[3] KENNETH R C. Digital Image Processing [M]. Prentice Hall: a Simon& Schuster Company, 1996.
[4] MALLAT S G. A theory for multi-resolution signal decomposition: the wavelet representation [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(7): 674-693.
[5] JO Y T, SHEN L X, SENG L L, et al. A general approach for analysis and application of discrete multi-wavelet transform [J]. IEEE Transactions on Signal Processing, 2000, 48(2): 457-464.
[6] MALLAT S. Multiresolution approximations and wavelet orthonormal bases of L2(R) [J]. Transaction of American Mathematical Society, 1989, 315(1): 69-87.
[7] Mallat S. Multiresolution representation and wavelets [D]. Philadelphi: Univ. of Pennsylvaniaa, 1988.
[8] NEELAMANI R, CHOI H, BARANIUK R. Wavelet-based deconvolution using optimally regularized inversion for ill-conditioned systems [J]. SPIE, 1999, 3813: 58-72.
[9] MURAT B, MISHA E K, ERIC L M. Wavelet Domain Image Restoration with Adaptive Edge-Preserving Regularization [J]. IEEE Trans. On Image Processing, 9(4): 597-608.
[10] MICHAEL E Z, TACK M K, YANG J S. Multi-resolution Image Restoration in the Wavelet Domain [J]. IEEE Trans. on Circuits and Systems-II: Analog and Digital Signal Processing, 1995, 42(9): 578-591.
