Multiresolution tree structured vector quantization

Jia Li, Navin Chaddha, Robert M. Gray

Research output: Contribution to journalConference article

1 Scopus citations

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 in the paper 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 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 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.

Original languageEnglish (US)
Pages (from-to)922-925
Number of pages4
JournalConference Record of the Asilomar Conference on Signals, Systems and Computers
Volume2
StatePublished - Jan 1 1997
EventProceedings of the 1996 30th Asilomar Conference on Signals, Systems & Computers. Part 2 (of 2) - Pacific Grove, CA, USA
Duration: Nov 3 1996Nov 6 1996

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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