Simultaneous Noise Suppression and Signal Compression Using a Library of Orthonormal Bases and the Minimum Description Length Criterion

Wavelet Analysis and Its Applications

Volumn 4, Issue C, 1994, Pages 299-324

  Saito, Naoki ^a  

^a SCHLUMBERGER DOLL RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85011629828     PISSN: 1874608X     EISSN: None     Source Type: Book Series    
DOI: 10.1016/B978-0-08-052087-2.50017-7     Document Type: Chapter

References (36)

1. Ahmed, N., Rao, K.R., Orthogonal Transforms for Digital Signal Processing, 1975, Springer-Verlag, New York.
2. Auscher, P., Weiss, G., Wickerhauser, M.V., Local sine and cosine bases of Coifman and Meyer and the construction of smooth wavelets. Chui, C.K., (eds.) Wavelets: A Tutorial in Theory and Applications, 1992, Academic Press, San Diego, 237–256.
3. Barron, A. R., Complexity regularization with application to artificial neural networks, in Proceeding NATO ASI on Nonparametric Functional Estimation, Kluwer, 1991.
4. Barron, A.R., Cover, T.M., Minimum complexity density estimation. IEEE Trans. Inform. Theory 37:4 (1991), 1034–1054.
5. Beylkin, G., Coifman, R., Rokhlin, V., Fast wavelet transforms and numerical algorithms I. Comm. Pure Appl. Math. 44 (1991), 141–183.
6. Bradley, J.N., Brislawn, C.M., Image compression by vector quantization of multiresolution decompositions. Physica D 60 (1992), 245–258.
7. Coifman, R. R. and F. Majid, Adapted waveform analysis and denoising, in Progress in Wavelet Analysis and Applications, Y. Meyer and S. Roques (eds.), Editions Frontieres, B.P.33, 91192 Gif-sur-Yvette Cedex, France, 63–76, 1993.
8. Coifman, R.R., Meyer, Y., Remarques sur l'analyse de fourier à fenětre. Comptes Rendus Acad. Sci. Paris, Série I 312 (1991), 259–261.
9. Coifman, R.R., Wickerhauser, M.V., Entropy-based algorithms for best basis selection. IEEE Trans. Inform. Theory 38:2 (1992), 713–719.
10. Coifman, R.R., Wickerhauser, M.V., Wavelets and adapted waveform analysis. Benedetto, J., Frazier, M., (eds.) Wavelets: Mathematics and Applications, 1993, CRC Press, Boca Raton, Florida chapter 10.
11. Cover, T.M., Thomas, J.A., Elements of Information Theory, 1991, Wiley Interscience, New York.
12. Daubechies, I., Orthonormal bases of compactly supported wavelets. Comm. Pure Appl. Math. 41 (1988), 909–996.
13. Daubechies, I., Ten Lectures on Wavelets, volume 61 of CBMS-NSF Regional Conference Series in Applied Mathematics, SIAM, Philadelphia, 1992.
14. DeVore, R.A., Jawerth, B., Lucier, B.J., Image compression through wavelet transform coding. IEEE Trans. Inform. Theory 38:2 (1992), 719–746.
15. Donoho, D. L., Wavelet Shrinkage and W.V.D.: a 10-minute tour, in Progress in Wavelet Analysis and Applications, Y. Meyer and S. Roques (eds.), Editions Frontieres, B.P.33, 91192 Gif-sur-Yvette Cedex, Prance, 109–128, 1993.
16. Donoho, D. L. and I. M. Johnstone, Ideal spatial adaptation by wavelet shrinkage, preprint, Dept. of Statistics, Stanford University, Stanford, CA, Jun. 1992, revised Apr. 1993.
17. n. IEEE Trans. Inform. Theory 38:2 (1992), 556–568.
18. n. IEEE Trans. Inform. Theory 38:2 (1992), 533–555.
19. Leclerc, Y.G., Constructing simple stable descriptions for image partitioning. Intern. J. Computer Vision 3 (1989), 73–102.
20. Mallat, S., A theory for multiresolution signal decomposition. IEEE Trans. Pattern Anal. Machine Intell. 11:7 (1989), 674–693.
21. Mallat, S., Zhang, Z., Matching pursuit with time-frequency dictionaries. IEEE Trans. Signal Processing, the special issue on wavelets and signal processing, 41(12), 1993 to appear.
22. Meyer, Y., Ryan, R.D., (eds.) Wavelets: Algorithms and Applications, 1993, SIAM, Philadelphia, PA.
23. Meyer, Y., Salinger, D.H., (eds.) Wavelets and Operators, volume 37 of Cambridge Studies in Advanced Mathematics, 1993, Cambridge University Press, New York.
24. Niblack, W., MDL Methods in Image Analysis and Computer Vision, IEEE Conf. Comput. Vision, Pattern Recognition, Tutorial note, New York, Jun. 1993.
25. Rioul, O., Regular wavelets: a discrete-time approach. IEEE Trans. Signal Processing, the special issue on wavelets and signal processing, 41(12), 1993 to appear.
26. Rioul, O., Vetterli, M., Wavelets and signal processing. IEEE SP Magazine 8:4 (1991), 14–38.
27. Rissanen, J., A universal prior for integers and estimation by minimum description length. Ann. Statist. 11:2 (1983), 416–431.
28. Rissanen, J., Universal coding, information, prediction, and estimation. IEEE Trans. Inform. Theory 30:4 (1984), 629–636.
29. Rissanen, J., Stochastic Complexity in Statistical Inquiry, 1989, World Scientific, Singapore.
30. Shapiro, J. M., Image coding using the embedded zerotree wavelet algorithm, in Proc. SPIE Conf. on Mathematical Imaging: Wavelet Applications in Signal and Image Processing, A. F. Laine (ed.), volume 2034, 180–193, 1993.
31. Wallace, R. S., Finding natural clusters through entropy minimization, PhD thesis, School of Comput. Science, Carnegie Mellon University, Pittsburgh, PA 15213, Jun. 1989.
32. Wax, M., Kailath, T., Detection of signals by information theoretic criteria. IEEE Trans. Acoust., Speech, Signal Processing ASSP–33:2 (1985), 387–392.
33. Wickerhauser, M. V., Lectures on wavelet packet algorithms, preprint, Dept. of Mathematics, Washington University, St. Louis, Missouri, Nov. 1991.
34. Wickerhauser, M. V., Fast approximate factor analysis, in Proc. SPIE Conf. on Curves and Surfaces in Computer Vision and Graphics II, volume 1610, 23–32, 1991.
35. Wickerhauser, M.V., High-resolution still picture compression. Digital Signal Processing: A Review Journal 2:4 (1992), 204–226.
36. Wilson, R., Finite prolate spheroidal sequences and their applications I: generations and properties. IEEE Trans. Pattern Anal. Machine Intell. PAMI-9:6 (1987), 787–795.