• DocumentCode
    2477682
  • Title

    Quantization as histogram segmentation: globally optimal scalar quantizer design in network systems

  • Author

    Muresan, Dan ; Effros, Michelle

  • Author_Institution
    Dept. of Electr. Eng., Stanford Univ., CA, USA
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    302
  • Lastpage
    311
  • Abstract
    We propose a polynomial-time algorithm for optimal scalar quantizer design on discrete-alphabet sources. Special cases of the proposed approach yield optimal design algorithms for fixed-rate and entropy-constrained scalar quantizers, multi-resolution scalar quantizers, multiple description scalar quantizers, and Wyner-Ziv scalar quantizers. The algorithm guarantees globally optimal solutions for fixed-rate and entropy-constrained scalar quantizers and constrained optima for the other coding scenarios. We derive the algorithm by demonstrating the connection between scalar quantization, histogram segmentation, and the shortest path problem in a certain directed acyclic graph.
  • Keywords
    computational complexity; directed graphs; entropy codes; optimisation; quantisation (signal); statistical analysis; Wyner-Ziv scalar quantizers; codebook; coding; constrained optima; directed acyclic graph; discrete-alphabet sources; entropy-constrained scalar quantizers; fixed-rate scalar quantizers; globally optimal scalar quantizer; histogram segmentation; multi-resolution scalar quantizers; multiple description scalar quantizers; network systems; polynomial-time algorithm; quantization; shortest path problem; Algorithm design and analysis; Data compression; Decoding; Design optimization; Histograms; Intelligent networks; Partitioning algorithms; Polynomials; Quantization; Shortest path problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Compression Conference, 2002. Proceedings. DCC 2002
  • ISSN
    1068-0314
  • Print_ISBN
    0-7695-1477-4
  • Type

    conf

  • DOI
    10.1109/DCC.2002.999968
  • Filename
    999968