J., Starck, J.L.: A proximal iteration for deconvolving Poisson noisy
images using sparse representations. IEEE Trans. Image Process. 18 , 310-321 (2009)
16. Atto, A.M., Pastor, D., Mercier, G.: Smooth sigmoid wavelet shrinkage for non-parametric
estimation. In: IEEE International Conference on Acoustics, Speech, and Signal Processing,
Las Vegas (2008)
17. Pizurica, A., Philips, W.: Estimating the probability of the presence of a signal of interest
in multiresolution single- and multiband image denoising. IEEE Trans. Image Process. 15 ,
654-665 (2006)
18. Goossens, B., Pizurica, A., Philips, W.: Removal of correlated noise by modeling the signal of
interest in the wavelet domain. IEEE Trans. Image Process. 18 , 1153-1165 (2009)
19. Bartusek, K., Prinosil, J., Smekal, Z.: Wavelet-based de-noising techniques in MRI. Comput.
Methods Programs Biomed. 104 , 480-488 (2011)