A Fast Search Method for Vector Quantization Using Enhanced Sum Pyramid Data Structure

Zhibin Pan, Koji Kotani, Tadahiro Ohmi

Research output: Contribution to journalArticlepeer-review


Conventional vector quantization (VQ) encoding method by full search (FS) is very heavy computationally but it can reach the best PSNR. In order to speed up the encoding process, many fast search methods have been developed. Base on the concept of multi-resolutions, the FS equivalent fast search methods using mean-type pyramid data structure have been proposed already in [2]-[4]. In this Letter, an enhanced sum pyramid data structure is suggested to improve search efficiency further, which benefits from (1) exact computing in integer form, (2) one more 2-dimensional new resolution and (3) an optimal pair selecting way for constructing the new resolution. Experimental results show that a lot of codewords can be rejected efficiently by using this added new resolution that features lower dimensions and earlier difference check order.

Original languageEnglish
Pages (from-to)764-769
Number of pages6
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number3
Publication statusPublished - 2004 Mar


  • Enhanced sum pyramid
  • Fast search
  • Multi-resolutions
  • Vector quantization

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics


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