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Reference [1.1]S.Mallat, “A Theory for Multi-resolution Signal Decomposition:The Wavelet Representation,” IEEE Trans. Pattern Anal. And Machine Intell., Vol. 11, no. 7, pp.674-693, July 1989 [1.2]ISO/IEC JTC1/SC29 WG1N 1646R, “Discrete Wavelet Transform of Tile Components, ” 2000 [1.3]M. Vishwanth, “The Recursive Pyramid Algorithm for Discrete Wavelet Transform,” IEEE Trans. On Signal Processing, vol. 42, no. 3, pp.673-676, 1994 [1.4]W.S Peng and C. Y Lee, “An Efficient VLSI Architecture for Separable 2-D Discrete Wavelet Transform” Proc. of IEEE Int. Conf. Image processing, 1999 [1.5]ISO/IEC JTC1/SC29/WGIN 1013, “Low Memory Line–based Wavelet Transform Using Lifting Scheme,” 1998 [2.1]A.N. Akansu, M.V. Tazebay, M.J. Medley and P. K. Das, “Wavelets and Sub-band Transforms:Fundamentals and Communication Applications,” IEEE Communications Magazine, pp. 104-115, Dec. 1997. [2.2]M. Antonini, M. Barlaud, P. Mathieu, and I. Daubechies, “Image Coding Using Wavelet Transform”, IEEE Trans. Image Processing, vol. 1, pp. 205-220, Apr. 1992. [2.3]M. Vetterli and C. Herley, “Wavelets and Filter Banks:Theory and Design,” IEEE Transactions on Signal Processing, vol. 40, pp. 2207-2232, Sep. 1992. [2.4]S. Mallat, “Multi-frequency Channel Decompositions of Images and Wavelet Models,” IEEE Trans. ASSP, vol. 37, pp. 2091-2110, 1989. [2.5]S. Mallat, “A Theory for Multi-resolution Signal Decomposition:The Wavelet Representation,” IEEE Trans. Pattern Anal. Machine Intell., vol. 11, pp. 674-693, July 1989. [2.6]B. Jawerth and W. Sweldens, “An Overview of Wavelet Based Multi-resolution Analysis,” SIAM Rev., vol. 36, pp.377-412, 1994. [2.7]I. Daubenchies, “Orthonormal Bases of Compactly Supported Wavelets,” Comn. Pure Appl. Math., vol. 41, pp. 906-966, 1988. [2.8]M. Vetterli, “Filter Banks Allowing Perfect Reconstruction,” Signal Processing, vol. 10, pp. 219-244, April 1986. [2.9]V.K. Heer and H.E Reinfelder, “A Comparison of Reversible Methods for Data Compression,” in Medical Imaging IV, pp. 354-365, Proc. SPIE 1233, 1990. [2.10]S. A. Martucci and R. M. Mersereau, “The Symmetric Convolution Approach to the Non-expansive Implementation of FIR Filter Banks for Image,” in Proc. 1993 IEEE Int. Conf. Acoustics, Speech, Signal Processing, Minneapolis, MN, Apr. 1993, pp. V.65-V.68 [2.11]A. Cohen, I. Daubechies, and J.C. Feauveau, “Biorthogonal Bases of Compactly Supported Wavelets,” Commun Pure Appl. Math., pp. 485-500, 1992. [2.12]W.Sweldens, “The lifting scheme:A New Philosophy in Biorthogonal Wavelet Constructions,” Proc. SPIE Wavelet Application in Signal and Image Processing III, pp 68-79, 1995. [2.13]W.Sweldens, “The lifting scheme:A Custom-Design Construction of Biorthogonal Wavelets,” Appl. Comput. Harmon. Anal., 3(2):186-200, 1996. [3.1]ISO/IEC JTC1/SC29 WG1N 1646R, “Discrete Wavelet Transform of Tile Components, ” 2000 [4.1]W. Sweldens and P. Schröder. “Building Your Own Wavelets at Home.” Technical Report1995:5, Industrial Mathematic Initiative, Department of Mathematics, University of South Carolina, 1995. [4.2]I. Darbechies and W. Sweldens, “Factoring Wavelet Transforms into Lifting Steps,” tech. Rep., Bell Laboratories, 19 [5.1]J.M. Shapiro, “Embedded Image Coding Using Zerotrees of Wavelet Coefficients,” IEEE Transactions on Signal Processing, SP-41:3445-3462, December 1993. [5.2]A. Said and W.A. Pearlman, “A New Fast and Efficient Coder Based on Set Partitioning in Hierarchical Trees,” IEEE Transactions on Circuits and Systems for Video Technologies, pages 243-250, June 1996. [5.3]D. Taubman, “Directionality and Scalability in Image and Video Compression,” Ph.D. thesis, University of California-Berkeley, May 1994. [5.4]G.K. Wallace, “The JPEG Still Picture Compression Standard,” Communications of the ACM, 34:31-44, April 1991.
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