• DocumentCode
    304739
  • Title

    Transform coding using adaptive bases and quantization

  • Author

    Goyal, Vivek K. ; Zhuang, Jun ; Vetterli, Martin ; Chan, Christopher

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
  • Volume
    1
  • fYear
    1996
  • fDate
    16-19 Sep 1996
  • Firstpage
    365
  • Abstract
    This paper considers the problem of universal transform coding based on estimating the Karhunen-Loeve transform from quantized data. The use of quantized data in the estimation allows the encoder and decoder to maintain the same state without any side information. A theorem is presented that proves, under certain conditions, that consistent estimation of all the required moments is possible from uniformly scalar quantized data regardless of the quantization coarseness. This consistent estimation requires the solution of nonlinear equations. Very simple approximations that avoid these nonlinear equations are used to develop a practical adaptive coding technique. Promising experimental results obtained with this method are presented
  • Keywords
    adaptive codes; adaptive signal processing; image coding; transform coding; transforms; vector quantisation; Karhunen-Loeve transform; adaptive bases; adaptive coding; adaptive quantization; adaptive vector quantization; approximations; consistent estimation; decoder; encoder; experimental results; image coding; moments estimation; nonlinear equations solution; quantization coarseness; uniformly scalar quantized data; universal transform coding; Adaptive coding; Computer science; Costs; Decoding; Huffman coding; Nonlinear equations; Quantization; State estimation; Statistics; Transform coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1996. Proceedings., International Conference on
  • Conference_Location
    Lausanne
  • Print_ISBN
    0-7803-3259-8
  • Type

    conf

  • DOI
    10.1109/ICIP.1996.560834
  • Filename
    560834