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11
Issue
vol 67 / November, 2024
Article

DOI 10.17586/0021-3454-2016-59-12-991-996

UDC 004.627

IMPROVING THE EFFICIENCY OF DATA COMPRESSION USING A HIERARCHICALLY ENUMERATIVE CODING

. Nguyen Van Truong
ITMO University, Saint Petersburg, 197101, Russian Federation; postgraduate


A. A. Tropchenko
ITMO University, Saint Petersburg, 197101, Russian Federation; Associate Professor


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Abstract. A method is proposed for improving the efficiency of multimedia data compression standards. To improve the efficiency of entropy coding within the standard, the hierarchical enumerative coding (HEnuC) is used, including the coding method of Lynch-Davisson (LD) and enumerative coding of bounded integers (EBI). Experimental study of the proposed solutions is performed using MatLab package for several images. The presented results demonstrate better compression than achieved with the simple entropy coding (Huffman method). The developed approach is recommended for the use in telecommunication systems for storage, transmission, and processing of multimedia data.
Keywords: hierarchical enumerative coding (HEnuC), entropy coding, compression rate, lexicographic index, multimedia data compression

References:
  1. Richardson I.E. H.264 and MPEG-4 Video Compression: Video Coding for Next-generation Multimedia, John Wiley & Sons, 2004, 306 р.
  2. Vatolin D., Ratushnyak A., Smirnov M., Yukin V. Metody szhatiya dannykh. Ustroystvo arkhivatorov, szhatie izobrazheniy i video (Methods of Data Compression. The Device Archiver, Compression of Images and Videos), Moscow, 2003, 384 p. (in Russ.)
  3. Huffman D.A. Proc. IRE, 1952, no. 9(40), pp. 1098–1101. DOI: 10.1109/JRPROC.1952.273898.
  4. Sharma M. International Journal of Computer Science and Network Security, 2010, no. 5(10), pp. 133–141. 
  5. Rissanen J.J., Langdon G.G. IBM Journal of Research and Development, 1979, no. 2(23), pp. 149–162.
  6. Howard P.G., Vitter J.C. Proceedings of the IEEE, 1994, no. 6(82), pp. 857–865. DOI: 10.1109/5.286189.
  7. Welch T.A. IEEE Computer Society, 1984, no. 6(17), pp. 8–19. DOI: 10.1109/MC.1984.1659158.
  8. Ziv J., Lempel A. IEEE Trans. Information Theory, 1977, no. 3(23), pp. 337–343. DOI: 10.1109/TIT.1977.1055714.
  9. Lynch T.J. Proc. IEEE, 1966, no. 10(54), pp. 1490–1491. DOI: 10.1109/PROC.1966.5167.
  10. Davisson L.D. Proc. IEEE, 1966, no. 12(54), pp. 2010.
  11. Schalkwijk J.P.M. IEEE Trans. on Information Theory, 1972, no. 3(18), pp. 395–399. DOI: 10.1109/TIT.1972.1054832.
  12. Cover T.M. IEEE Trans. on Information Theory, 1973, no. 1(19), pp. 73–77. DOI: 10.1109/TIT.1973.1054929.
  13. Lehmer D.H. Proc. of Symposia in Applied Mathematics, American Mathematical Society, Providence, R.I., 1960, no. 10, pp. 179–193.
  14. Öktem L. IEEE Electrotechnical Conf., 1994, no. 1, pp. 329–331. DOI: 10.1109/MELCON.1994.381087.
  15. Öktem L., Astola J. IEEE Electronics Letters, 1999, no. 17(35), pp. 1428–1429. DOI: 10.1049/el:19990969.