Pakiety falkowe w kompresji sygnałów i obrazów

Rakowski, W.

Artykuł - szczegóły

Tytuł artykułu

Pakiety falkowe w kompresji sygnałów i obrazów

Autorzy

Rakowski W.

Wybrane pełne teksty z tego czasopisma

http://ijet.pl/index.php/ijet

Identyfikatory

Warianty tytułu

Wavelet packets in signal and image compression

Języki publikacji

Abstrakty

W pracy przedstawiono podstawy matematyczne reprezentacji sygnałów za pomocą pakietów falkowych. Pokazano bazy do aproksymacji sygnałów oparte na pakietach falkowych Walsha. Podano algorytm szukania najlepszej bazy i jego implementację w języku ANSI C. Zamieszczono informację o złożoności obliczeniowej algorytmów reprezentacji sygnałów za pomocą pakietów falkowych. Omówiono wykorzystanie pakietów falkowych w kompresji dźwięków i obrazów.

In the paper mathematical basics of signal representation by wavelet packets were presented. Walsh wavelet packet bases for signal approximation were described. An algorithm to search the best basis and the implementation of the algorithm in ANSI C programming language were shown. Computational complexity of the wavelet packet representation was presented. Application of wavelet packets in both signal an image compression were discussed.

Słowa kluczowe

falka filtr falkowy transformacja falkowa pakiet falkowy najlepsza baza kompresja dźwięku kompresja obrazu

wavelet wavelet filter wavelet transform wavelet packets best basis sound compression image compression

Wydawca

Wydawnictwo Naukowe PWN SA

Czasopismo

Kwartalnik Elektroniki i Telekomunikacji

Rocznik

2004

Tom

Vol. 50, z. 2

Strony

159--178

Opis fizyczny

Bibliogr. 36 poz.

Twórcy

autor

Rakowski W.

Politechnika Białostocka, Wydział Informatyki, ul. Wiejska 45 A, 15-351 Białystok, waldi@ii.pb.bialystok.pl

Bibliografia

1. R. Coifman, Y. Meyer, V. Wickerhauser: Size Properties of Wavelet-Packets. M.B. Ruskai, G. Beylkin, R. Coifman, I. Daubechics, S. Mallat, Y. Meyer, L. Raphael, editors, Wavelets and Their Applications, Boston, Jones and Bartlett Publishers, MA, 1992, pp. 453-470.
2. R. Coifman, Y. Meyer, V. Wickerhauser: Wavelel Analysis and Signal Processing. M.B. Ruskai, G. Beylkin, R. Coifman, I. Daubechics, S. Mallat, Y. Meyer, L. Raphael, editors, Wavelets and Their Applications, Boston, Jones and Bartlett Publishers, MA, 1992, pp. 153-178.
3. R. R. Coifman, Y. Meyer, S. R. Quake, M. V. Wickerhauser: Signal Processing and Compression with Wavelel Packels. J .S. Byrnes, J. L. Byrnes, K.A. Hargreaves, K. Berry, editors, Wavelets and Their Applications, volume 442 of NATO ASI Series C: Mathematical and Physical Sciences, Kluwer Academic Publishers, Dordrecht/Boston/London, 1994. Proccedings of the NATO Advanced Study Institute at II Ciocco, Barga, Italy, August, 1992, pp. 363-379.
4. R. R. Coifman, M. V. Wickerhauser: Entropy-Based Algorithms for Best Basis Selection. IEEE Transactions on Information Theory, 38(2), 1992, pp. 713-718.
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7. I. Daubechies: Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 1992.
8. M. Feil, A. Uhl: Wavelet Packet Decomposition and Best Basis Selection on Massively Parallel SIMD Arrays. Proceedings of the International Conference Wavelets and Multi scale Methods (IWC'98), INRIA, Rocquencourt, April 1998, http://citeseer.nj.nec.com/article/feil98wavelet.html.
9. M. Feil, A. Uhl: Algorithmes and Programming Paradigms for 2-D Wavelet Packer Decomposition on Multicomputers and Multiprocessors. ACPC, 1999, pp. 367-376, http//citeseer.nj.nec.com/feil99algorithm.html.
10. S.-Y. Han, S.-Y. Cho: Coefficient Partitioning Scanning Order Wavelet Pocket Algorithm for Satellite Images. CAIP 2003, 10th International Conference on Computer Analysis or Images and Patterns, Groningen, The Netherlands, Aug., 2003, pp. 25-27.
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13. R. Kutil, A. Uhl: Parallel adaptive wavelet analysis. Future Generation Computer Systems, 18(1), 2001, pp. 97-106, http://citeseer.nj.nec.com/kutil01parallel.html.
14. A. Laine, J. Fan: Texture classification by wavelet pocket signatures. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(15), 1993, pp. 1186-1191.
15. R. E. Learned, A. S. Willsky: A wavelet packet approach to transient signal classification. Appl. Comput. Harmonic Anal, 2, 1995, pp. 265-278.
16. A. R. Lindscy, J. C. Dill: Digital transceiver implementation for wavelet pocket modulation. H. H. Szu, editor, Wavelet Applications V, SPIE Proceedings, volume 3391, 1998, pp. 255-264.
17. S. Mallat: A Wavelet Tour of Signal Processing. Academic Press, San Diego, 1998.
18. S. G. Mallat: Multiresolution approximations and wavelet orthonormal bases of L2(R). Transactions of the American Mathematical Society, 315( 1), September 1989, pp. 69-87.
19. S. G. Mallat: A theory for multiresolution signal decomposition: The wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(7), July 1989, pp. 674-693.
20. F. G. Meyer, A. Z. Averbuch, J.-O. Stromberg: Fast Adaptive Wavelet Packet Image Compression. IEEE Transactions on Image Processing, 9(5), May 2000.
21. L. Bacchelli Montefusco: Semi-orthogonal Wavelet Packet Bases for Parallel Least-squares Approximation. J. Comput. Appl. Math., 73, 1996, pp. 191-208.
22. W. Rakowski: Kodowanie transformat falkowych dla obrazów. VI Sympozjum Nowości w Technice Audio-Technika Audio a Multimedia, Warszawa, 22-23 października 1999, ss. 101-111.
23. W. Rakowski: Metody falkowe kompresji obrazów z obszarami zainteresowania. Rozprawy Naukowe Nr 99. Wydawnictwo Politechniki Białostockiej, Białystok, 2002.
24. W. Rakowski: A Proof of the Necessary Condition for Perfect Reconstruction of Signals Using the Two-Channel Wavelet Filter Bank. Bulletin of the Polish Academy of Sciences, Technical Sciences, 51(1), 2003, pp. 13-23.
25. K. Ramchandran, M. Vetterli: Best Wavelet Pocket Bases in a Rate-Distortion Sense. IEEE Transactions on Image Processing, 2(2), 1993, pp. 160-175.
26. K. Ramchandran, Z. Xiong, K. Asai, M. Vetterli: Adaptive Transforms for Image Coding Using Spatially-varing Wavelet Packets. IEEE Transactions on Image Processing, 5, 1996, pp. 1197-1204.
27. N. Saito, R. R. Coifman: Local Discriminant Bases. A. F. Laine, M. A. Unser, editors, Wavelet Applications in Signal and Image Processing II, SPIE Proceedings, vol. 2303, 1995, pp. 2-14.
28. Y. Shoham, A. Gersho: Efficient Bit Allocation for an Arbitrary Set of Quantizers. IEEE Transactions on Acoustics, Speech, and Signal Processing, 36(9) September 1988, pp. 1445-1453.
29. P. Srinivasan, L. Jamienson: High Quality Audio Compression Using an Adaptive Wavelet Pocket Decomposition and Psychoacoustic Modelling. IEEE Transactions on Signal Processing, 46(4), 1998, pp. 1085-1093.
30. J. Szabatin: Podstawy teorii sygnałów., Warszawa, WKŁ, 2000.
31. C. Taswell: Satisficing Search Algorithms for Selecting Near-Best Bases in Adaptive Tree-Structured Wavelet Transforms. IEEE Transactions on Signal Processing, 44(10), 1996, pp. 2423-2438.
32. M. Vetterli: Filter Banks Allowing Perfect Reconstruction. Signal Processing. 10(3), April 1986, pp. 219-244.
33. M. V. Wickerhauser: INRIA Lectures on Wavelet Packet Algorithms. Pierre-Louis Lions, editor, Problémes Non-Linéaires Appliqués , Ondelettes et Paquets D'Ondes,. INRIA, Roquencourt, France, 17-21 June 1991, pp. 31-99 http://www.math.wustl.edu/victor/papers/lwpa.pdf.
34. M. V. Wickerhauser: Acoustic signal compression with wavelet packets.+ Ch. K. Chui, editor, Wavelets - A Tutorial in Theory and Applications, Academic Press, Boston, 1992, pp. 679-700, http://www.math.wustl.edu/victor/papers/acoustic.ps.gz.
35. M. V. Wickerhauser: Progress in Wavelet Algorithms and Applications. H. H. Szu, editor, Wavelet and Independent Component Analysis Applications IX, vol. 4738 of SPIE Proceedings, Orlando, Florida, 3-5 April 2002, pp. 1-12 hup://www.math.wustl.edu/victor/papers/pwaa.pdf.
36. Z. Xiong, K. Ramchandran, M. T. Orchard: Wavelet Packet Image Coding Using Space-frequency Quantization. IEEE Transactions on Image Processing, 7, 1998, pp. 160-174.

Typ dokumentu

Bibliografia

Identyfikator YADDA

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