Bilinear vector quantization

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Vector quantization (VQ) is a simple and useful data compression algorithm which has been widely applied in many fields such as image processing and pattern recognition. Because each data block is encoded by only one approximate vector in the codebook, the accuracy of the reconstructed blocks is usually poor in VQ. In this paper, the bilinear vector quantization (BVQ) algorithm is proposed with simple expressions. Experiment results show that the quality of the reconstructed data blocks in BVQ is much better than that in VQ when their encoding time is kept the same. Hence, BVQ is more efficient and more effective than VQ.

Original languageEnglish
Title of host publication2013 IEEE Digital Signal Processing and Signal Processing Education Meeting, DSP/SPE 2013 - Proceedings
PublisherIEEE Computer Society
Pages1-6
Number of pages6
ISBN (Print)9781479916160
DOIs
StatePublished - 2013
Event2013 IEEE Digital Signal Processing and Signal Processing Education Meeting, DSP/SPE 2013 - Napa, CA, United States
Duration: 11 Aug 201314 Aug 2013

Publication series

Name2013 IEEE Digital Signal Processing and Signal Processing Education Meeting, DSP/SPE 2013 - Proceedings

Conference

Conference2013 IEEE Digital Signal Processing and Signal Processing Education Meeting, DSP/SPE 2013
Country/TerritoryUnited States
CityNapa, CA
Period11/08/1314/08/13

Keywords

  • Vector quantization
  • bilinear vector quantization
  • data compression

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