Predictive vector quantization using neural networks

M. R. Hashemi, T. H. Yeap, S. Panchanathan

Research output: Contribution to journalConference articlepeer-review

Abstract

In this paper we propose a new predictive vector quantization (PVQ) technique for image and video compression. This technique has been implemented using neural networks. A Kohonen self-organized feature map is used to implement the vector quantizer, while a multi layer perceptron implements the predictor. The proposed technique provides a superior coding performance.

Original languageEnglish (US)
Pages (from-to)834-837
Number of pages4
JournalCanadian Conference on Electrical and Computer Engineering
Volume2
StatePublished - Dec 1 1995
Externally publishedYes
EventProceedings of the 1995 Canadian Conference on Electrical and Computer Engineering. Part 1 (of 2) - Montreal, Can
Duration: Sep 5 1995Sep 8 1995

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering

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