A generalized multiple projection axes method for fast encoding of vector quantization

Zhibin Pan, Koji Kotani, Tadahiro Ohmi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The encoding process of vector quantization (VQ) is computationally very expensive due to a lot of k-dimensional Euclidean distance computations. In order to speed up VQ's encoding process, it is very effective to use a computationally inexpensive distance estimation first to try to reject a candidate codeword instead of an immediate actual distance computation. If a successful rejection is achieved, the computational burden can be reduced because the actual distance computation becomes unnecessary. A very search-efficient VQ encoding method by using multiple projection axes has already been developed in the previous work, which is a general version of the central axis. In this paper, a further generalized version of this previous work is proposed, which can completely remove the constraints for selecting the projection axis in a diagonally symmetric way as required by the previous work. Meanwhile, a theoretical criterion of how to select an optimal projection axis for a candidate codeword is also given. Furthermore, in order to use the generalized multi projection axes simultaneously, the energy accumulation property in an orthogonal space is integrated. Experimental results confirmed the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)1316-1326
Number of pages11
JournalPattern Recognition Letters
Volume26
Issue number9
DOIs
Publication statusPublished - 2005 Jul 1

Keywords

  • Fast encoding
  • Generalized projection axis
  • Vector quantization

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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