[1] Sroubek F. and Flusser J., Multichannel blind iterative image restoration, IEEE Trans. Image Processing, 2003; 12(9): 1094 1106.
[3] Katkovnik V., Egiazarian K., and Astola J., A Spatially Adaptive Nonparametric Regression Image Deblurring, IEEE Trans. Image Processing, 2005; 14(10): 1469-1478.
[4] Katkovnik V., Paliy D., Egiazarian K., and Astola J., Frequency domain blind deconvolution in multiframe imaging using anisotropic spatially-adaptive denoising, in Proc. 14th European Signal Process. Conf., EUSIPCO 2006, Florence, Sept. 2006.
[5] Banham M. and Katsaggelos A., Digital image restoration, IEEE Signal Processing Mag., 1997; 14(2): 24–41.
[6] Kundur D. and Hatzinakos D., Blind image deconvolution, IEEE Signal Processing Mag., 1996; 13(3): 43–64.
[7] Chan T., Osher S., Shen J., The digital TV filter and nonlinear denoising, IEEE Trans. Image Processing, 2001; 10(10): 231 241.
[8] Panci G., Campisi P., Colonnese S., and Scarano G., Multichannel blind image deconvolution using the Bussgang algorithm: Spatial and multiresolution approaches, IEEE Trans. Image Processing, 2003; 12(11): 1324-1337.
[9] Harikumar G. and Bresler Y., Perfect blind restoration of images blurred by multiple filters: Theory and efficient algorithm, IEEE Trans. Image Processing, 1999; 8(2): 202-219.
[10] Harikumar G. and Bresler Y., Exact image deconvolution from multiple FIR blurs, IEEE Trans. Image Processing, 1999; 8(6): 846-862.
[11] Giannakis G.B. and Heath Jr. R.W., Blind identification of multichannel FIR blurs and perfect image restoration, IEEE Trans. Image Processing, 2000; 9(11): 1877-1896.
[12] Sroubek F. and Flusser J., Multichannel blind deconvolution of spatially misaligned images, IEEE Trans. Image Processing, 2005; 14(7): 874-883.
[13] Taxt T., Strand J., Two-dimensional noise-robust blind deconvolution of ultrasound images, IEEE Trans. Ultrasonics, Ferroelectrics and Frequency Control, 2001; 48(4): 861-866.
[14] Abeyratne U.R., Petropulu A.P., Reid J.M., Golas T., Conant E., Forsberg F., Higher order versus second order statistics in ultrasound image deconvolution, IEEE Trans. Ultrasonics, Ferroelectrics and Frequency Control, 1997; 4(6): 1409-1416.
[15] Guerrero-Colon J.A., Mancera L., Portilla J., Image restoration using space-variant Gaussian scale mixtures in overcomplete pyramids, IEEE Trans. on Image Processing, 2008; 17(1): 27-41.
[16] Katkovnik V., Egiazarian K., and Astola J., Adaptive window size image de-noising based on intersection of confidence intervals (ICI) rule, Journal of Mathematical Imaging and Vision, 2002; 16: 223-235.
[17] Foi A., Katkovnik V., and Egiazarian K., Pointwise shape-adaptive DCT for high-quality denoising and deblocking of grayscale and color images, IEEE Trans. Image Processing, 2007; 16(5): 1395-1411.
[18] Selesnic I.W.k, Baraniuk R.G., and Kingsbury N., The dual-tree complex wavelet transform - A coherent framework for multiscale signal and image processing, IEEE Signal Processing Magazine, 2005; 22(6): 123- 151.
[19] Rabbani H., Vafadoost M., Noise reduction based on a local Laplace pdf in complex wavelet domain, in Proc. 4th Iranian Conference of Machine Vision and Image Processing (MVIP07), Mashad, Feb. 2007.
[20] Tikhonov A., On the stability of inverse problems, Doklady Akademii Nauk SSSR, 1943; 39(5): 195-198.
[21] Chambolle A., Inverse problems in image processing and image segmentation: some mathematical and numerical aspects, Springer Lecture Notes, Sept. 2000.
[22] L. Rudin, S. Osher, and E. Fatemi, Nonlinear total variation based noise removal algorithms, Phys. D, 1992; 60: 259-268.
[23] Mumford D. and Shah J., Optimal approximation by piecewise smooth functions and associated variational problems, Comm. Pure Applied Math., 1989; 42: 577- 685.
[24] Deuflhard P., Newton Methods for Nonlinear Problems. Affine Invariance and Adaptive Algorithms. Springer Series in Computational Mathematics, vol. 35. Springer, Berlin, 2004.
[25] Donoho D.L. and Johnstone I.M., Ideal spatial adaptation by wavelet shrinkage, Biometrika, 1994; 81(3): 425–455.
[26] Crouse M.S., Nowak R.D., and Baraniuk R.G., Wavelet-based statistical signal processing using hidden Markov models, IEEE Trans. Signal Processing, 1998; 46(4): 886–902.
[27] Chang S.G., Yu B., and Vetterli M., Adaptive wavelet thresholding for image denoising and compression, IEEE Trans. Image Process., 2000; 9(9): 1532–1546.
[28] Portilla J., Strela V., Wainwright M.J., and Simoncelli E.P., Image denoising using gaussian scale mixtures in the wavelet domain, IEEE Trans. Image Processing., 2003; 12(11): 1338–1351.
[29] Kingsbury N.G., A dual-tree complex wavelet transform with improved orthogonality and symmetry properties, in Proc. ICIP, 2000; 2: 375–378.
[30] Richardson W.H., Bayesian-Based Iterative Method of Image Restoration, JOSA, 1972; 62(1): 55–59.
[31] Lucy L.B., An iterative technique for the rectification of observed distributions, Astronomical Journal, 1974; 79(6): 745–754.
[32] Vega-Alvarado L., Elezgaray I., Hemar A., Menard M., Ranger C., Corkidi G., A comparison of image deconvolution algorithms applied to the detection of endocytic vesicles in fluorescence images of neural proteins, in Proc. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 22-26 Aug. 2007: 755 – 758.
)