QUANTIFICATION MULTIDIMENSIONNELLE SPHÉRIQUE LOGARITHMIQUE ΜU-LAW
Mots-clés :
Quantification sphérique logarithmiqueRésumé
Plusieurs chercheurs ont envisagé la quantification logarithmique du signal sphérique. La conception d'un quantificateur sphérique logarithmique en k dimensions est considérée dans cet article. La quantification logarithmique est ici utilisée pour des vecteurs constitués d'échantillons en coordonnées sphériques. La combinaison de la quantification logarithmique et sphérique (LSQ) est une méthode de quantification multidimensionnelle efficace à une plage dynamique élevée, en préservant le signal d'origine aussi près que possible. Le rapport signal sur bruit (SNR) et sa dépendance à la dimension de la sphère à des débits binaires inférieurs sont dérivés et discutés dans cet article.
Références
(1) D. Neuhoff, Quantization, IEEE Transactions on Information Theory, 44, 6, pp. 2325-2383 (1998).
(2) Gersho, R. M. Gray, Vector Quantization and Signal Compression, Boston: Kluwer (1992).
(3) S. Preihs, T. Lamprecht, J. Ostermann, Error robust low delay audio coding using spherical logarithmic quantization, in 24th European Signal Processing Conference (EUSIPCO), pp. 1970-1974, Budapest, Hungary, (29 August-2 September 2016).
(4) H. Kruger, R. Schreiber, B. Geiser, P. Vary, On logarithmic spherical vector quantization, in International Symposium on Information theory and its applications ISITA 2008, Auckland, New Zelland, (7-10 December 2008).
(5) P. Swaszek, J. B. Thomas, Multidimensional spherical coordinates quantization, IEEE Transactions on Information Theory, 29, 4, pp. 570-576 (July 1983).
(6) J. Hamkins, K. Zegger, Gaussian source coding with spherical codes, IEEE Transactions on Information Theory, 48, 11, pp. 2980-2989 (November 2002).
(7) J. Conway, N. Sloane, Sphere Packings, Lattices and Groups, Springer (1993).
(8) Z. Perić, J. Lukić, J. Nikolić, D. Denić, Design of nonuniform dead-zone quantizer with low number of quantization levels for the Laplacian source, Rev. Roum. Sci. Techn - Elektrotechn. et Energ., 58, 1, pp. 93-100 (2013).
(9) H. H. Henning, J. W. Pan, D2 channel bank: System aspects, The Bell System Technical Journal, 51, 8, pp. 1641-1657 (1972).
(10) N. S. Jayant, P. Noll, Digital Coding of Waveforms, Englewood Cliffs, NJ: Prentice-Hall (1984).
(11) Z. Perić, D. Aleksić, M. Stefanović, J. Nikolić, New approach to support region determination of the μ-law quantizer, Elektronika Ir Elektrotechnika, 19, 8, pp. 111-114 (2013).
(12) Z. Perić, D. Aleksić, Quasilogarithmic quantizer for Laplacian source: supporting region ubiquitous optimization task, Rev. Roum. Sci. Techn - Elektrotechn. et Energ., 64, 4, pp. 403-408 (2019).
(13) J. B. Huber, B. Matschkal, Spherical logarithmic quantization and its application for DPCM, in 5th International ITG Conference on source and channel coding, pp. 349-356, Erlangen, Germany (January 2004).
(14) B. Matschkal, F. Bergner, J. B. Huber, Joint signal processing for spherical logarithmic quantization and DPCM, in 6th International ITG Conference on source and channel coding, Munich, Germany (April 2006).
(15) Z. Utkovski, A. Utkovski, T. Eriksson, High-dimensional spherical quantization of Gaussian sources, in Canadian Workshop on Information Theory, pp. 211-214, Montreal, Quebec (June 2005).
(16) J. Hamkins, Design and analysis of spherical codes, Ph.D. dissertation, University Illinois at Urbana-Champaign, USA (September 1996).
(17) H. S. M. Coxeter, Regular Polytopes, 3rd edition, New York: Dover (1973).