• DocumentCode
    311160
  • Title

    Multiresolution tree structured vector quantization

  • Author

    Li, Jia ; Chaddha, Navin ; Gray, Robert M.

  • Author_Institution
    Dept. of Electr. Eng., Stanford Univ., CA, USA
  • fYear
    1996
  • fDate
    3-6 Nov. 1996
  • Firstpage
    922
  • Abstract
    In some applications of progressive image transmission, the images are viewed at several resolutions with fewer bits at lower resolutions. A multiresolution tree structured vector quantizer is developed to produce an embedded code, so that the quality of the image is optimized for the corresponding resolution at any number of bits. The resolution at which the image is viewed given a particular number of bits is determined by the specific decoder. The multiresolution tree structured vector quantizer presented generates the codebook by greedy tree growing, which is an extension of the generalized BFOS algorithm. The tree is grown one step further by splitting the node which will yield the best ratio of the change in distortion at the corresponding resolution of the current bit rate to the change in rate. The decoder has codewords of all resolutions obtained by optimal centroiding for a given resolution and a given encoder partition. The encoding of an image is essentially the same as the BFOS algorithm and the difference is that instead of having a fixed distortion measure, the distortion measure is defined for the corresponding resolution at a particular bit rate. This algorithm is compared with the generalized BFOS algorithm for image quality at different resolutions.
  • Keywords
    decoding; image coding; image resolution; rate distortion theory; vector quantisation; visual communication; VQ; bit rate; codebook; codewords; decoder; distortion measure; embedded code; generalized BFOS algorithm; greedy tree growing; image quality; image resolution; multiresolution tree structured vector quantization; progressive image transmission; Bit rate; Decoding; Distortion measurement; Image coding; Image communication; Image quality; Image resolution; Particle measurements; Partitioning algorithms; Vector quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 1996. Conference Record of the Thirtieth Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA, USA
  • ISSN
    1058-6393
  • Print_ISBN
    0-8186-7646-9
  • Type

    conf

  • DOI
    10.1109/ACSSC.1996.599079
  • Filename
    599079