Transform-based vector quantization using bitmap search algorithms

Jar Ferr Yang, Yu Hwe Lee, Jen Fa Huang, Zhong Geng Lee

Research output: Contribution to journalArticlepeer-review


In this paper, we propose fast bitmap search algorithms to reduce the computational complexity of transform-based vector quantization (VQ) techniques, which achieve better quality in reconstructed images than the ordinary VQ. By removing the unlikely codewords in each step, the bitmap search method, which starts from the most significant bitmap then the successive significant ones, can save more than 90% computation of the ordinary transformed VQ. By applying to the singular value decomposition (SVD) VQ as an example, theoretical analyses and simulation results show that the proposed bitmap search methods dramatically reduce the computation and achieve invisible distortion in the reconstructed images.

Original languageEnglish
Pages (from-to)2113-2121
Number of pages9
JournalIEICE Transactions on Information and Systems
Issue number12
Publication statusPublished - 2000

All Science Journal Classification (ASJC) codes

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


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