Fast codebook design for vector quantization on partitioned space

Shintaro Momose, Kentaro Sano, Tadao Nakamura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Vector quantization(VQ) is an attractive technique for lossy data compression, which has been a key technology for data storage and/or transfer. So far, various competitive learning (CL) algorithms have been proposed to design optimal code-books presenting quantization with minimized errors. However, their practical use has been limited for large scale problems, due to the computational complexity of competitive learning. This paper presents a fast codebook design algorithm reducing the computational complexity. The algorithm partitions input-vector space into some subspaces, and designs a subcodebook for each subspace independently. Experimental results indicate a speedup of this algorithm without serious increase of quantization errors, and promising potential of its parallelization.

Original languageEnglish
Title of host publicationProceedings of the Second International Conference on Information Technology and Applications (ICITA 2004)
Pages58-63
Number of pages6
Publication statusPublished - 2004 Dec 27
EventProceedings of the Second International Conference on Information Technology and Applications (ICITA 2004) - Harbin, China
Duration: 2004 Jan 92004 Jan 11

Publication series

NameProceedings of the Second International Conference on Information Technology and Applications (ICITA 2004)

Other

OtherProceedings of the Second International Conference on Information Technology and Applications (ICITA 2004)
Country/TerritoryChina
CityHarbin
Period04/1/904/1/11

Keywords

  • Competitive learning
  • Optimal codebook design
  • Space partitioning
  • Vector quantization

ASJC Scopus subject areas

  • Engineering(all)

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