Variable-rate vector quantizer design using genetic algorithm

Wen Jyi Hwang*, Sheng Lin Hong

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


This letter presents a novel variable-rate vector quantizer (VQ) design algorithm, which is a hybrid approach combining a genetic algorithm with the entropy-constrained VQ (ECVQ) algorithm. The proposed technique outperforms the ECVQ algorithm in the sense that it reaches to a nearby global optimum rather than a local one. Simulation results show that, when applied to the image coding, the technique achieves higher PSNR and image quality than those of ECVQ algorithm.

Original languageEnglish
Pages (from-to)616-620
Number of pages5
JournalIEICE Transactions on Information and Systems
Issue number6
Publication statusPublished - 1998
Externally publishedYes


  • Genetic algorithm
  • Global optimization
  • Vector quantization

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence


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