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A Proof of the Necessary Condition for Perfect Reconstruction of Signals Using the Two-channel Wavelet Filter Bank

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Języki publikacji
EN
Abstrakty
EN
Wavelet representation of signals and images is very useful for compression purposes. To obtain a wavelet representation by splitting a digital signal into two subsampled sygnals in a two-channel filter bank, the filters must satisfy perfect reconstruction conditions. This paper presents a theorem that formulates perfect reconstruction conditions for two-channel filter bank and a complete proof of both necessary and sufficiant conditions. Additional requirements for filters guaranteeing the existence of the wavelets are reviewed.
Słowa kluczowe
Rocznik
Strony
13--23
Opis fizyczny
2 rys., bibliogr. 16 poz.
Twórcy
autor
  • Białystok University of Technology, Faculty of Computer Science, Wiejska Str. 45a, 15-345 Białystok (Wydział Informatyki Politechniki Białostockiej)
Bibliografia
  • [1] A. Cohen, I. Daubechies, J.-C. Feauveau, Biorthogonal bases of compactly supported wavelets, Communications on Pure and Applied Mathematics, 45 (1992) 485-560.
  • [2] A. Croisier, D. Esteban, C. Galand, Perfect channel splitting by use of interpolation/decimation techniques, In Internat. Conf. On Information Sciences and Systems, Patras, Greece (August 1976) 443-446.
  • [3] I. Daubechies, Orthonormal bases of compactly supported wavelets, Communications in Pure and Applied Mathematics, 41 (1988) 909-996.
  • [4] P. N. Heller, J. M. Shapiro, R. O. Wells, Optimally smooth symmetric quadrature mirror filters for image coding, In: Wavelet Applications II, Orlando, FL, SPIE (1995) 119-130.
  • [5] S. Mallat, A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 11, 7, (1989) 674-693.
  • [6] S. Mallat, A wavelet tour of signal processing, Academic Press, San Diego 1998.
  • [7] W. Rakowski, Z. Bartosiewicz, Daubechies filters in wavelet image compression, Fundamenta Informaticae, 34, 4, (July 1998), 455-467.
  • [8] H. L. Resnikoff, R. O. Wells, Wavelet analysis, Springer-Verlag, New York 1998.
  • [9] O. Rioul, A discrete-time multiresolution theory, IEEE Transactions on Signal Processing, 41, 8, (Aug. 1993) 2591-2606.
  • [10] Y. Shang, L. Li, B. Wah, Optimization design of biorthogonal filter banks for image compression, Information Sciences, 132 (2001) 23-51.
  • [11] M. J. T. Smith, T. P. Barnwell III, Exact reconstruction techniques for tree-structured subband coders, IEEE Trans. on ASSP, 34 (1986) 434-441.
  • [12] G. Strang, T. Nguyen, Wavelets and filter banks, Wellesley-Cambridge Press, Wellesley, MA, 1996.
  • [13] P. P. Vaidyanathan, Multirate systems and filter banks, Prentice Hall, Englewood Cliffs, NJ, 1993.
  • [14] M. Vetterli, Filter banks allowing perfect reconstruction, Signal Processing, 10, 3, (April 1986) 219-244.
  • [15] M. Vetterli, C. Herley, Wavelets and filter banks: theory and design, 40, 9, (September 1992) 2207-2232.
  • [16] M. Vetterli, J. Kovačević, Wavelets and subband coding, Prentice Hall Signal Processing Series, Prentice-Hall, Englewood Cliffs, NJ, USA 1995.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPG1-0009-0006
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